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Tran EB, Vonk JMJ, Casaletto K, Zhang D, Christin R, Marathe S, Gorno-Tempini ML, Chang EF, Kleen JK. Development and validation of a nonverbal consensus-based semantic memory paradigm in patients with epilepsy. J Int Neuropsychol Soc 2024:1-9. [PMID: 38616725 DOI: 10.1017/s1355617724000158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
OBJECTIVE Brain areas implicated in semantic memory can be damaged in patients with epilepsy (PWE). However, it is challenging to delineate semantic processing deficits from acoustic, linguistic, and other verbal aspects in current neuropsychological assessments. We developed a new Visual-based Semantic Association Task (ViSAT) to evaluate nonverbal semantic processing in PWE. METHOD The ViSAT was adapted from similar predecessors (Pyramids & Palm Trees test, PPT; Camels & Cactus Test, CCT) comprised of 100 unique trials using real-life color pictures that avoid demographic, cultural, and other potential confounds. We obtained performance data from 23 PWE participants and 24 control participants (Control), along with crowdsourced normative data from 54 Amazon Mechanical Turk (Mturk) workers. RESULTS ViSAT reached a consensus >90% in 91.3% of trials compared to 83.6% in PPT and 82.9% in CCT. A deep learning model demonstrated that visual features of the stimulus images (color, shape; i.e., non-semantic) did not influence top answer choices (p = 0.577). The PWE group had lower accuracy than the Control group (p = 0.019). PWE had longer response times than the Control group in general and this was augmented for the semantic processing (trial answer) stage (both p < 0.001). CONCLUSIONS This study demonstrated performance impairments in PWE that may reflect dysfunction of nonverbal semantic memory circuits, such as seizure onset zones overlapping with key semantic regions (e.g., anterior temporal lobe). The ViSAT paradigm avoids confounds, is repeatable/longitudinal, captures behavioral data, and is open-source, thus we propose it as a strong alternative for clinical and research assessment of nonverbal semantic memory.
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Affiliation(s)
- Edwina B Tran
- Department of Neurology, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Jet M J Vonk
- Department of Neurology, University of California, San Francisco, CA, USA
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Kaitlin Casaletto
- Department of Neurology, University of California, San Francisco, CA, USA
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Da Zhang
- Department of Neurology, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Raphael Christin
- Department of Neurology, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Siddharth Marathe
- Department of Neurology, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Maria Luisa Gorno-Tempini
- Department of Neurology, University of California, San Francisco, CA, USA
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Edward F Chang
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Jonathan K Kleen
- Department of Neurology, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
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2
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Jackson AD, Cohen JL, Phensy AJ, Chang EF, Dawes HE, Sohal VS. Amygdala-hippocampus somatostatin interneuron beta-synchrony underlies a cross-species biomarker of emotional state. Neuron 2024; 112:1182-1195.e5. [PMID: 38266646 PMCID: PMC10994747 DOI: 10.1016/j.neuron.2023.12.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 03/20/2023] [Accepted: 12/22/2023] [Indexed: 01/26/2024]
Abstract
Emotional responses arise from limbic circuits including the hippocampus and amygdala. In the human brain, beta-frequency communication between these structures correlates with self-reported mood and anxiety. However, both the mechanism and significance of this biomarker as a readout vs. driver of emotional state remain unknown. Here, we show that beta-frequency communication between ventral hippocampus and basolateral amygdala also predicts anxiety-related behavior in mice, both on long timescales (∼30 min) and immediately preceding behavioral choices. Genetically encoded voltage indicators reveal that this biomarker reflects synchronization between somatostatin interneurons across both structures. Indeed, synchrony between these neurons dynamically predicts approach-avoidance decisions, and optogenetically shifting the phase of synchronization by just 25 ms is sufficient to bidirectionally modulate anxiety-related behaviors. Thus, back-translation establishes a human biomarker as a causal determinant (not just predictor) of emotional state, revealing a novel mechanism whereby interregional synchronization that is frequency, phase, and cell type specific controls emotional processing.
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Affiliation(s)
- Adam D Jackson
- Department of Psychiatry and Behavioral Sciences, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA; Weill Institute for Neurosciences, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA
| | - Joshua L Cohen
- Department of Psychiatry and Behavioral Sciences, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA; Weill Institute for Neurosciences, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA
| | - Aarron J Phensy
- Department of Psychiatry and Behavioral Sciences, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA; Weill Institute for Neurosciences, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA
| | - Edward F Chang
- Department of Neurological Surgery, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA; Weill Institute for Neurosciences, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA
| | - Heather E Dawes
- Department of Neurological Surgery, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA; Weill Institute for Neurosciences, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA
| | - Vikaas S Sohal
- Department of Psychiatry and Behavioral Sciences, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA; Weill Institute for Neurosciences, Center for Integrative Neuroscience and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94143-0444, USA.
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3
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Blenkmann AO, Leske SL, Llorens A, Lin JJ, Chang EF, Brunner P, Schalk G, Ivanovic J, Larsson PG, Knight RT, Endestad T, Solbakk AK. Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods. J Neurosci Methods 2024; 404:110056. [PMID: 38224783 DOI: 10.1016/j.jneumeth.2024.110056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 11/27/2023] [Accepted: 01/03/2024] [Indexed: 01/17/2024]
Abstract
BACKGROUND Intracranial electrodes are typically localized from post-implantation CT artifacts. Automatic algorithms localizing low signal-to-noise ratio artifacts and high-density electrode arrays are missing. Additionally, implantation of grids/strips introduces brain deformations, resulting in registration errors when fusing post-implantation CT and pre-implantation MR images. Brain-shift compensation methods project electrode coordinates to cortex, but either fail to produce smooth solutions or do not account for brain deformations. NEW METHODS We first introduce GridFit, a model-based fitting approach that simultaneously localizes all electrodes' CT artifacts in grids, strips, or depth arrays. Second, we present CEPA, a brain-shift compensation algorithm combining orthogonal-based projections, spring-mesh models, and spatial regularization constraints. RESULTS We tested GridFit on ∼6000 simulated scenarios. The localization of CT artifacts showed robust performance under difficult scenarios, such as noise, overlaps, and high-density implants (<1 mm errors). Validation with data from 20 challenging patients showed 99% accurate localization of the electrodes (3160/3192). We tested CEPA brain-shift compensation with data from 15 patients. Projections accounted for simple mechanical deformation principles with < 0.4 mm errors. The inter-electrode distances smoothly changed across neighbor electrodes, while changes in inter-electrode distances linearly increased with projection distance. COMPARISON WITH EXISTING METHODS GridFit succeeded in difficult scenarios that challenged available methods and outperformed visual localization by preserving the inter-electrode distance. CEPA registration errors were smaller than those obtained for well-established alternatives. Additionally, modeling resting-state high-frequency activity in five patients further supported CEPA. CONCLUSION GridFit and CEPA are versatile tools for registering intracranial electrode coordinates, providing highly accurate results even in the most challenging implantation scenarios. The methods are implemented in the iElectrodes open-source toolbox.
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Affiliation(s)
- Alejandro Omar Blenkmann
- Department of Psychology, University of Oslo, Norway; RITMO Centre for Interdisciplinary Studies in Rhythm, Time, and Motion, University of Oslo, Norway.
| | - Sabine Liliana Leske
- Department of Musicology, University of Oslo, Norway; RITMO Centre for Interdisciplinary Studies in Rhythm, Time, and Motion, University of Oslo, Norway; Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway
| | - Anaïs Llorens
- Department of Psychology, University of Oslo, Norway; Department of Psychology and the Helen Wills Neuroscience Institute, University of California, Berkeley, USA; Université de Franche-Comté, SUPMICROTECH, CNRS, Institut FEMTO-ST, 25000 Besançon, France; Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team TURC, 75014 Paris, France
| | - Jack J Lin
- Department of Neurology and Center for Mind and Brain, University of California, Davis, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, USA
| | - Peter Brunner
- Department of Neurology, Albany Medical College, Albany, NY, USA; National Center for Adaptive Neurotechnologies, Albany, NY, USA; Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Gerwin Schalk
- Department of Neurology, Albany Medical College, Albany, NY, USA; National Center for Adaptive Neurotechnologies, Albany, NY, USA; Tianqiao and Chrissy Chen Institute, Chen Frontier Lab for Applied Neurotechnology, Shanghai, China; Fudan University/Huashan Hospital, Department of Neurosurgery, Shanghai, China
| | | | | | - Robert Thomas Knight
- Department of Psychology and the Helen Wills Neuroscience Institute, University of California, Berkeley, USA
| | - Tor Endestad
- Department of Psychology, University of Oslo, Norway; RITMO Centre for Interdisciplinary Studies in Rhythm, Time, and Motion, University of Oslo, Norway; Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway
| | - Anne-Kristin Solbakk
- Department of Psychology, University of Oslo, Norway; RITMO Centre for Interdisciplinary Studies in Rhythm, Time, and Motion, University of Oslo, Norway; Department of Neurosurgery, Oslo University Hospital, Norway; Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway
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4
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Hullett PW, Leonard MK, Gorno-Tempini ML, Mandelli ML, Chang EF. Parallel Encoding of Speech in Human Frontal and Temporal Lobes. bioRxiv 2024:2024.03.19.585648. [PMID: 38562883 PMCID: PMC10983886 DOI: 10.1101/2024.03.19.585648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Models of speech perception are centered around a hierarchy in which auditory representations in the thalamus propagate to primary auditory cortex, then to the lateral temporal cortex, and finally through dorsal and ventral pathways to sites in the frontal lobe. However, evidence for short latency speech responses and low-level spectrotemporal representations in frontal cortex raises the question of whether speech-evoked activity in frontal cortex strictly reflects downstream processing from lateral temporal cortex or whether there are direct parallel pathways from the thalamus or primary auditory cortex to the frontal lobe that supplement the traditional hierarchical architecture. Here, we used high-density direct cortical recordings, high-resolution diffusion tractography, and hemodynamic functional connectivity to evaluate for evidence of direct parallel inputs to frontal cortex from low-level areas. We found that neural populations in the frontal lobe show speech-evoked responses that are synchronous or occur earlier than responses in the lateral temporal cortex. These short latency frontal lobe neural populations encode spectrotemporal speech content indistinguishable from spectrotemporal encoding patterns observed in the lateral temporal lobe, suggesting parallel auditory speech representations reaching temporal and frontal cortex simultaneously. This is further supported by white matter tractography and functional connectivity patterns that connect the auditory nucleus of the thalamus (medial geniculate body) and the primary auditory cortex to the frontal lobe. Together, these results support the existence of a robust pathway of parallel inputs from low-level auditory areas to frontal lobe targets and illustrate long-range parallel architecture that works alongside the classical hierarchical speech network model.
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Lee AM, Sturm VE, Dawes H, Krystal AD, Chang EF. Human Anterior Insular Cortex Encodes Multiple Electrophysiological Representations of Anxiety-Related Behaviors. bioRxiv 2024:2024.03.05.583610. [PMID: 38496459 PMCID: PMC10942279 DOI: 10.1101/2024.03.05.583610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Anxiety is a common symptom across psychiatric disorders, but the neurophysiological underpinnings of these symptoms remain unclear. This knowledge gap has prevented the development of circuit-based treatments that can target the neural substrates underlying anxiety. Here, we conducted an electrophysiological mapping study to identify neurophysiological activity associated with self-reported state anxiety in 17 subjects implanted with intracranial electrodes for seizure localization. Participants had baseline anxiety traits ranging from minimal to severe. Subjects volunteered to participate in an anxiety induction task in which they were temporarily exposed to the threat of unpredictable shock during intracranial recordings. We found that anterior insular beta oscillatory activity was selectively elevated during epochs when unpredictable aversive stimuli were being delivered, and this enhancement in insular beta was correlated with increases in self-reported anxiety. Beta oscillatory activity within the frontoinsular region was also evoked selectively by cues-predictive of threat, but not safety cues. Anterior insular gamma responses were less selective than gamma, strongly evoked by aversive stimuli and had weaker responses to salient threat and safety cues. On longer timescales, this gamma signal also correlated with increased skin conductance, a measure of autonomic state. Lastly, we found that direct electrical stimulation of the anterior insular cortex in a subset of subjects elicited self-reported increases in anxiety that were accompanied by enhanced frontoinsular beta oscillations. Together, these findings suggest that electrophysiologic representations of anxiety- related states and behaviors exist within anterior insular cortex. The findings also suggest the potential of reducing anterior insular beta activity as a therapeutic target for refractory anxiety-spectrum disorders.
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6
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Semonche A, Rinaldo L, Lee Y, Dubnicoff T, Matles H, Chou D, Abla A, Chang EF. Microvascular decompression of a vertebral artery loop causing cervical radiculopathy: illustrative case. J Neurosurg Case Lessons 2024; 7:CASE23254. [PMID: 38408348 PMCID: PMC10901126 DOI: 10.3171/case23254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 01/09/2024] [Indexed: 02/28/2024]
Abstract
BACKGROUND Vertebral artery loops are a rare cause of cervical radiculopathy. Surgical options for nerve root decompression include an anterior or posterior approach, with or without additional microvascular decompression. OBSERVATIONS The authors describe a case of a 49-year-old man with a long-standing history of left-sided neck pain and migraines, who was found to have a vertebral artery loop in the left C3-4 neural foramen compressing the left C4 nerve root. The patient underwent a posterior cervical decompression with instrumented fusion and macrovascular decompression of the left C4 nerve root via Teflon felt insertion. In a literature review, we identified 20 similar cases that had also been managed surgically. LESSONS Although the anterior approach is more frequently described in the literature, a posterior approach for nerve compression by a vertebral artery loop is also a safe and effective treatment. The authors report the third case of this surgical approach with a good outcome.
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Affiliation(s)
- Alexa Semonche
- 1Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
| | - Lorenzo Rinaldo
- 1Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
| | - Young Lee
- 1Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
| | - Todd Dubnicoff
- 1Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
| | - Harlan Matles
- 2Menlo Park Concierge Medicine, Menlo Park, California
| | - Dean Chou
- 3Department of Neurological Surgery, Columbia University Vagelos College of Physicians and Surgeons, New York, New York; and
| | - Adib Abla
- 4Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, Florida
| | - Edward F Chang
- 1Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
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7
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Sankaran N, Leonard MK, Theunissen F, Chang EF. Encoding of melody in the human auditory cortex. Sci Adv 2024; 10:eadk0010. [PMID: 38363839 PMCID: PMC10871532 DOI: 10.1126/sciadv.adk0010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 01/17/2024] [Indexed: 02/18/2024]
Abstract
Melody is a core component of music in which discrete pitches are serially arranged to convey emotion and meaning. Perception varies along several pitch-based dimensions: (i) the absolute pitch of notes, (ii) the difference in pitch between successive notes, and (iii) the statistical expectation of each note given prior context. How the brain represents these dimensions and whether their encoding is specialized for music remains unknown. We recorded high-density neurophysiological activity directly from the human auditory cortex while participants listened to Western musical phrases. Pitch, pitch-change, and expectation were selectively encoded at different cortical sites, indicating a spatial map for representing distinct melodic dimensions. The same participants listened to spoken English, and we compared responses to music and speech. Cortical sites selective for music encoded expectation, while sites that encoded pitch and pitch-change in music used the same neural code to represent equivalent properties of speech. Findings reveal how the perception of melody recruits both music-specific and general-purpose sound representations.
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Affiliation(s)
- Narayan Sankaran
- Department of Neurological Surgery, University of California, San Francisco, 675 Nelson Rising Lane, San Francisco, CA 94158, USA
| | - Matthew K. Leonard
- Department of Neurological Surgery, University of California, San Francisco, 675 Nelson Rising Lane, San Francisco, CA 94158, USA
| | - Frederic Theunissen
- Department of Psychology, University of California, Berkeley, 2121 Berkeley Way, Berkeley, CA 94720, USA
| | - Edward F. Chang
- Department of Neurological Surgery, University of California, San Francisco, 675 Nelson Rising Lane, San Francisco, CA 94158, USA
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8
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Morshed RA, Cummins DD, Nguyen MP, Saggi S, Vasudevan HN, Braunstein SE, Goldschmidt E, Chang EF, McDermott MW, Berger MS, Theodosopoulos PV, Daras M, Hervey-Jumper SL, Aghi MK. Genomic alterations associated with postoperative nodular leptomeningeal disease after resection of brain metastases. J Neurosurg 2024; 140:328-337. [PMID: 37548547 DOI: 10.3171/2023.5.jns23460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 05/30/2023] [Indexed: 08/08/2023]
Abstract
OBJECTIVE The relationship between brain metastasis resection and risk of nodular leptomeningeal disease (nLMD) is unclear. This study examined genomic alterations found in brain metastases with the aim of identifying alterations associated with postoperative nLMD in the context of clinical and treatment factors. METHODS A retrospective, single-center study was conducted on patients who underwent resection of brain metastases between 2014 and 2022 and had clinical and genomic data available. Postoperative nLMD was the primary endpoint of interest. Targeted next-generation sequencing of > 500 oncogenes was performed in brain metastases. Cox proportional hazards analyses were performed to identify clinical features and genomic alterations associated with nLMD. RESULTS The cohort comprised 101 patients with tumors originating from multiple cancer types. There were 15 patients with nLMD (14.9% of the cohort) with a median time from surgery to nLMD diagnosis of 8.2 months. Two supervised machine learning algorithms consistently identified CDKN2A/B codeletion and ERBB2 amplification as the top predictors associated with postoperative nLMD across all cancer types. In a multivariate Cox proportional hazards analysis including clinical factors and genomic alterations observed in the cohort, tumor volume (× 10 cm3; HR 1.2, 95% CI 1.01-1.5; p = 0.04), CDKN2A/B codeletion (HR 5.3, 95% CI 1.7-16.9; p = 0.004), and ERBB2 amplification (HR 3.9, 95% CI 1.1-14.4; p = 0.04) were associated with a decreased time to postoperative nLMD. CONCLUSIONS In addition to increased resected tumor volume, ERBB2 amplification and CDKN2A/B deletion were independently associated with an increased risk of postoperative nLMD across multiple cancer types. Additional work is needed to determine if targeted therapy decreases this risk in the postoperative setting.
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Affiliation(s)
| | | | | | | | - Harish N Vasudevan
- Departments of1Neurological Surgery and
- 2Radiation Oncology, University of California, San Francisco, California; and
| | - Steve E Braunstein
- 2Radiation Oncology, University of California, San Francisco, California; and
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9
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Leonard MK, Gwilliams L, Sellers KK, Chung JE, Xu D, Mischler G, Mesgarani N, Welkenhuysen M, Dutta B, Chang EF. Large-scale single-neuron speech sound encoding across the depth of human cortex. Nature 2024; 626:593-602. [PMID: 38093008 PMCID: PMC10866713 DOI: 10.1038/s41586-023-06839-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 11/06/2023] [Indexed: 01/31/2024]
Abstract
Understanding the neural basis of speech perception requires that we study the human brain both at the scale of the fundamental computational unit of neurons and in their organization across the depth of cortex. Here we used high-density Neuropixels arrays1-3 to record from 685 neurons across cortical layers at nine sites in a high-level auditory region that is critical for speech, the superior temporal gyrus4,5, while participants listened to spoken sentences. Single neurons encoded a wide range of speech sound cues, including features of consonants and vowels, relative vocal pitch, onsets, amplitude envelope and sequence statistics. Neurons at each cross-laminar recording exhibited dominant tuning to a primary speech feature while also containing a substantial proportion of neurons that encoded other features contributing to heterogeneous selectivity. Spatially, neurons at similar cortical depths tended to encode similar speech features. Activity across all cortical layers was predictive of high-frequency field potentials (electrocorticography), providing a neuronal origin for macroelectrode recordings from the cortical surface. Together, these results establish single-neuron tuning across the cortical laminae as an important dimension of speech encoding in human superior temporal gyrus.
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Affiliation(s)
- Matthew K Leonard
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Laura Gwilliams
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jason E Chung
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Duo Xu
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Gavin Mischler
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | - Nima Mesgarani
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | | | | | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
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10
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Zhu D, Brookes DH, Busia A, Carneiro A, Fannjiang C, Popova G, Shin D, Donohue KC, Lin LF, Miller ZM, Williams ER, Chang EF, Nowakowski TJ, Listgarten J, Schaffer DV. Optimal trade-off control in machine learning-based library design, with application to adeno-associated virus (AAV) for gene therapy. Sci Adv 2024; 10:eadj3786. [PMID: 38266077 PMCID: PMC10807795 DOI: 10.1126/sciadv.adj3786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 12/22/2023] [Indexed: 01/26/2024]
Abstract
Adeno-associated viruses (AAVs) hold tremendous promise as delivery vectors for gene therapies. AAVs have been successfully engineered-for instance, for more efficient and/or cell-specific delivery to numerous tissues-by creating large, diverse starting libraries and selecting for desired properties. However, these starting libraries often contain a high proportion of variants unable to assemble or package their genomes, a prerequisite for any gene delivery goal. Here, we present and showcase a machine learning (ML) method for designing AAV peptide insertion libraries that achieve fivefold higher packaging fitness than the standard NNK library with negligible reduction in diversity. To demonstrate our ML-designed library's utility for downstream engineering goals, we show that it yields approximately 10-fold more successful variants than the NNK library after selection for infection of human brain tissue, leading to a promising glial-specific variant. Moreover, our design approach can be applied to other types of libraries for AAV and beyond.
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Affiliation(s)
- Danqing Zhu
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA 94720, USA
| | - David H. Brookes
- Biophysics Graduate Group, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Akosua Busia
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Ana Carneiro
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA
| | | | - Galina Popova
- Department of Anatomy, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Psychiatry and Behavioural Sciences, University of California San Francisco, San Francisco, CA 94143, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA 94143, USA
| | - David Shin
- Department of Anatomy, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Psychiatry and Behavioural Sciences, University of California San Francisco, San Francisco, CA 94143, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA 94143, USA
| | - Kevin C. Donohue
- Department of Psychiatry and Behavioural Sciences, University of California San Francisco, San Francisco, CA 94143, USA
- School of Medicine, University of California San Francisco, San Francisco, CA, USA. 94143
- Kavli Institute of Fundamental Neuroscience, University of California San Francisco, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94143, USA
| | - Li F. Lin
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Zachary M. Miller
- Department of Chemistry, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Evan R. Williams
- Department of Chemistry, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Edward F. Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Tomasz J. Nowakowski
- Department of Anatomy, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Psychiatry and Behavioural Sciences, University of California San Francisco, San Francisco, CA 94143, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jennifer Listgarten
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94720, USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - David V. Schaffer
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA 94720, USA
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94720, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
- Innovative Genomics Institute (IGI), University of California, Berkeley, Berkeley, CA 94720, USA
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11
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Ammanuel SG, Kondapavulur S, Lu AY, Breshears JD, Clark JP, Silva AB, Chang EF. Intraoperative cortical stimulation mapping with laryngeal electromyography for the localization of human laryngeal motor cortex. J Neurosurg 2024:1-10. [PMID: 38181494 DOI: 10.3171/2023.10.jns231023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 10/11/2023] [Indexed: 01/07/2024]
Abstract
OBJECTIVE The objectives of this study were to describe the authors' clinical methodology and outcomes for mapping the laryngeal motor cortex (LMC) and define localization of the LMC in a cohort of neurosurgical patients undergoing intraoperative brain mapping. Because of mapping variability across patients, the authors aimed to define the probabilistic distribution of cortical sites that evoke laryngeal movement, as well as adjacent cortical somatotopic representations for the face (mouth), tongue, and hand. METHODS Thirty-six patients underwent left (n = 18) or right (n = 18) craniotomy with asleep motor mapping. For each patient, electromyography (EMG) electrodes were placed in the face, tongue, and hand; a nerve integrity monitor (NIM) endotracheal tube with surface electrodes detected EMG activity from the bilateral vocal folds. After dense cortical stimulation was delivered throughout the sensorimotor cortex, motor responses were then mapped onto a three-dimensional reconstruction of the patient's cortical surfaces for location characterization of the evoked responses. Finally, stimulation sites were transformed into a two-dimensional coordinate system for probabilistic mapping of the stimulation site relative to the central sulcus and sylvian fissure. RESULTS The authors found that the LMC was predominantly localized to a mid precentral gyrus region, dorsal to face representation and surrounding a transverse sulcus ventral to the hand knob. In 14 of 36 patients, the authors identified additional laryngeal responses located ventral to all orofacial representations, providing evidence for dual LMC representations. CONCLUSIONS The authors determined the probabilistic distribution of the LMC. Cortical stimulation mapping with an NIM endotracheal tube is an easy and effective method for mapping the LMC and is simply integrated into the current neuromonitoring methods for brain mapping.
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Affiliation(s)
- Simon G Ammanuel
- 1Department of Neurological Surgery, University of Wisconsin, Madison, Wisconsin
| | | | - Alex Y Lu
- Departments of2Neurological Surgery and
| | - Jonathan D Breshears
- 3Marion Bloch Neuroscience Institute, Saint Luke's Hospital, Kansas City, Missouri; and
| | - John P Clark
- 5Surgical Neurophysiology, University of California, San Francisco, California
| | | | - Edward F Chang
- Departments of2Neurological Surgery and
- 4Center for Integrative Neuroscience, University of California, San Francisco, California
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12
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Sellers KK, Cohen JL, Khambhati AN, Fan JM, Lee AM, Chang EF, Krystal AD. Closed-loop neurostimulation for the treatment of psychiatric disorders. Neuropsychopharmacology 2024; 49:163-178. [PMID: 37369777 PMCID: PMC10700557 DOI: 10.1038/s41386-023-01631-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/31/2023] [Accepted: 06/02/2023] [Indexed: 06/29/2023]
Abstract
Despite increasing prevalence and huge personal and societal burden, psychiatric diseases still lack treatments which can control symptoms for a large fraction of patients. Increasing insight into the neurobiology underlying these diseases has demonstrated wide-ranging aberrant activity and functioning in multiple brain circuits and networks. Together with varied presentation and symptoms, this makes one-size-fits-all treatment a challenge. There has been a resurgence of interest in the use of neurostimulation as a treatment for psychiatric diseases. Initial studies using continuous open-loop stimulation, in which clinicians adjusted stimulation parameters during patient visits, showed promise but also mixed results. Given the periodic nature and fluctuations of symptoms often observed in psychiatric illnesses, the use of device-driven closed-loop stimulation may provide more effective therapy. The use of a biomarker, which is correlated with specific symptoms, to deliver stimulation only during symptomatic periods allows for the personalized therapy needed for such heterogeneous disorders. Here, we provide the reader with background motivating the use of closed-loop neurostimulation for the treatment of psychiatric disorders. We review foundational studies of open- and closed-loop neurostimulation for neuropsychiatric indications, focusing on deep brain stimulation, and discuss key considerations when designing and implementing closed-loop neurostimulation.
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Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joshua L Cohen
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joline M Fan
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | - A Moses Lee
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
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13
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Hadad S, Gupta R, Oberheim Bush NA, Taylor JW, Villanueva-Meyer JE, Young JS, Wu J, Ravindranathan A, Zhang Y, Warrier G, McCoy L, Shai A, Pekmezci M, Perry A, Bollen AW, Phillips JJ, Braunstein SE, Raleigh DR, Theodosopoulos P, Aghi MK, Chang EF, Hervey-Jumper SL, Costello JF, de Groot J, Butowski NA, Clarke JL, Chang SM, Berger MS, Molinaro AM, Solomon DA. "De novo replication repair deficient glioblastoma, IDH-wildtype" is a distinct glioblastoma subtype in adults that may benefit from immune checkpoint blockade. Acta Neuropathol 2023; 147:3. [PMID: 38079020 PMCID: PMC10713691 DOI: 10.1007/s00401-023-02654-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 10/24/2023] [Accepted: 10/24/2023] [Indexed: 12/18/2023]
Abstract
Glioblastoma is a clinically and molecularly heterogeneous disease, and new predictive biomarkers are needed to identify those patients most likely to respond to specific treatments. Through prospective genomic profiling of 459 consecutive primary treatment-naïve IDH-wildtype glioblastomas in adults, we identified a unique subgroup (2%, 9/459) defined by somatic hypermutation and DNA replication repair deficiency due to biallelic inactivation of a canonical mismatch repair gene. The deleterious mutations in mismatch repair genes were often present in the germline in the heterozygous state with somatic inactivation of the remaining allele, consistent with glioblastomas arising due to underlying Lynch syndrome. A subset of tumors had accompanying proofreading domain mutations in the DNA polymerase POLE and resultant "ultrahypermutation". The median age at diagnosis was 50 years (range 27-78), compared with 63 years for the other 450 patients with conventional glioblastoma (p < 0.01). All tumors had histologic features of the giant cell variant of glioblastoma. They lacked EGFR amplification, lacked combined trisomy of chromosome 7 plus monosomy of chromosome 10, and only rarely had TERT promoter mutation or CDKN2A homozygous deletion, which are hallmarks of conventional IDH-wildtype glioblastoma. Instead, they harbored frequent inactivating mutations in TP53, NF1, PTEN, ATRX, and SETD2 and recurrent activating mutations in PDGFRA. DNA methylation profiling revealed they did not align with known reference adult glioblastoma methylation classes, but instead had unique globally hypomethylated epigenomes and mostly classified as "Diffuse pediatric-type high grade glioma, RTK1 subtype, subclass A". Five patients were treated with immune checkpoint blockade, four of whom survived greater than 3 years. The median overall survival was 36.8 months, compared to 15.5 months for the other 450 patients (p < 0.001). We conclude that "De novo replication repair deficient glioblastoma, IDH-wildtype" represents a biologically distinct subtype in the adult population that may benefit from prospective identification and treatment with immune checkpoint blockade.
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Affiliation(s)
- Sara Hadad
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Rohit Gupta
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Nancy Ann Oberheim Bush
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Jennie W Taylor
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Jacob S Young
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Jasper Wu
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Ajay Ravindranathan
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Yalan Zhang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Gayathri Warrier
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Lucie McCoy
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Anny Shai
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Melike Pekmezci
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Arie Perry
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew W Bollen
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Joanna J Phillips
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Steve E Braunstein
- Department of Radiation Oncology, University of California, San Francisco, CA, USA
| | - David R Raleigh
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Radiation Oncology, University of California, San Francisco, CA, USA
| | - Philip Theodosopoulos
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Manish K Aghi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Shawn L Hervey-Jumper
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Joseph F Costello
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - John de Groot
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Nicholas A Butowski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Jennifer L Clarke
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Mitchel S Berger
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
| | - David A Solomon
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA.
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14
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Silva AB, Leonard MK, Oganian Y, D’Esopo E, Krish D, Kopald B, Tran EB, Chang EF, Kleen JK. Interictal epileptiform discharges contribute to word-finding difficulty in epilepsy through multiple cognitive mechanisms. Epilepsia 2023; 64:3266-3278. [PMID: 37753856 PMCID: PMC10841419 DOI: 10.1111/epi.17781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 09/22/2023] [Accepted: 09/25/2023] [Indexed: 09/28/2023]
Abstract
OBJECTIVE Cognitive impairment often impacts quality of life in epilepsy even if seizures are controlled. Word-finding difficulty is particularly prevalent and often attributed to etiological (static, baseline) circuit alterations. We sought to determine whether interictal discharges convey significant superimposed contributions to word-finding difficulty in patients, and if so, through which cognitive mechanism(s). METHODS Twenty-three patients undergoing intracranial monitoring for drug-resistant epilepsy participated in multiple tasks involving word production (auditory naming, short-term verbal free recall, repetition) to probe word-finding difficulty across different cognitive domains. We compared behavioral performance between trials with versus without interictal discharges across six major brain areas and adjusted for intersubject differences using mixed-effects models. We also evaluated for subjective word-finding difficulties through retrospective chart review. RESULTS Subjective word-finding difficulty was reported by the majority (79%) of studied patients preoperatively. During intracranial recordings, interictal epileptiform discharges (IEDs) in the medial temporal lobe were associated with long-term lexicosemantic memory impairments as indexed by auditory naming (p = .009), in addition to their established impact on short-term verbal memory as indexed by free recall (p = .004). Interictal discharges involving the lateral temporal cortex and lateral frontal cortex were associated with delayed reaction time in the auditory naming task (p = .016 and p = .018), as well as phonological working memory impairments as indexed by repetition reaction time (p = .002). Effects of IEDs across anatomical regions were strongly dependent on their precise timing within the task. SIGNIFICANCE IEDs appear to act through multiple cognitive mechanisms to form a convergent basis for the debilitating clinical word-finding difficulty reported by patients with epilepsy. This was particularly notable for medial temporal spikes, which are quite common in adult focal epilepsy. In parallel with the treatment of seizures, the modulation of interictal discharges through emerging pharmacological means and neurostimulation approaches may be an opportunity to help address devastating memory and language impairments in epilepsy.
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Affiliation(s)
- Alexander B. Silva
- Department of Neurosurgery, Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Medical Scientist Training Program, University of California, San Francisco, CA, USA
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - Matthew K. Leonard
- Department of Neurosurgery, Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | | | - Emma D’Esopo
- Department of Neurology, Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Devon Krish
- Department of Neurology, Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Brandon Kopald
- Department of Neurology, Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Edwina B. Tran
- Department of Neurology, Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Edward F. Chang
- Department of Neurosurgery, Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, USA
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - Jonathan K. Kleen
- Department of Neurology, Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, USA
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15
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Li Y, Anumanchipalli GK, Mohamed A, Chen P, Carney LH, Lu J, Wu J, Chang EF. Dissecting neural computations in the human auditory pathway using deep neural networks for speech. Nat Neurosci 2023; 26:2213-2225. [PMID: 37904043 PMCID: PMC10689246 DOI: 10.1038/s41593-023-01468-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 09/13/2023] [Indexed: 11/01/2023]
Abstract
The human auditory system extracts rich linguistic abstractions from speech signals. Traditional approaches to understanding this complex process have used linear feature-encoding models, with limited success. Artificial neural networks excel in speech recognition tasks and offer promising computational models of speech processing. We used speech representations in state-of-the-art deep neural network (DNN) models to investigate neural coding from the auditory nerve to the speech cortex. Representations in hierarchical layers of the DNN correlated well with the neural activity throughout the ascending auditory system. Unsupervised speech models performed at least as well as other purely supervised or fine-tuned models. Deeper DNN layers were better correlated with the neural activity in the higher-order auditory cortex, with computations aligned with phonemic and syllabic structures in speech. Accordingly, DNN models trained on either English or Mandarin predicted cortical responses in native speakers of each language. These results reveal convergence between DNN model representations and the biological auditory pathway, offering new approaches for modeling neural coding in the auditory cortex.
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Affiliation(s)
- Yuanning Li
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China
| | - Gopala K Anumanchipalli
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, USA
| | | | - Peili Chen
- School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materialsand Devices, ShanghaiTech University, Shanghai, China
| | - Laurel H Carney
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA
| | - Junfeng Lu
- Neurologic Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- Brain Function Laboratory, Neurosurgical Institute, Fudan University, Shanghai, China
| | - Jinsong Wu
- Neurologic Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- Brain Function Laboratory, Neurosurgical Institute, Fudan University, Shanghai, China
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
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16
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Raygor KP, Rinaldo L, Dubnicoff TB, Shih T, Chang EF, Abla AA. Awake Craniotomy and Electrocorticography-Guided Extended Lesionectomy of Motor Cortex Cavernoma: 2-Dimensional Operative Video. Oper Neurosurg (Hagerstown) 2023; 25:e286. [PMID: 37441797 DOI: 10.1227/ons.0000000000000837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 05/19/2023] [Indexed: 07/15/2023] Open
Affiliation(s)
- Kunal P Raygor
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Lorenzo Rinaldo
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Todd B Dubnicoff
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Tina Shih
- Department of Neurology, University of California, San Francisco, California, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Adib A Abla
- Department of Neurological Surgery, University of California, San Francisco, California, USA
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17
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Lu J, Li Y, Zhao Z, Liu Y, Zhu Y, Mao Y, Wu J, Chang EF. Neural control of lexical tone production in human laryngeal motor cortex. Nat Commun 2023; 14:6917. [PMID: 37903780 PMCID: PMC10616086 DOI: 10.1038/s41467-023-42175-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 09/28/2023] [Indexed: 11/01/2023] Open
Abstract
In tonal languages, which are spoken by nearly one-third of the world's population, speakers precisely control the tension of vocal folds in the larynx to modulate pitch in order to distinguish words with completely different meanings. The specific pitch trajectories for a given tonal language are called lexical tones. Here, we used high-density direct cortical recordings to determine the neural basis of lexical tone production in native Mandarin-speaking participants. We found that instead of a tone category-selective coding, local populations in the bilateral laryngeal motor cortex (LMC) encode articulatory kinematic information to generate the pitch dynamics of lexical tones. Using a computational model of tone production, we discovered two distinct patterns of population activity in LMC commanding pitch rising and lowering. Finally, we showed that direct electrocortical stimulation of different local populations in LMC evoked pitch rising and lowering during tone production, respectively. Together, these results reveal the neural basis of vocal pitch control of lexical tones in tonal languages.
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Affiliation(s)
- Junfeng Lu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200040, China
- National Center for Neurological Disorders, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Yuanning Li
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, 201210, China
- Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, 94158, USA
- State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, 201210, China
| | - Zehao Zhao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200040, China
- National Center for Neurological Disorders, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Yan Liu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200040, China
- National Center for Neurological Disorders, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Yanming Zhu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- Speech and Hearing Bioscience & Technology Program, Division of Medical Sciences, Harvard University, Boston, MA, 02215, USA
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200040, China.
- National Center for Neurological Disorders, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
| | - Jinsong Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200040, China.
- National Center for Neurological Disorders, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA.
- Weill Institute for Neurosciences, University of California, San Francisco, CA, 94158, USA.
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18
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Windolf C, Yu H, Paulk AC, Meszéna D, Muñoz W, Boussard J, Hardstone R, Caprara I, Jamali M, Kfir Y, Xu D, Chung JE, Sellers KK, Ye Z, Shaker J, Lebedeva A, Raghavan M, Trautmann E, Melin M, Couto J, Garcia S, Coughlin B, Horváth C, Fiáth R, Ulbert I, Movshon JA, Shadlen MN, Churchland MM, Churchland AK, Steinmetz NA, Chang EF, Schweitzer JS, Williams ZM, Cash SS, Paninski L, Varol E. DREDge: robust motion correction for high-density extracellular recordings across species. bioRxiv 2023:2023.10.24.563768. [PMID: 37961359 PMCID: PMC10634799 DOI: 10.1101/2023.10.24.563768] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
High-density microelectrode arrays (MEAs) have opened new possibilities for systems neuroscience in human and non-human animals, but brain tissue motion relative to the array poses a challenge for downstream analyses, particularly in human recordings. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm which is well suited for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from spikes in the action potential (AP) frequency band, DREDge enables automated tracking of motion at high temporal resolution in the local field potential (LFP) frequency band. In human intraoperative recordings, which often feature fast (period <1s) motion, DREDge correction in the LFP band enabled reliable recovery of evoked potentials, and significantly reduced single-unit spike shape variability and spike sorting error. Applying DREDge to recordings made during deep probe insertions in nonhuman primates demonstrated the possibility of tracking probe motion of centimeters across several brain regions while simultaneously mapping single unit electrophysiological features. DREDge reliably delivered improved motion correction in acute mouse recordings, especially in those made with an recent ultra-high density probe. We also implemented a procedure for applying DREDge to recordings made across tens of days in chronic implantations in mice, reliably yielding stable motion tracking despite changes in neural activity across experimental sessions. Together, these advances enable automated, scalable registration of electrophysiological data across multiple species, probe types, and drift cases, providing a stable foundation for downstream scientific analyses of these rich datasets.
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Affiliation(s)
- Charlie Windolf
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
| | - Han Yu
- Zuckerman Institute, Columbia University
- Department of Electrical Engineering, Columbia University
| | - Angelique C Paulk
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Domokos Meszéna
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - William Muñoz
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Julien Boussard
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
| | - Richard Hardstone
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Irene Caprara
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Mohsen Jamali
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Yoav Kfir
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Duo Xu
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Jason E Chung
- Department of Neurological Surgery, University of California San Francisco
| | - Kristin K Sellers
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Zhiwen Ye
- Department of Biological Structure, University of Washington
| | - Jordan Shaker
- Department of Biological Structure, University of Washington
| | | | | | - Eric Trautmann
- Department of Neuroscience, Columbia University Medical Center
- Zuckerman Institute, Columbia University
- Grossman Center for the Statistics of Mind, Columbia University
| | - Max Melin
- David Geffen School of Medicine, University of California Los Angeles
| | - João Couto
- David Geffen School of Medicine, University of California Los Angeles
| | - Samuel Garcia
- Centre National de la Recherche Scientifique, Centre de Recherche en Neurosciences de Lyon
| | - Brian Coughlin
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Csaba Horváth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Richárd Fiáth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - István Ulbert
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | | | - Michael N Shadlen
- Zuckerman Institute, Columbia University
- Howard Hughes Medical Institute
| | | | - Anne K Churchland
- David Geffen School of Medicine, University of California Los Angeles
| | | | - Edward F Chang
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Jeffrey S Schweitzer
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Sydney S Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Liam Paninski
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
- Department of Neuroscience, Columbia University Medical Center
- Grossman Center for the Statistics of Mind, Columbia University
| | - Erdem Varol
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
- Department of Computer Science & Engineering, New York University
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19
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Sankaran N, Leonard MK, Theunissen F, Chang EF. Encoding of melody in the human auditory cortex. bioRxiv 2023:2023.10.17.562771. [PMID: 37905047 PMCID: PMC10614915 DOI: 10.1101/2023.10.17.562771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Melody is a core component of music in which discrete pitches are serially arranged to convey emotion and meaning. Perception of melody varies along several pitch-based dimensions: (1) the absolute pitch of notes, (2) the difference in pitch between successive notes, and (3) the higher-order statistical expectation of each note conditioned on its prior context. While humans readily perceive melody, how these dimensions are collectively represented in the brain and whether their encoding is specialized for music remains unknown. Here, we recorded high-density neurophysiological activity directly from the surface of human auditory cortex while Western participants listened to Western musical phrases. Pitch, pitch-change, and expectation were selectively encoded at different cortical sites, indicating a spatial code for representing distinct dimensions of melody. The same participants listened to spoken English, and we compared evoked responses to music and speech. Cortical sites selective for music were systematically driven by the encoding of expectation. In contrast, sites that encoded pitch and pitch-change used the same neural code to represent equivalent properties of speech. These findings reveal the multidimensional nature of melody encoding, consisting of both music-specific and domain-general sound representations in auditory cortex. Teaser The human brain contains both general-purpose and music-specific neural populations for processing distinct attributes of melody.
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20
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Sankaran N, Moses D, Chiong W, Chang EF. Recommendations for promoting user agency in the design of speech neuroprostheses. Front Hum Neurosci 2023; 17:1298129. [PMID: 37920562 PMCID: PMC10619159 DOI: 10.3389/fnhum.2023.1298129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 10/04/2023] [Indexed: 11/04/2023] Open
Abstract
Brain-computer interfaces (BCI) that directly decode speech from brain activity aim to restore communication in people with paralysis who cannot speak. Despite recent advances, neural inference of speech remains imperfect, limiting the ability for speech BCIs to enable experiences such as fluent conversation that promote agency - that is, the ability for users to author and transmit messages enacting their intentions. Here, we make recommendations for promoting agency based on existing and emerging strategies in neural engineering. The focus is on achieving fast, accurate, and reliable performance while ensuring volitional control over when a decoder is engaged, what exactly is decoded, and how messages are expressed. Additionally, alongside neuroscientific progress within controlled experimental settings, we argue that a parallel line of research must consider how to translate experimental successes into real-world environments. While such research will ultimately require input from prospective users, here we identify and describe design choices inspired by human-factors work conducted in existing fields of assistive technology, which address practical issues likely to emerge in future real-world speech BCI applications.
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Affiliation(s)
- Narayan Sankaran
- Kavli Center for Ethics, Science and the Public, University of California, Berkeley, Berkeley, CA, United States
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - David Moses
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Winston Chiong
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Edward F. Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, United States
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21
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Loube DK, Tan YL, Yoshii-Contreras J, Kleen J, Rao VR, Chang EF, Knowlton RC. Ictal EEG Source Imaging With Supplemental Electrodes. J Clin Neurophysiol 2023:00004691-990000000-00102. [PMID: 37820169 DOI: 10.1097/wnp.0000000000001025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/13/2023] Open
Abstract
INTRODUCTION Noninvasive brain imaging tests play a major role in guiding decision-making and the usage of invasive, costly intracranial electroencephalogram (ICEEG) in the presurgical epilepsy evaluation. This study prospectively examined the concordance in localization between ictal EEG source imaging (ESI) and ICEEG as a reference standard. METHODS Between August 2014 and April 2019, patients during video monitoring with scalp EEG were screened for those with intractable focal epilepsy believed to be amenable to surgical treatment. Additional 10-10 electrodes (total = 31-38 per patient, "31+") were placed over suspected regions of seizure onset in 104 patients. Of 42 patients requiring ICEEG, 30 (mean age 30, range 19-59) had sufficiently localized subsequent intracranial studies to allow comparison of localization between tests. ESI was performed using realistic forward boundary element models used in dipole and distributed source analyses. RESULTS At least partial sublobar concordance between ESI and ICEEG solutions was obtained in 97% of cases, with 73% achieving complete agreement. Median Euclidean distances between ESI and ICEEG solutions ranged from 25 to 30 mm (dipole) and 23 to 38 mm (distributed source). The latter was significantly more accurate with 31+ compared with 21 electrodes (P < 0.01). A difference of ≤25 mm was present in two thirds of the cases. No significant difference was found between dipole and distributed source analyses. CONCLUSIONS A practical method of ictal ESI (nonuniform placement of 31-38 electrodes) yields high accuracy for seizure localization in epilepsy surgery candidates. These results support routine clinical application of ESI in the presurgical evaluation.
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Affiliation(s)
| | - Yee-Leng Tan
- Department of Neurology, National Neuroscience Institute, SingHealth, Republic of Singapore
| | - June Yoshii-Contreras
- Division of Epilepsy, Department of Neurology, University of California San Diego, California, U.S.A; and
| | - Jonathan Kleen
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, U.S.A
| | - Vikram R Rao
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, U.S.A
| | - Edward F Chang
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, U.S.A
| | - Robert C Knowlton
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, U.S.A
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22
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Stephen EP, Li Y, Metzger S, Oganian Y, Chang EF. Latent neural dynamics encode temporal context in speech. Hear Res 2023; 437:108838. [PMID: 37441880 DOI: 10.1016/j.heares.2023.108838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 06/15/2023] [Accepted: 07/03/2023] [Indexed: 07/15/2023]
Abstract
Direct neural recordings from human auditory cortex have demonstrated encoding for acoustic-phonetic features of consonants and vowels. Neural responses also encode distinct acoustic amplitude cues related to timing, such as those that occur at the onset of a sentence after a silent period or the onset of the vowel in each syllable. Here, we used a group reduced rank regression model to show that distributed cortical responses support a low-dimensional latent state representation of temporal context in speech. The timing cues each capture more unique variance than all other phonetic features and exhibit rotational or cyclical dynamics in latent space from activity that is widespread over the superior temporal gyrus. We propose that these spatially distributed timing signals could serve to provide temporal context for, and possibly bind across time, the concurrent processing of individual phonetic features, to compose higher-order phonological (e.g. word-level) representations.
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Affiliation(s)
- Emily P Stephen
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, United States; Department of Mathematics and Statistics, Boston University, Boston, MA 02215, United States
| | - Yuanning Li
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, United States; School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Sean Metzger
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, United States
| | - Yulia Oganian
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, United States; Center for Integrative Neuroscience, University of Tübingen, Tübingen, Germany
| | - Edward F Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, United States.
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23
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Zhang J, Ryu JY, Tirado SR, Dickinson LD, Abosch A, Aziz-Sultan MA, Boulos AS, Barrow DL, Batjer HH, Binyamin TR, Blackburn SL, Chang EF, Chen PR, Colby GP, Cosgrove GR, David CA, Day AL, Folkerth RD, Frerichs KU, Howard BM, Jahromi BR, Niemela M, Ojemann SG, Patel NJ, Richardson RM, Shi X, Valle-Giler EP, Wang AC, Welch BG, Williams Z, Zusman EE, Weiss ST, Du R. A Transcriptomic Comparative Study of Cranial Vasculature. Transl Stroke Res 2023:10.1007/s12975-023-01186-w. [PMID: 37612482 DOI: 10.1007/s12975-023-01186-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 07/06/2023] [Accepted: 08/07/2023] [Indexed: 08/25/2023]
Abstract
In genetic studies of cerebrovascular diseases, the optimal vessels to use as controls remain unclear. Our goal is to compare the transcriptomic profiles among 3 different types of control vessels: superficial temporal artery (STA), middle cerebral arteries (MCA), and arteries from the circle of Willis obtained from autopsies (AU). We examined the transcriptomic profiles of STA, MCA, and AU using RNAseq. We also investigated the effects of using these control groups on the results of the comparisons between aneurysms and the control arteries. Our study showed that when comparing pathological cerebral arteries to control groups, all control groups presented similar responses in the activation of immunological processes, the regulation of intracellular signaling pathways, and extracellular matrix productions, despite their intrinsic biological differences. When compared to STA, AU exhibited upregulation of stress and apoptosis genes, whereas MCA showed upregulation of genes associated with tRNA/rRNA processing. Moreover, our results suggest that the matched case-control study design, which involves control STA samples collected from the same subjects of matched aneurysm samples in our study, can improve the identification of non-inherited disease-associated genes. Given the challenges associated with obtaining fresh intracranial arteries from healthy individuals, our study suggests that using MCA, AU, or paired STA samples as controls are feasible strategies for future large-scale studies investigating cerebral vasculopathies. However, the intrinsic differences of each type of control should be taken into consideration when interpreting the results. With the limitations of each control type, it may be most optimal to use multiple tissues as controls.
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Affiliation(s)
- Jianing Zhang
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - Jee-Yeon Ryu
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - Selena-Rae Tirado
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | | | - Aviva Abosch
- Department of Neurosurgery, University of Nebraska Medical Center, Omaha, NE, USA
| | - M Ali Aziz-Sultan
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - Alan S Boulos
- Department of Neurosurgery, Albany Medical Center, Albany, NY, USA
| | - Daniel L Barrow
- Department of Neurosurgery, Emory University, Atlanta, GA, USA
| | - H Hunt Batjer
- Department of Neurosurgery, University of Texas Southwestern, Dallas, TX, USA
| | | | - Spiros L Blackburn
- Department of Neurosurgery, University of Texas Health Science Center, Houston, TX, USA
| | - Edward F Chang
- Department of Neurosurgery, University of California San Francisco, San Francisco, CA, USA
- Department of Neurosurgery, University of California Los Angeles, Los Angeles, CA, USA
| | - P Roc Chen
- Department of Neurosurgery, University of Texas Health Science Center, Houston, TX, USA
| | - Geoffrey P Colby
- Department of Neurosurgery, University of California Los Angeles, Los Angeles, CA, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - Carlos A David
- Department of Neurosurgery, University of North Carolina Chapel Hill, Chapel Hill, NC, USA
| | - Arthur L Day
- Department of Neurosurgery, University of Texas Health Science Center, Houston, TX, USA
| | - Rebecca D Folkerth
- Department of Forensic Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Kai U Frerichs
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - Brian M Howard
- Department of Neurosurgery, Emory University, Atlanta, GA, USA
| | - Behnam R Jahromi
- Department of Neurosurgery, Helsinki University and Helsinki University Hospital, Helsinki, Finland
| | - Mika Niemela
- Department of Neurosurgery, Helsinki University and Helsinki University Hospital, Helsinki, Finland
| | - Steven G Ojemann
- Department of Neurosurgery, University of Colorado, Denver, CO, USA
| | - Nirav J Patel
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Xiangen Shi
- Department of Neurosurgery, Affiliated Fuxing Hospital, Capital Medical University, Beijing, China
| | | | - Anthony C Wang
- Department of Neurosurgery, University of California Los Angeles, Los Angeles, CA, USA
| | - Babu G Welch
- Department of Neurosurgery, University of Texas Southwestern, Dallas, TX, USA
| | - Ziv Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | | | - Scott T Weiss
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Rose Du
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA.
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24
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Natraj N, Seko S, Abiri R, Yan H, Graham Y, Tu-Chan A, Chang EF, Ganguly K. Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control. bioRxiv 2023:2023.08.11.551770. [PMID: 37645922 PMCID: PMC10462094 DOI: 10.1101/2023.08.11.551770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
The nervous system needs to balance the stability of neural representations with plasticity. It is unclear what is the representational stability of simple actions, particularly those that are well-rehearsed in humans, and how it changes in new contexts. Using an electrocorticography brain-computer interface (BCI), we found that the mesoscale manifold and relative representational distances for a repertoire of simple imagined movements were remarkably stable. Interestingly, however, the manifold's absolute location demonstrated day-to-day drift. Strikingly, representational statistics, especially variance, could be flexibly regulated to increase discernability during BCI control without somatotopic changes. Discernability strengthened with practice and was specific to the BCI, demonstrating remarkable contextual specificity. Accounting for drift, and leveraging the flexibility of representations, allowed neuroprosthetic control of a robotic arm and hand for over 7 months without recalibration. Our study offers insight into how electrocorticography can both track representational statistics across long periods and allow long-term complex neuroprosthetic control.
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Affiliation(s)
- Nikhilesh Natraj
- Dept. of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
- UCSF - Veteran Affairs Medical Center, San Francisco, California, USA
| | - Sarah Seko
- Dept. of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
- UCSF - Veteran Affairs Medical Center, San Francisco, California, USA
| | - Reza Abiri
- Electrical, Computer and Biomedical Engineering, University of Rhode Island, Rhode Island, USA
| | - Hongyi Yan
- Dept. of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
- UCSF - Veteran Affairs Medical Center, San Francisco, California, USA
| | - Yasmin Graham
- Dept. of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
- UCSF - Veteran Affairs Medical Center, San Francisco, California, USA
| | - Adelyn Tu-Chan
- Dept. of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
- UCSF - Veteran Affairs Medical Center, San Francisco, California, USA
| | - Edward F Chang
- Department of Neurological Surgery, Weill Institute for Neuroscience, University of California-San Francisco, San Francisco, California, USA
| | - Karunesh Ganguly
- Dept. of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
- UCSF - Veteran Affairs Medical Center, San Francisco, California, USA
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25
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Cummins DD, Garcia JH, Nguyen MP, Saggi S, Chung JE, Goldschmidt E, Berger MS, Theodosopoulos PV, Chang EF, Daras M, Hervey-Jumper SL, Aghi MK, Morshed RA. Association of CDKN2A alterations with increased postoperative seizure risk after resection of brain metastases. Neurosurg Focus 2023; 55:E14. [PMID: 37527678 DOI: 10.3171/2023.5.focus23133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 05/16/2023] [Indexed: 08/03/2023]
Abstract
OBJECTIVE Seizures are common and significantly disabling for patients with brain metastases (BMs). Although resection can provide seizure control, a subset of patients with BMs may continue to suffer seizures postoperatively. Genomic BM characteristics may influence which patients are at risk for postoperative seizures. This work explores correlations between genomic alterations and risk of postoperative seizures following BM resection. METHODS All patients underwent BM resection at a single institution, with available clinical and sequencing data on more than 500 oncogenes. Clinical seizures were documented pre- and postoperatively. A random forest machine learning classification was used to determine candidate genomic alterations associated with postoperative seizures, and clinical and top genomic variables were correlated with postoperative seizures by using Cox proportional hazards models. RESULTS There were 112 patients with BMs who underwent 114 surgeries and had at least 1 month of postoperative follow-up. Seizures occurred preoperatively in 26 (22.8%) patients and postoperatively in 25 (21.9%). The Engel classification achieved at 6 months for those with preoperative seizures was class I in 13 (50%); class II in 6 (23.1%); class III in 5 (19.2%), and class IV in 2 (7.7%). In those with postoperative seizures, only 8 (32.0%) had seizures preoperatively, and preoperative seizures were not a significant predictor of postoperative seizures (HR 1.84; 95% CI 0.79-4.37; p = 0.156). On random forest classification and multivariate Cox analysis controlling for factors including recurrence, extent of resection, and number of BMs, CDKN2A alterations were associated with postoperative seizures (HR 3.22; 95% CI 1.27-8.16; p = 0.014). Melanoma BMs were associated with higher risk of postoperative seizures compared with all other primary malignancies (HR 5.23; 95% CI 1.37-19.98; p = 0.016). Of 39 BMs with CDKN2A alteration, 35.9% (14/39) had postoperative seizures, compared to 14.7% (11/75) without CDKN2A alteration. The overall rate of postoperative seizures in melanoma BMs was 42.9% (15/35), compared with 12.7% (10/79) for all other primary malignancies. CONCLUSIONS CDKN2A alterations and melanoma primary malignancy are associated with increased postoperative seizure risk following resection of BMs. These results may help guide postoperative seizure prophylaxis in patients undergoing resection of BMs.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Mariza Daras
- Departments of1Neurological Surgery and
- 2Neurology, University of California, San Francisco, California
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26
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Metzger SL, Littlejohn KT, Silva AB, Moses DA, Seaton MP, Wang R, Dougherty ME, Liu JR, Wu P, Berger MA, Zhuravleva I, Tu-Chan A, Ganguly K, Anumanchipalli GK, Chang EF. A high-performance neuroprosthesis for speech decoding and avatar control. Nature 2023; 620:1037-1046. [PMID: 37612505 PMCID: PMC10826467 DOI: 10.1038/s41586-023-06443-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 07/17/2023] [Indexed: 08/25/2023]
Abstract
Speech neuroprostheses have the potential to restore communication to people living with paralysis, but naturalistic speed and expressivity are elusive1. Here we use high-density surface recordings of the speech cortex in a clinical-trial participant with severe limb and vocal paralysis to achieve high-performance real-time decoding across three complementary speech-related output modalities: text, speech audio and facial-avatar animation. We trained and evaluated deep-learning models using neural data collected as the participant attempted to silently speak sentences. For text, we demonstrate accurate and rapid large-vocabulary decoding with a median rate of 78 words per minute and median word error rate of 25%. For speech audio, we demonstrate intelligible and rapid speech synthesis and personalization to the participant's pre-injury voice. For facial-avatar animation, we demonstrate the control of virtual orofacial movements for speech and non-speech communicative gestures. The decoders reached high performance with less than two weeks of training. Our findings introduce a multimodal speech-neuroprosthetic approach that has substantial promise to restore full, embodied communication to people living with severe paralysis.
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Affiliation(s)
- Sean L Metzger
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
- University of California, Berkeley-University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - Kaylo T Littlejohn
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA
| | - Alexander B Silva
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
- University of California, Berkeley-University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - David A Moses
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - Margaret P Seaton
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Ran Wang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - Maximilian E Dougherty
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Jessie R Liu
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
- University of California, Berkeley-University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - Peter Wu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA
| | | | - Inga Zhuravleva
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA
| | - Adelyn Tu-Chan
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Karunesh Ganguly
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Gopala K Anumanchipalli
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA.
- University of California, Berkeley-University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA.
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27
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Uggerly ASV, Cummins DD, Nguyen MP, Saggi S, Goldschmidt E, Chang EF, McDermott MW, Berger MS, Theodosopoulos PV, Hervey-Jumper SL, Daras M, Aghi MK, Morshed RA. Genomic alterations associated with rapid progression of brain metastases. Neurosurg Focus 2023; 55:E15. [PMID: 37527682 DOI: 10.3171/2023.5.focus23214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 05/22/2023] [Indexed: 08/03/2023]
Abstract
OBJECTIVE The aim of this study was to investigate associations between genomic alterations in resected brain metastases and rapid local and distant CNS recurrence identified at the time of postoperative adjuvant radiosurgery. METHODS This was a retrospective study on patients who underwent resection of intracranial brain metastases. Next-generation sequencing of more than 500 coding genes was performed on brain metastasis specimens. Postoperative and preradiosurgery MR images were compared to identify rapid recurrence. Genomic data were associated with rapid local and distant CNS recurrence of brain metastases using nominal regression analyses. RESULTS The cohort contained 92 patients with 92 brain metastases. Thirteen (14.1%) patients had a rapid local recurrence, and 64 (69.6%) patients had rapid distant CNS progression by the time of postoperative adjuvant radiosurgery, which occurred in a median time of 25 days (range 3-85 days) from surgery. RB1 and CTNNB1 mutations were seen in 8.7% and 9.8% of the cohort, respectively, and were associated with a significantly higher risk of rapid local recurrence (RB1: OR 13.6, 95% CI 2.0-92.39, p = 0.008; and CTNNB1: OR 11.97, 95% CI 2.25-63.78, p = 0.004) on multivariate analysis. No genes were found to be associated with rapid distant CNS progression. However, the presence of extracranial disease was significantly associated with a higher risk of rapid distant recurrence on multivariate analysis (OR 4.06, 95% CI 1.08-15.34, p = 0.039). CONCLUSIONS Genomic alterations in RB1 or CTNNB1 were associated with a significantly higher risk of rapid recurrence at the resection site. Although no genomic alterations were associated with rapid distant recurrence, having active extracranial disease was a risk factor for new lesions by the time of adjuvant radiotherapy after resection.
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Affiliation(s)
- Amalie S V Uggerly
- 1Department of Neurosurgery, Odense University Hospital, Odense, Denmark
- 2Department of Clinical Research, University of Southern Denmark, Odense, Denmark; and
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Daniel D Cummins
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Minh P Nguyen
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Satvir Saggi
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Ezequiel Goldschmidt
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Edward F Chang
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Michael W McDermott
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Mitchel S Berger
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Philip V Theodosopoulos
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Shawn L Hervey-Jumper
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Mariza Daras
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Manish K Aghi
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Ramin A Morshed
- 3Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California
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Sellers KK, Khambhati AN, Stapper N, Fan JM, Rao VR, Scangos KW, Chang EF, Krystal AD. Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder. J Vis Exp 2023. [PMID: 37486114 DOI: 10.3791/65177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2023] Open
Abstract
Deep brain stimulation involves the administration of electrical stimulation to targeted brain regions for therapeutic benefit. In the context of major depressive disorder (MDD), most studies to date have administered continuous or open-loop stimulation with promising but mixed results. One factor contributing to these mixed results may stem from when the stimulation is applied. Stimulation administration specific to high-symptom states in a personalized and responsive manner may be more effective at reducing symptoms compared to continuous stimulation and may avoid diminished therapeutic effects related to habituation. Additionally, a lower total duration of stimulation per day is advantageous for reducing device energy consumption. This protocol describes an experimental workflow using a chronically implanted neurostimulation device to achieve closed-loop stimulation for individuals with treatment-refractory MDD. This paradigm hinges on determining a patient-specific neural biomarker that is related to states of high symptoms and programming the device detectors, such that stimulation is triggered by this read-out of symptom state. The described procedures include how to obtain neural recordings concurrent with patient symptom reports, how to use these data in a state-space model approach to differentiate low- and high-symptom states and corresponding neural features, and how to subsequently program and tune the device to deliver closed-loop stimulation therapy.
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Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco; Weill Institute for Neurosciences, University of California, San Francisco;
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California, San Francisco; Weill Institute for Neurosciences, University of California, San Francisco
| | - Noah Stapper
- Weill Institute for Neurosciences, University of California, San Francisco; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
| | - Joline M Fan
- Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology, University of California, San Francisco
| | - Vikram R Rao
- Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology, University of California, San Francisco
| | - Katherine W Scangos
- Weill Institute for Neurosciences, University of California, San Francisco; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco; Weill Institute for Neurosciences, University of California, San Francisco
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
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Oganian Y, Bhaya-Grossman I, Johnson K, Chang EF. Vowel and formant representation in the human auditory speech cortex. Neuron 2023; 111:2105-2118.e4. [PMID: 37105171 PMCID: PMC10330593 DOI: 10.1016/j.neuron.2023.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 02/08/2023] [Accepted: 04/04/2023] [Indexed: 04/29/2023]
Abstract
Vowels, a fundamental component of human speech across all languages, are cued acoustically by formants, resonance frequencies of the vocal tract shape during speaking. An outstanding question in neurolinguistics is how formants are processed neurally during speech perception. To address this, we collected high-density intracranial recordings from the human speech cortex on the superior temporal gyrus (STG) while participants listened to continuous speech. We found that two-dimensional receptive fields based on the first two formants provided the best characterization of vowel sound representation. Neural activity at single sites was highly selective for zones in this formant space. Furthermore, formant tuning is adjusted dynamically for speaker-specific spectral context. However, the entire population of formant-encoding sites was required to accurately decode single vowels. Overall, our results reveal that complex acoustic tuning in the two-dimensional formant space underlies local vowel representations in STG. As a population code, this gives rise to phonological vowel perception.
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Affiliation(s)
- Yulia Oganian
- Department of Neurological Surgery, University of California, San Francisco, 675 Nelson Rising Lane, San Francisco, CA 94158, USA
| | - Ilina Bhaya-Grossman
- Department of Neurological Surgery, University of California, San Francisco, 675 Nelson Rising Lane, San Francisco, CA 94158, USA; University of California, Berkeley-University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA 94720, USA
| | - Keith Johnson
- Department of Linguistics, University of California, Berkeley, Berkeley, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, 675 Nelson Rising Lane, San Francisco, CA 94158, USA.
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30
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Fan JM, Lee AM, Sellers KK, Woodworth K, Makhoul GS, Liu TX, Henderson C, Astudillo Maya DA, Martinez R, Zamanian H, Speidel BA, Khambhati AN, Rao VR, Sugrue LP, Scangos KW, Chang EF, Krystal AD. Intracranial electrical stimulation of corticolimbic sites modulates arousal in humans. Brain Stimul 2023; 16:1072-1082. [PMID: 37385540 PMCID: PMC10634663 DOI: 10.1016/j.brs.2023.06.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 06/23/2023] [Accepted: 06/26/2023] [Indexed: 07/01/2023] Open
Abstract
BACKGROUND Humans routinely shift their sleepiness and wakefulness levels in response to emotional factors. The diversity of emotional factors that modulates sleep-wake levels suggests that the ascending arousal network may be intimately linked with networks that mediate mood. Indeed, while animal studies have identified select limbic structures that play a role in sleep-wake regulation, the breadth of corticolimbic structures that directly modulates arousal in humans remains unknown. OBJECTIVE We investigated whether select regional activation of the corticolimbic network through direct electrical stimulation can modulate sleep-wake levels in humans, as measured by subjective experience and behavior. METHODS We performed intensive inpatient stimulation mapping in two human participants with treatment resistant depression, who underwent intracranial implantation with multi-site, bilateral depth electrodes. Stimulation responses of sleep-wake levels were measured by subjective surveys (i.e. Stanford Sleepiness Scale and visual-analog scale of energy) and a behavioral arousal score. Biomarker analyses of sleep-wake levels were performed by assessing spectral power features of resting-state electrophysiology. RESULTS Our findings demonstrated three regions whereby direct stimulation modulated arousal, including the orbitofrontal cortex (OFC), subgenual cingulate (SGC), and, most robustly, ventral capsule (VC). Modulation of sleep-wake levels was frequency-specific: 100Hz OFC, SGC, and VC stimulation promoted wakefulness, whereas 1Hz OFC stimulation increased sleepiness. Sleep-wake levels were correlated with gamma activity across broad brain regions. CONCLUSIONS Our findings provide evidence for the overlapping circuitry between arousal and mood regulation in humans. Furthermore, our findings open the door to new treatment targets and the consideration of therapeutic neurostimulation for sleep-wake disorders.
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Affiliation(s)
- Joline M Fan
- Department of Neurology, University of California, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
| | - A Moses Lee
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Kristin K Sellers
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Kai Woodworth
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Ghassan S Makhoul
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Tony X Liu
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Catherine Henderson
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Daniela A Astudillo Maya
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Rebecca Martinez
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Hashem Zamanian
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Benjamin A Speidel
- Department of Neurology, University of California, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Ankit N Khambhati
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Vikram R Rao
- Department of Neurology, University of California, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Leo P Sugrue
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA
| | - Katherine W Scangos
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Edward F Chang
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
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31
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Shirvalkar P, Prosky J, Chin G, Ahmadipour P, Sani OG, Desai M, Schmitgen A, Dawes H, Shanechi MM, Starr PA, Chang EF. First-in-human prediction of chronic pain state using intracranial neural biomarkers. Nat Neurosci 2023; 26:1090-1099. [PMID: 37217725 PMCID: PMC10330878 DOI: 10.1038/s41593-023-01338-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 04/18/2023] [Indexed: 05/24/2023]
Abstract
Chronic pain syndromes are often refractory to treatment and cause substantial suffering and disability. Pain severity is often measured through subjective report, while objective biomarkers that may guide diagnosis and treatment are lacking. Also, which brain activity underlies chronic pain on clinically relevant timescales, or how this relates to acute pain, remains unclear. Here four individuals with refractory neuropathic pain were implanted with chronic intracranial electrodes in the anterior cingulate cortex and orbitofrontal cortex (OFC). Participants reported pain metrics coincident with ambulatory, direct neural recordings obtained multiple times daily over months. We successfully predicted intraindividual chronic pain severity scores from neural activity with high sensitivity using machine learning methods. Chronic pain decoding relied on sustained power changes from the OFC, which tended to differ from transient patterns of activity associated with acute, evoked pain states during a task. Thus, intracranial OFC signals can be used to predict spontaneous, chronic pain state in patients.
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Affiliation(s)
- Prasad Shirvalkar
- UCSF Department of Anesthesiology and Perioperative Care, Division of Pain Medicine, University of California San Francisco, San Francisco, CA, USA.
- UCSF Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
- UCSF Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA.
- UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
| | - Jordan Prosky
- UCSF Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Gregory Chin
- UCSF Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Parima Ahmadipour
- Departments of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
| | - Omid G Sani
- Departments of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
| | - Maansi Desai
- Department of Speech, Language, and Hearing Sciences, The University of Texas at Austin, Austin, TX, USA
| | - Ashlyn Schmitgen
- UCSF Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Heather Dawes
- UCSF Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Maryam M Shanechi
- Departments of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
| | - Philip A Starr
- UCSF Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- UCSF Department of Physiology, University of California San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- UCSF Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- UCSF Department of Physiology, University of California San Francisco, San Francisco, CA, USA
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Qi T, Mandelli ML, Pereira CLW, Wellman E, Bogley R, Licata AE, Chang EF, Oganian Y, Gorno-Tempini ML. Anatomical and behavioral correlates of auditory perception in developmental dyslexia. bioRxiv 2023:2023.05.09.539936. [PMID: 37214875 PMCID: PMC10197694 DOI: 10.1101/2023.05.09.539936] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Developmental dyslexia (DD) is typically associated with difficulties in manipulating speech sounds and, sometimes, in basic auditory processing. However, the neuroanatomical correlates of auditory difficulties in DD and their contribution to individual clinical phenotypes are still unknown. Recent intracranial electrocorticography (ECoG) findings associated processing of sound amplitude rises and speech sounds with posterior and middle superior temporal gyrus (STG), respectively. We hypothesize that regional STG anatomy will relate to specific auditory abilities in DD and that auditory processing abilities will relate to behavioral difficulties. One hundred and ten children (78 DD, 32 typically developing, age 7-15 years) completed amplitude rise time (ART) and speech in noise discrimination (SiN) tasks. They also underwent a battery of cognitive tests. Anatomical MRI scans were used to identify regions in which local cortical gyrification complexity correlated with auditory tasks in DD. Behaviorally, ART but not SiN performance was impaired in DD. Neurally, ART and SiN performance correlated with gyrification in posterior STG and middle STG, respectively. Furthermore, ART significantly contributed to reading impairments in DD, while SiN explained variance in phonological awareness only. Finally, ART and SiN performance was not correlated, and each task was correlated with distinct neuropsychological measures, such that distinct DD subgroups could be identified. Overall, we provide a direct link between the neurodevelopment of the left STG and individual variability in auditory processing abilities in DD. The dissociation between speech and non-speech deficits supports distinct DD phenotypes and implicates different approaches to interventions.
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Affiliation(s)
- Ting Qi
- Department of Neurology, University of California San Francisco, United States
- UCSF Dyslexia Center, University of California San Francisco, United States
| | - Maria Luisa Mandelli
- Department of Neurology, University of California San Francisco, United States
- UCSF Dyslexia Center, University of California San Francisco, United States
| | - Christa L. Watson Pereira
- Department of Neurology, University of California San Francisco, United States
- UCSF Dyslexia Center, University of California San Francisco, United States
| | - Emma Wellman
- Department of Neurology, University of California San Francisco, United States
- UCSF Dyslexia Center, University of California San Francisco, United States
| | - Rian Bogley
- Department of Neurology, University of California San Francisco, United States
- UCSF Dyslexia Center, University of California San Francisco, United States
| | - Abigail E. Licata
- Department of Neurology, University of California San Francisco, United States
- UCSF Dyslexia Center, University of California San Francisco, United States
| | - Edward F. Chang
- Department of Neurological Surgery, University of California San Francisco, United States
| | - Yulia Oganian
- Department of Neurological Surgery, University of California San Francisco, United States
- Center for Integrative Neuroscience, University of Tübingen, Tübingen, Germany
| | - Maria Luisa Gorno-Tempini
- Department of Neurology, University of California San Francisco, United States
- UCSF Dyslexia Center, University of California San Francisco, United States
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Dreyer AM, Michalke L, Perry A, Chang EF, Lin JJ, Knight RT, Rieger JW. Grasp-specific high-frequency broadband mirror neuron activity during reach-and-grasp movements in humans. Cereb Cortex 2023; 33:6291-6298. [PMID: 36562997 PMCID: PMC10183732 DOI: 10.1093/cercor/bhac504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 11/30/2022] [Accepted: 12/01/2022] [Indexed: 12/24/2022] Open
Abstract
Broadly congruent mirror neurons, responding to any grasp movement, and strictly congruent mirror neurons, responding only to specific grasp movements, have been reported in single-cell studies with primates. Delineating grasp properties in humans is essential to understand the human mirror neuron system with implications for behavior and social cognition. We analyzed electrocorticography data from a natural reach-and-grasp movement observation and delayed imitation task with 3 different natural grasp types of everyday objects. We focused on the classification of grasp types from high-frequency broadband mirror activation patterns found in classic mirror system areas, including sensorimotor, supplementary motor, inferior frontal, and parietal cortices. Classification of grasp types was successful during movement observation and execution intervals but not during movement retention. Our grasp type classification from combined and single mirror electrodes provides evidence for grasp-congruent activity in the human mirror neuron system potentially arising from strictly congruent mirror neurons.
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Affiliation(s)
- Alexander M Dreyer
- Department of Psychology, Carl von Ossietzky University Oldenburg, Oldenburg 26129, Germany
| | - Leo Michalke
- Department of Psychology, Carl von Ossietzky University Oldenburg, Oldenburg 26129, Germany
| | - Anat Perry
- Department of Psychology, Hebrew University of Jerusalem, Jerusalem 91905, Israel
| | - Edward F Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, United States
| | - Jack J Lin
- Department of Biomedical Engineering and the Comprehensive Epilepsy Program, Department of Neurology, University of California, Irvine, CA 92868, United States
| | - Robert T Knight
- Department of Psychology and the Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, United States
| | - Jochem W Rieger
- Department of Psychology, Carl von Ossietzky University Oldenburg, Oldenburg 26129, Germany
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Hitti FL, Widge AS, Riva-Posse P, Malone DA, Okun MS, Shanechi MM, Foote KD, Lisanby SH, Ankudowich E, Chivukula S, Chang EF, Gunduz A, Hamani C, Feinsinger A, Kubu CS, Chiong W, Chandler JA, Carbunaru R, Cheeran B, Raike RS, Davis RA, Halpern CH, Vanegas-Arroyave N, Markovic D, Bick SK, McIntyre CC, Richardson RM, Dougherty DD, Kopell BH, Sweet JA, Goodman WK, Sheth SA, Pouratian N. Future directions in psychiatric neurosurgery: Proceedings of the 2022 American Society for Stereotactic and Functional Neurosurgery meeting on surgical neuromodulation for psychiatric disorders. Brain Stimul 2023; 16:867-878. [PMID: 37217075 DOI: 10.1016/j.brs.2023.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 05/10/2023] [Accepted: 05/14/2023] [Indexed: 05/24/2023] Open
Abstract
OBJECTIVE Despite advances in the treatment of psychiatric diseases, currently available therapies do not provide sufficient and durable relief for as many as 30-40% of patients. Neuromodulation, including deep brain stimulation (DBS), has emerged as a potential therapy for persistent disabling disease, however it has not yet gained widespread adoption. In 2016, the American Society for Stereotactic and Functional Neurosurgery (ASSFN) convened a meeting with leaders in the field to discuss a roadmap for the path forward. A follow-up meeting in 2022 aimed to review the current state of the field and to identify critical barriers and milestones for progress. DESIGN The ASSFN convened a meeting on June 3, 2022 in Atlanta, Georgia and included leaders from the fields of neurology, neurosurgery, and psychiatry along with colleagues from industry, government, ethics, and law. The goal was to review the current state of the field, assess for advances or setbacks in the interim six years, and suggest a future path forward. The participants focused on five areas of interest: interdisciplinary engagement, regulatory pathways and trial design, disease biomarkers, ethics of psychiatric surgery, and resource allocation/prioritization. The proceedings are summarized here. CONCLUSION The field of surgical psychiatry has made significant progress since our last expert meeting. Although weakness and threats to the development of novel surgical therapies exist, the identified strengths and opportunities promise to move the field through methodically rigorous and biologically-based approaches. The experts agree that ethics, law, patient engagement, and multidisciplinary teams will be critical to any potential growth in this area.
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Affiliation(s)
- Frederick L Hitti
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA.
| | - Alik S Widge
- Department of Psychiatry and Behavioral Sciences, University of Minnesota-Twin Cities, Minneapolis, MN, USA
| | - Patricio Riva-Posse
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Donald A Malone
- Department of Psychiatry, Cleveland Clinic Lerner College of Medicine, Cleveland, OH, USA
| | - Michael S Okun
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, Gainesville, FL, USA
| | - Maryam M Shanechi
- Departments of Electrical and Computer Engineering and Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Kelly D Foote
- Department of Neurosurgery, Norman Fixel Institute for Neurological Diseases, Gainesville, FL, USA
| | - Sarah H Lisanby
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Elizabeth Ankudowich
- Division of Translational Research, National Institute of Mental Health, Bethesda, MD, USA
| | - Srinivas Chivukula
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Aysegul Gunduz
- Department of Biomedical Engineering and Fixel Institute for Neurological Disorders, University of Florida, Gainesville, FL, USA
| | - Clement Hamani
- Sunnybrook Research Institute, Hurvitz Brain Sciences Centre, Harquail Centre for Neuromodulation, Division of Neurosurgery, University of Toronto, Toronto, Canada
| | - Ashley Feinsinger
- Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Cynthia S Kubu
- Department of Neurology, Cleveland Clinic and Case Western Reserve University, School of Medicine, Cleveland, OH, USA
| | - Winston Chiong
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Jennifer A Chandler
- Faculty of Law, University of Ottawa, Ottawa, ON, USA; Affiliate Investigator, Bruyère Research Institute, Ottawa, ON, USA
| | | | | | - Robert S Raike
- Global Research Organization, Medtronic Inc. Neuromodulation, Minneapolis, MN, USA
| | - Rachel A Davis
- Departments of Psychiatry and Neurosurgery, University of Colorado Anschutz, Aurora, CO, USA
| | - Casey H Halpern
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; The Cpl Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | | | - Dejan Markovic
- Department of Electrical Engineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Sarah K Bick
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Cameron C McIntyre
- Departments of Biomedical Engineering and Neurosurgery, Duke University, Durham, NC, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Brian H Kopell
- Department of Neurosurgery, Center for Neuromodulation, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jennifer A Sweet
- Department of Neurosurgery, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Wayne K Goodman
- Department of Psychiatry and Behavior Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Nader Pouratian
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
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Krishna S, Choudhury A, Keough MB, Seo K, Ni L, Kakaizada S, Lee A, Aabedi A, Popova G, Lipkin B, Cao C, Nava Gonzales C, Sudharshan R, Egladyous A, Almeida N, Zhang Y, Molinaro AM, Venkatesh HS, Daniel AGS, Shamardani K, Hyer J, Chang EF, Findlay A, Phillips JJ, Nagarajan S, Raleigh DR, Brang D, Monje M, Hervey-Jumper SL. Glioblastoma remodelling of human neural circuits decreases survival. Nature 2023; 617:599-607. [PMID: 37138086 PMCID: PMC10191851 DOI: 10.1038/s41586-023-06036-1] [Citation(s) in RCA: 53] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 03/31/2023] [Indexed: 05/05/2023]
Abstract
Gliomas synaptically integrate into neural circuits1,2. Previous research has demonstrated bidirectional interactions between neurons and glioma cells, with neuronal activity driving glioma growth1-4 and gliomas increasing neuronal excitability2,5-8. Here we sought to determine how glioma-induced neuronal changes influence neural circuits underlying cognition and whether these interactions influence patient survival. Using intracranial brain recordings during lexical retrieval language tasks in awake humans together with site-specific tumour tissue biopsies and cell biology experiments, we find that gliomas remodel functional neural circuitry such that task-relevant neural responses activate tumour-infiltrated cortex well beyond the cortical regions that are normally recruited in the healthy brain. Site-directed biopsies from regions within the tumour that exhibit high functional connectivity between the tumour and the rest of the brain are enriched for a glioblastoma subpopulation that exhibits a distinct synaptogenic and neuronotrophic phenotype. Tumour cells from functionally connected regions secrete the synaptogenic factor thrombospondin-1, which contributes to the differential neuron-glioma interactions observed in functionally connected tumour regions compared with tumour regions with less functional connectivity. Pharmacological inhibition of thrombospondin-1 using the FDA-approved drug gabapentin decreases glioblastoma proliferation. The degree of functional connectivity between glioblastoma and the normal brain negatively affects both patient survival and performance in language tasks. These data demonstrate that high-grade gliomas functionally remodel neural circuits in the human brain, which both promotes tumour progression and impairs cognition.
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Affiliation(s)
- Saritha Krishna
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Abrar Choudhury
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | | | - Kyounghee Seo
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Lijun Ni
- Department of Neurology, Stanford University, Stanford, CA, USA
| | - Sofia Kakaizada
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Anthony Lee
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Alexander Aabedi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Galina Popova
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Benjamin Lipkin
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Caroline Cao
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Cesar Nava Gonzales
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Rasika Sudharshan
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew Egladyous
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Nyle Almeida
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Yalan Zhang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | | | - Andy G S Daniel
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | | | - Jeanette Hyer
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Anne Findlay
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Joanna J Phillips
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Srikantan Nagarajan
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - David R Raleigh
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
- Department of Radiation Oncology, University of California, San Francisco, San Francisco, USA
| | - David Brang
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Michelle Monje
- Department of Neurology, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford, CA, USA
| | - Shawn L Hervey-Jumper
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
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Patel A, Mummaneni PV, Zheng J, Rosner BI, Thombley R, Sorour O, Theodosopoulos PV, Aghi MK, Berger MS, Chang EF, Chou D, Manley GT, DiGiorgio AM. On-Call Junior Neurosurgery Residents Spend 9 hours of Their On-Call Shift Actively Using the Electronic Health Record. Neurosurgery 2023; 92:870-875. [PMID: 36729755 DOI: 10.1227/neu.0000000000002288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 10/03/2022] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND The electronic health record (EHR) is central to clinical workflow, yet few studies to date have explored EHR usage patterns among neurosurgery trainees. OBJECTIVE To describe the amount of EHR time spent by postgraduate year (PGY)-2 and PGY-3 neurosurgery residents during on-call days and the distribution of EHR activities in which they engage. METHODS This cohort study used the EHR audit logs, time-stamped records of user activities, to review EHR usage of PGY-2 and PGY-3 neurosurgery residents scheduled for 1 or more on-call days across 2 calendar years at the University of California San Francisco. We focused on the PGY-2 and PGY-3, which, in our training program, represent the primary participants in the in-house on-call pool. RESULTS Over 723 call days, 12 different residents took at least one on-call shift. The median (IQR) number of minutes that residents spent per on-call shift actively using the EHR was 536.8 (203.5), while interacting with an average (SD) of 68.1 (14.7) patient charts. There was no significant difference between Active EHR Time between residents as PGY-2 and PGY-3 on paired t -tests. Residents spent the most time on the following EHR activities: patient reports, notes, order management, patient list, and chart review. CONCLUSION Residents spent, on average, 9 hours of their on-call shift actively using the EHR, and there was no improved efficiency as residents gained experience. We noted several areas of administrative EHR burden, which could be reduced.
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Affiliation(s)
- Arati Patel
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Praveen V Mummaneni
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Jeff Zheng
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Benjamin I Rosner
- Center for Clinical Informatics and Improvement Research, University of California, San Francisco, San Francisco, California, USA
- Institute for Health Policy Studies, University of California, San Francisco, San Francisco, California, USA
| | - Robert Thombley
- Center for Clinical Informatics and Improvement Research, University of California, San Francisco, San Francisco, California, USA
- Institute for Health Policy Studies, University of California, San Francisco, San Francisco, California, USA
| | - Omar Sorour
- University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - Philip V Theodosopoulos
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Manish K Aghi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Mitchel S Berger
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Dean Chou
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Geoffrey T Manley
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
- Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital, San Francisco, California, USA
| | - Anthony M DiGiorgio
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
- Institute for Health Policy Studies, University of California, San Francisco, San Francisco, California, USA
- Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital, San Francisco, California, USA
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Sellers KK, Stapper N, Astudillo Maya DA, Henderson C, Khambhati AN, Fan JM, Rao VR, Scangos KW, Chang EF, Krystal AD. Changes in intracranial neurophysiology associated with acute COVID-19 infection. Clin Neurophysiol 2023; 148:29-31. [PMID: 36791656 PMCID: PMC9896881 DOI: 10.1016/j.clinph.2023.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 01/28/2023] [Indexed: 02/05/2023]
Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
| | - Noah Stapper
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Daniela A Astudillo Maya
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Catherine Henderson
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Joline M Fan
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Vikram R Rao
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Katherine W Scangos
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
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Winkler EA, Kim C, Ross J, Garcia J, Gil E, Oh I, Chen L, Wu D, Catapano J, Raygor KP, Narsinh K, Kim H, Weinsheimer S, Cooke D, Walcott BP, Lawton MT, Gupta N, Zlokovic B, Chang EF, Abla AA, Lim DA, Nowakowski T. 385 A Cell Resolution Atlas of the Human Cerebrovasculature Reveals Angiogenic and Inflammatory Cell Programs in Arteriovenous Malformations. Neurosurgery 2023. [DOI: 10.1227/neu.0000000000002375_385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
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Levy DF, Silva AB, Scott TL, Liu JR, Harper S, Zhao L, Hullett PW, Kurteff G, Wilson SM, Leonard MK, Chang EF. Apraxia of speech with phonological alexia and agraphia following resection of the left middle precentral gyrus: illustrative case. J Neurosurg Case Lessons 2023; 5:CASE22504. [PMID: 37014023 PMCID: PMC10550577 DOI: 10.3171/case22504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 01/23/2023] [Indexed: 03/29/2023]
Abstract
BACKGROUND Apraxia of speech is a disorder of speech-motor planning in which articulation is effortful and error-prone despite normal strength of the articulators. Phonological alexia and agraphia are disorders of reading and writing disproportionately affecting unfamiliar words. These disorders are almost always accompanied by aphasia. OBSERVATIONS A 36-year-old woman underwent resection of a grade IV astrocytoma based in the left middle precentral gyrus, including a cortical site associated with speech arrest during electrocortical stimulation mapping. Following surgery, she exhibited moderate apraxia of speech and difficulty with reading and spelling, both of which improved but persisted 6 months after surgery. A battery of speech and language assessments was administered, revealing preserved comprehension, naming, cognition, and orofacial praxis, with largely isolated deficits in speech-motor planning and the spelling and reading of nonwords. LESSONS This case describes a specific constellation of speech-motor and written language symptoms-apraxia of speech, phonological agraphia, and phonological alexia in the absence of aphasia-which the authors theorize may be attributable to disruption of a single process of "motor-phonological sequencing." The middle precentral gyrus may play an important role in the planning of motorically complex phonological sequences for production, independent of output modality.
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Affiliation(s)
- Deborah F. Levy
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
| | - Alexander B. Silva
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
- University of California Berkeley - University of California San Francisco Graduate Program in Bioengineering, Berkeley, California
- Medical Scientist Training Program, University of California, San Francisco, California
| | - Terri L. Scott
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
| | - Jessie R. Liu
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
- University of California Berkeley - University of California San Francisco Graduate Program in Bioengineering, Berkeley, California
| | - Sarah Harper
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
| | - Lingyun Zhao
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
| | - Patrick W. Hullett
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
| | - Garret Kurteff
- Department of Speech, Language, and Hearing Sciences, University of Texas Austin, Austin, Texas; and
| | - Stephen M. Wilson
- Department of Hearing and Speech Sciences, Vanderbilt University, Nashville, Tennessee
| | - Matthew K. Leonard
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
| | - Edward F. Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
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Andrews JP, Cahn N, Speidel BA, Chung JE, Levy DF, Wilson SM, Berger MS, Chang EF. Dissociation of Broca's area from Broca's aphasia in patients undergoing neurosurgical resections. J Neurosurg 2023; 138:847-857. [PMID: 35932264 PMCID: PMC9899289 DOI: 10.3171/2022.6.jns2297] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 06/15/2022] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Broca's aphasia is a syndrome of impaired fluency with retained comprehension. The authors used an unbiased algorithm to examine which neuroanatomical areas are most likely to result in Broca's aphasia following surgical lesions. METHODS Patients were prospectively evaluated with standardized language batteries before and after surgery. Broca's area was defined anatomically as the pars opercularis and triangularis of the inferior frontal gyrus. Broca's aphasia was defined by the Western Aphasia Battery language assessment. Resections were outlined from MRI scans to construct 3D volumes of interest. These were aligned using a nonlinear transformation to Montreal Neurological Institute brain space. A voxel-based lesion-symptom mapping (VLSM) algorithm was used to test for areas statistically associated with Broca's aphasia when incorporated into a resection, as well as areas associated with deficits in fluency independent of Western Aphasia Battery classification. Postoperative MRI scans were reviewed in blinded fashion to estimate the percentage resection of Broca's area compared to areas identified using the VLSM algorithm. RESULTS A total of 289 patients had early language evaluations, of whom 19 had postoperative Broca's aphasia. VLSM analysis revealed an area that was highly correlated (p < 0.001) with Broca's aphasia, spanning ventral sensorimotor cortex and supramarginal gyri, as well as extending into subcortical white matter tracts. Reduced fluency scores were significantly associated with an overlapping region of interest. The fluency score was negatively correlated with fraction of resected precentral, postcentral, and supramarginal components of the VLSM area. CONCLUSIONS Broca's aphasia does not typically arise from neurosurgical resections in Broca's area. When Broca's aphasia does occur after surgery, it is typically in the early postoperative period, improves by 1 month, and is associated with resections of ventral sensorimotor cortex and supramarginal gyri.
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Affiliation(s)
- John P. Andrews
- Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California; and
| | - Nathan Cahn
- Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California; and
| | - Benjamin A. Speidel
- Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California; and
| | - Jason E. Chung
- Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California; and
| | - Deborah F. Levy
- Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California; and
| | - Stephen M. Wilson
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Mitchel S. Berger
- Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California; and
| | - Edward F. Chang
- Department of Neurological Surgery, University of California, San Francisco, School of Medicine, San Francisco, California; and
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Lee AT, Nichols NM, Speidel BA, Fan JM, Cajigas I, Knowlton RC, Chang EF. Modern intracranial electroencephalography for epilepsy localization with combined subdural grid and depth electrodes with low and improved hemorrhagic complication rates. J Neurosurg 2023; 138:821-827. [PMID: 35901681 DOI: 10.3171/2022.5.jns221118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 05/19/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Recent trends have moved from subdural grid electrocorticography (ECoG) recordings toward stereo-electroencephalography (SEEG) depth electrodes for intracranial localization of seizures, in part because of perceived morbidity from subdural grid and strip electrodes. For invasive epilepsy monitoring, the authors describe the outcomes of a hybrid approach, whereby patients receive a combination of subdural grids, strips, and frameless stereotactic depth electrode implantations through a craniotomy. Evolution of surgical techniques was employed to reduce complications. In this study, the authors review the surgical hemorrhage and functional outcomes of this hybrid approach. METHODS A retrospective review was performed of consecutive patients who underwent hybrid implantation from July 2012 to May 2022 at an academic epilepsy center by a single surgeon. Outcomes included hemorrhagic and nonhemorrhagic complications, neurological deficits, length of monitoring, and number of electrodes. RESULTS A total of 137 consecutive procedures were performed; 113 procedures included both subdural and depth electrodes. The number of depth electrodes and electrode contacts did not increase the risk of hemorrhage. A mean of 1.9 ± 0.8 grid, 4.9 ± 2.1 strip, and 3.0 ± 1.9 depth electrodes were implanted, for a mean of 125.1 ± 32 electrode contacts per patient. The overall incidence of hematomas over the study period was 5.1% (7 patients) and decreased significantly with experience and the introduction of new surgical techniques. The incidence of hematomas in the last 4 years of the study period was 0% (55 patients). Symptomatic hematomas were all delayed and extra-axial. These patients required surgical evacuation, and there were no cases of hematoma recurrence. All neurological deficits related to hematomas were temporary and were resolved at hospital discharge. There were 2 nonhemorrhagic complications. The mean duration of monitoring was 7.3 ± 3.2 days. Seizures were localized in 95% of patients, with 77% of patients eventually undergoing resection and 17% undergoing responsive neurostimulation device implantation. CONCLUSIONS In the authors' institutional experience, craniotomy-based subdural and depth electrode implantation was associated with low hemorrhage rates and no permanent morbidity. The rate of hemorrhage can be nearly eliminated with surgical experience and specific techniques. The decision to use subdural electrodes or SEEG should be tailored to the patient's unique pathology and surgeon experience.
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Affiliation(s)
| | | | | | - Joline M Fan
- 2Neurology, University of California, San Francisco, California
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Fan JM, Khambhati AN, Sellers KK, Stapper N, Maya DA, Kunwar E, Henderson C, Sugrue LP, Scangos KW, Chang EF, Rao VR, Krystal AD. Epileptiform discharges triggered with direct electrical stimulation for treatment-resistant depression: Factors that modulate risk and treatment considerations. Brain Stimul 2023; 16:462-465. [PMID: 36773780 PMCID: PMC10627048 DOI: 10.1016/j.brs.2023.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 02/05/2023] [Indexed: 02/11/2023] Open
Affiliation(s)
- Joline M Fan
- Department of Neurology, University of California, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
| | - Ankit N Khambhati
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Kristin K Sellers
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Noah Stapper
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | | | - Elysha Kunwar
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | | | - Leo P Sugrue
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Katherine W Scangos
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Edward F Chang
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Vikram R Rao
- Department of Neurology, University of California, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA
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Morshed RA, Saggi S, Cummins DD, Molinaro AM, Young JS, Viner JA, Villanueva-Meyer JE, Goldschmidt E, Boreta L, Braunstein SE, Chang EF, McDermott MW, Berger MS, Theodosopoulos PV, Hervey-Jumper SL, Aghi MK, Daras M. Identification of risk factors associated with leptomeningeal disease after resection of brain metastases. J Neurosurg 2023:1-12. [PMID: 36640095 DOI: 10.3171/2022.12.jns221490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 12/07/2022] [Indexed: 01/15/2023]
Abstract
OBJECTIVE Resection of brain metastases (BMs) may be associated with increased risk of leptomeningeal disease (LMD). This study examined rates and predictors of LMD, including imaging subtypes, in patients who underwent resection of a BM followed by postoperative radiation. METHODS A retrospective, single-center study was conducted examining overall LMD, classic LMD (cLMD), and nodular LMD (nLMD) risk. Logistic regression, Cox proportional hazards, and random forest analyses were performed to identify risk factors associated with LMD. RESULTS Of the 217 patients in the cohort, 47 (21.7%) developed postoperative LMD, with 19 cases (8.8%) of cLMD and 28 cases (12.9%) of nLMD. Six-, 12-, and 24-month LMD-free survival rates were 92.3%, 85.6%, and 71.4%, respectively. Patients with cLMD had worse survival outcomes from the date of LMD diagnosis compared with nLMD (median 2.4 vs 6.9 months, p = 0.02, log-rank test). Cox proportional hazards analysis identified cerebellar/insular/occipital location (hazard ratio [HR] 3.25, 95% confidence interval [CI] 1.73-6.11, p = 0.0003), absence of extracranial disease (HR 2.49, 95% CI 1.27-4.88, p = 0.008), and ventricle contact (HR 2.82, 95% CI 1.5-5.3, p = 0.001) to be associated with postoperative LMD. A predictive model using random forest analysis with an area under the receiver operating characteristic curve of 0.87 in a test cohort identified tumor location, systemic disease status, and tumor volume as the most important factors associated with LMD. CONCLUSIONS Tumor location, absence of extracranial disease at the time of surgery, ventricle contact, and increased tumor volume were associated with LMD. Further work is needed to determine whether escalating therapies in patients at risk of LMD prevents disease dissemination.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Lauren Boreta
- 3Radiation Oncology, University of California, San Francisco, California and
| | - Steve E Braunstein
- 3Radiation Oncology, University of California, San Francisco, California and
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Morshed RA, Nguyen MP, Cummins DD, Saggi S, Young JS, Haddad AF, Goldschmidt E, Chang EF, McDermott MW, Berger MS, Theodosopoulos PV, Hervey-Jumper SL, Daras M, Aghi MK. CDKN2A/B co-deletion is associated with increased risk of local and distant intracranial recurrence after surgical resection of brain metastases. Neurooncol Adv 2023; 5:vdad007. [PMID: 36915611 PMCID: PMC10007908 DOI: 10.1093/noajnl/vdad007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Background While genetic alterations in brain metastases (BMs) have been previously explored, there are limited data examining their association with recurrence after surgical resection. This study aimed to identify genetic alterations within BMs associated with CNS recurrence after surgery across multiple cancer types. Methods A retrospective, single-center study was conducted with patients who underwent resection of a BM with available clinical and gene sequencing data available. Local and remote CNS recurrence were the primary study outcomes. Next-generation sequencing of the coding regions in over 500 oncogenes was performed in brain metastasis specimens. Cox proportional hazards analyses were performed to identify clinical features and genomic alterations associated with CNS recurrence. Results A total of 90 patients undergoing resection of 91 BMs composed the cohort. Genes most frequently mutated in the cohort included TP53 (64%), CDKN2A (37%), TERT (29%), CDKN2B (23%), NF1 (14%), KRAS (14%), and PTEN (13%), all of which occurred across multiple cancer types. CDKN2A/B co-deletion was seen in 21 (23.1%) brain metastases across multiple cancer types. In multivariate Cox proportional hazard analyses including patient, tumor, and treatment factors, CDKN2A/B co-deletion in the brain metastasis was associated with increased risk of local (HR 4.07, 95% CI 1.32-12.54, P = 0.014) and remote (HR 2.28, 95% CI 1.11-4.69, P = 0.025) CNS progression. Median survival and length of follow-up were not different based on CDKN2A/B mutation status. Conclusions CDKN2A/B co-deletion detected in BMs is associated with increased CNS recurrence after surgical resection. Additional work is needed to determine whether more aggressive treatment in patients with this mutation may improve outcomes.
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Affiliation(s)
- Ramin A Morshed
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Minh P Nguyen
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Daniel D Cummins
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Satvir Saggi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Jacob S Young
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Alexander F Haddad
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Ezequiel Goldschmidt
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | | | - Mitchel S Berger
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Philip V Theodosopoulos
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Shawn L Hervey-Jumper
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Mariza Daras
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Manish K Aghi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
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Garcia JH, Morshed RA, Chung J, Millares Chavez MA, Sudhakar V, Saggi S, Avalos LN, Gallagher A, Young JS, Daras M, McDermott MW, Garcia PA, Chang EF, Aghi MK. Factors associated with preoperative and postoperative seizures in patients undergoing resection of brain metastases. J Neurosurg 2023; 138:19-26. [PMID: 35535842 DOI: 10.3171/2022.3.jns212285] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 03/11/2022] [Indexed: 01/04/2023]
Abstract
OBJECTIVE Epileptic seizures are a common and potentially devastating complication of metastatic brain tumors. Although tumor-related seizures have been described in previous case series, most studies have focused on primary brain tumors and have not differentiated between different types of cerebral metastases. The authors analyzed a large surgical cohort of patients with brain metastases to examine risk factors associated with preoperative and postoperative seizures and to better understand the seizure risk factors of metastatic brain tumors. METHODS Patients who underwent resection of a brain metastasis at the University of California, San Francisco (UCSF), were retrospectively reviewed. Patients included in the study were ≥ 18 years of age, required resection of a brain metastasis, and were treated at UCSF. Primary cancers included melanoma, non-small cell lung adenocarcinoma, breast adenocarcinoma, colorectal adenocarcinoma, esophageal adenocarcinoma, gastric adenocarcinoma, renal cell carcinoma, urothelial carcinoma, ovarian carcinoma, cervical squamous cell carcinoma, and endometrial adenocarcinoma. Patients were evaluated for primary cancer type and seizure occurrence, as well as need for use of antiepileptic drugs preoperatively, at time of discharge, and at 6 months postoperatively. Additionally, Engel classification scores were assigned to those patients who initially presented with seizures preoperatively. Univariate and multivariate regression analyses were used to assess the association of tumor type with preoperative seizures. RESULTS Data were retrospectively analyzed for 348 consecutive patients who underwent surgical treatment of brain metastases between 1998 and 2019. The cohort had a mean age of 60 years at the time of surgery and was 59% female. The mean and median follow-up durations after the date of surgery for the cohort were 22 months and 10.8 months, respectively. In univariate analysis, frontal lobe location (p = 0.05), melanoma (p = 0.02), KRAS mutation in lung carcinoma (p = 0.04), intratumoral hemorrhage (p = 0.04), and prior radiotherapy (p = 0.04) were associated with seizure presentation. Postoperative checkpoint inhibitor use (p = 0.002), prior radiotherapy (p = 0.05), older age (p = 0.002), distant CNS progression (p = 0.004), and parietal lobe tumor location (p = 0.002) were associated with seizures at 6 months postoperatively. The final multivariate model confirmed the independent effects of tumor location in the frontal lobe and presence of intratumoral hemorrhage as predictors of preoperative seizures, and checkpoint inhibitor use and parietal lobe location were identified as significant predictors of seizures at 6 months postoperatively. CONCLUSIONS Within this surgical cohort of patients with brain metastases, seizures were seen in almost a quarter of patients preoperatively. Frontal lobe metastases and hemorrhagic tumors were associated with higher risk of preoperative seizures, whereas checkpoint inhibitor use and parietal lobe tumors appeared to be associated with seizures at 6 months postoperatively. Future research should focus on the effect of metastatic lesion-targeting therapeutic interventions on seizure control in these patients.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Paul A Garcia
- 2Department of Neurology, University of California, San Francisco, California
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Lai PMR, Ryu JY, Park SC, Gross BA, Dickinson LD, Dagen S, Aziz-Sultan MA, Boulos AS, Barrow DL, Batjer HH, Blackburn S, Chang EF, Chen PR, Colby GP, Cosgrove GR, David CA, Day AL, Frerichs KU, Niemela M, Ojemann SG, Patel NJ, Shi X, Valle-Giler EP, Wang AC, Welch BG, Zusman EE, Weiss ST, Du R. Somatic Variants in SVIL in Cerebral Aneurysms. Neurol Genet 2022; 8:e200040. [PMID: 36475054 PMCID: PMC9720733 DOI: 10.1212/nxg.0000000000200040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 09/12/2022] [Indexed: 11/30/2022]
Abstract
Background and ObjectivesWhile somatic mutations have been well-studied in cancer, their roles in other complex traits are much less understood. Our goal is to identify somatic variants that may contribute to the formation of saccular cerebral aneurysms.MethodsWe performed whole-exome sequencing on aneurysm tissues and paired peripheral blood. RNA sequencing and the CRISPR/Cas9 system were then used to perform functional validation of our results.ResultsSomatic variants involved in supervillin (SVIL) or its regulation were found in 17% of aneurysm tissues. In the presence of a mutation in theSVILgene, the expression level of SVIL was downregulated in the aneurysm tissue compared with normal control vessels. Downstream signaling pathways that were induced by knockdown ofSVILvia the CRISPR/Cas9 system in vascular smooth muscle cells (vSMCs) were determined by evaluating changes in gene expression and protein kinase phosphorylation. We found thatSVILregulated the phenotypic modulation of vSMCs to the synthetic phenotype via Krüppel-like factor 4 and platelet-derived growth factor and affected cell migration of vSMCs via the RhoA/ROCK pathway.DiscussionWe propose that somatic variants form a novel mechanism for the development of cerebral aneurysms. Specifically, somatic variants inSVILresult in the phenotypic modulation of vSMCs, which increases the susceptibility to aneurysm formation. This finding suggests a new avenue for the therapeutic intervention and prevention of cerebral aneurysms.
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Affiliation(s)
- Pui Man Rosalind Lai
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Jee-Yeon Ryu
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Sang-Cheol Park
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Bradley A Gross
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Lawrence D Dickinson
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Sarajune Dagen
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Mohammad Ali Aziz-Sultan
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Alan S Boulos
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Daniel L Barrow
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - H Hunt Batjer
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Spiros Blackburn
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Edward F Chang
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - P Roc Chen
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Geoffrey P Colby
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Garth Rees Cosgrove
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Carlos A David
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Arthur L Day
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Kai U Frerichs
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Mika Niemela
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Steven G Ojemann
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Nirav J Patel
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Xiangen Shi
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Edison P Valle-Giler
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Anthony C Wang
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Babu G Welch
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Edie E Zusman
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Scott T Weiss
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Rose Du
- Department of Neurosurgery (P.M.R.L., J.-Y.R., S.-C.P., S.D., M.A.A.-S., G.R.C., K.U.F., N.J.P., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Artificial Intelligence and Robotics Laboratory (S.-C.P.), Myongji Hospital, Goyang, Korea; Department of Neurosurgery (B.A.G.), University of Pittsburgh, PA; Department of Neurosurgery (L.D.D., E.E.Z.), Sutter Health, Danville, CA; Department of Neurosurgery (A.S.B.), Albany Medical Center, NY; Department of Neurosurgery (D.L.B.), Emory University, Atlanta, GA; Department of Neurosurgery (H.H.B., B.G.W.), University of Texas Southwestern, Dallas, TX; Department of Neurosurgery (S.B., P.R.C., A.L.D.), University of Texas Health Science Center, Houston; Department of Neurosurgery (E.F.C.), University of California San Francisco, CA; Department of Neurosurgery (G.P.C., A.C.W.), University of California Los Angeles; Department of Neurosurgery (C.A.D.), Lahey Hospital and Medical Center, Burlington, MA; Department of Neurosurgery (M.N.), Helsinki University and Helsinki University Hospital, Finland; Department of Neurosurgery (S.G.O.), University of Colorado, Denver; Department of Neurosurgery (X.S.), Affiliated Fuxing Hospital, Capital Medical University, Beijing, China; Department of Neurosurgery (E.P.V.-G.), Ochsner Medical Center, New Orleans, LA; and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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Hullett PW, Kandahari N, Shih TT, Kleen JK, Knowlton RC, Rao VR, Chang EF. Intact speech perception after resection of dominant hemisphere primary auditory cortex for the treatment of medically refractory epilepsy: illustrative case. J Neurosurg Case Lessons 2022; 4:CASE22417. [PMID: 36443954 PMCID: PMC9705521 DOI: 10.3171/case22417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 10/27/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND In classic speech network models, the primary auditory cortex is the source of auditory input to Wernicke's area in the posterior superior temporal gyrus (pSTG). Because resection of the primary auditory cortex in the dominant hemisphere removes inputs to the pSTG, there is a risk of speech impairment. However, recent research has shown the existence of other, nonprimary auditory cortex inputs to the pSTG, potentially reducing the risk of primary auditory cortex resection in the dominant hemisphere. OBSERVATIONS Here, the authors present a clinical case of a woman with severe medically refractory epilepsy with a lesional epileptic focus in the left (dominant) Heschl's gyrus. Analysis of neural responses to speech stimuli was consistent with primary auditory cortex localization to Heschl's gyrus. Although the primary auditory cortex was within the proposed resection margins, she underwent lesionectomy with total resection of Heschl's gyrus. Postoperatively, she had no speech deficits and her seizures were fully controlled. LESSONS While resection of the dominant hemisphere Heschl's gyrus/primary auditory cortex warrants caution, this case illustrates the ability to resect the primary auditory cortex without speech impairment and supports recent models of multiple parallel inputs to the pSTG.
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Affiliation(s)
- Patrick W. Hullett
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California
| | - Nazineen Kandahari
- Department of Neurosurgery, University of California San Francisco, San Francisco, California; and ,Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California
| | - Tina T. Shih
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California
| | - Jonathan K. Kleen
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California
| | - Robert C. Knowlton
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California
| | - Vikram R. Rao
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California
| | - Edward F. Chang
- Department of Neurosurgery, University of California San Francisco, San Francisco, California; and
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48
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Silva AB, Liu JR, Zhao L, Levy DF, Scott TL, Chang EF. A Neurosurgical Functional Dissection of the Middle Precentral Gyrus during Speech Production. J Neurosci 2022; 42:8416-8426. [PMID: 36351829 PMCID: PMC9665919 DOI: 10.1523/jneurosci.1614-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 08/30/2022] [Indexed: 11/17/2022] Open
Abstract
Classical models have traditionally focused on the left posterior inferior frontal gyrus (Broca's area) as a key region for motor planning of speech production. However, converging evidence suggests that it is not critical for either speech motor planning or execution. Alternative cortical areas supporting high-level speech motor planning have yet to be defined. In this review, we focus on the precentral gyrus, whose role in speech production is often thought to be limited to lower-level articulatory muscle control. In particular, we highlight neurosurgical investigations that have shed light on a cortical region anatomically located near the midpoint of the precentral gyrus, hence called the middle precentral gyrus (midPrCG). The midPrCG is functionally located between dorsal hand and ventral orofacial cortical representations and exhibits unique sensorimotor and multisensory functions relevant for speech processing. This includes motor control of the larynx, auditory processing, as well as a role in reading and writing. Furthermore, direct electrical stimulation of midPrCG can evoke complex movements, such as vocalization, and selective injury can cause deficits in verbal fluency, such as pure apraxia of speech. Based on these findings, we propose that midPrCG is essential to phonological-motoric aspects of speech production, especially syllabic-level speech sequencing, a role traditionally ascribed to Broca's area. The midPrCG is a cortical brain area that should be included in contemporary models of speech production with a unique role in speech motor planning and execution.
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Affiliation(s)
- Alexander B Silva
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
- Medical Scientist Training Program, University of California, San Francisco, California, 94158
- Graduate Program in Bioengineering, University of California, Berkeley, California 94720, & University of California, San Francisco, California, 94158
| | - Jessie R Liu
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
- Graduate Program in Bioengineering, University of California, Berkeley, California 94720, & University of California, San Francisco, California, 94158
| | - Lingyun Zhao
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
| | - Deborah F Levy
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
| | - Terri L Scott
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
- Graduate Program in Bioengineering, University of California, Berkeley, California 94720, & University of California, San Francisco, California, 94158
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Metzger SL, Liu JR, Moses DA, Dougherty ME, Seaton MP, Littlejohn KT, Chartier J, Anumanchipalli GK, Tu-Chan A, Ganguly K, Chang EF. Generalizable spelling using a speech neuroprosthesis in an individual with severe limb and vocal paralysis. Nat Commun 2022; 13:6510. [PMID: 36347863 PMCID: PMC9643551 DOI: 10.1038/s41467-022-33611-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 09/26/2022] [Indexed: 11/09/2022] Open
Abstract
Neuroprostheses have the potential to restore communication to people who cannot speak or type due to paralysis. However, it is unclear if silent attempts to speak can be used to control a communication neuroprosthesis. Here, we translated direct cortical signals in a clinical-trial participant (ClinicalTrials.gov; NCT03698149) with severe limb and vocal-tract paralysis into single letters to spell out full sentences in real time. We used deep-learning and language-modeling techniques to decode letter sequences as the participant attempted to silently spell using code words that represented the 26 English letters (e.g. "alpha" for "a"). We leveraged broad electrode coverage beyond speech-motor cortex to include supplemental control signals from hand cortex and complementary information from low- and high-frequency signal components to improve decoding accuracy. We decoded sentences using words from a 1,152-word vocabulary at a median character error rate of 6.13% and speed of 29.4 characters per minute. In offline simulations, we showed that our approach generalized to large vocabularies containing over 9,000 words (median character error rate of 8.23%). These results illustrate the clinical viability of a silently controlled speech neuroprosthesis to generate sentences from a large vocabulary through a spelling-based approach, complementing previous demonstrations of direct full-word decoding.
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Affiliation(s)
- Sean L. Metzger
- grid.266102.10000 0001 2297 6811Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA USA ,grid.47840.3f0000 0001 2181 7878University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA USA
| | - Jessie R. Liu
- grid.266102.10000 0001 2297 6811Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA USA ,grid.47840.3f0000 0001 2181 7878University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA USA
| | - David A. Moses
- grid.266102.10000 0001 2297 6811Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA USA
| | - Maximilian E. Dougherty
- grid.266102.10000 0001 2297 6811Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA USA
| | - Margaret P. Seaton
- grid.266102.10000 0001 2297 6811Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA USA
| | - Kaylo T. Littlejohn
- grid.266102.10000 0001 2297 6811Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA USA ,grid.47840.3f0000 0001 2181 7878Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA USA
| | - Josh Chartier
- grid.266102.10000 0001 2297 6811Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA USA
| | - Gopala K. Anumanchipalli
- grid.266102.10000 0001 2297 6811Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA USA ,grid.47840.3f0000 0001 2181 7878Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA USA
| | - Adelyn Tu-Chan
- grid.266102.10000 0001 2297 6811Department of Neurology, University of California, San Francisco, San Francisco, CA USA
| | - Karunesh Ganguly
- grid.266102.10000 0001 2297 6811Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Neurology, University of California, San Francisco, San Francisco, CA USA
| | - Edward F. Chang
- grid.266102.10000 0001 2297 6811Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA USA ,grid.47840.3f0000 0001 2181 7878University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA USA
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50
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Zhang Y, Lucas CHG, Young JS, Morshed RA, McCoy L, Oberheim Bush NA, Taylor JW, Daras M, Butowski NA, Villanueva-Meyer JE, Cha S, Wrensch M, Wiencke JK, Lee JC, Pekmezci M, Phillips JJ, Perry A, Bollen AW, Aghi MK, Theodosopoulos P, Chang EF, Hervey-Jumper SL, Berger MS, Clarke JL, Chang SM, Molinaro AM, Solomon DA. Prospective genomically guided identification of "early/evolving" and "undersampled" IDH-wildtype glioblastoma leads to improved clinical outcomes. Neuro Oncol 2022; 24:1749-1762. [PMID: 35395677 PMCID: PMC9527525 DOI: 10.1093/neuonc/noac089] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Genomic profiling studies of diffuse gliomas have led to new improved classification schemes that better predict patient outcomes compared to conventional histomorphology alone. One example is the recognition that patients with IDH-wildtype diffuse astrocytic gliomas demonstrating lower-grade histologic features but genomic and/or epigenomic profile characteristic of glioblastoma typically have poor outcomes similar to patients with histologically diagnosed glioblastoma. Here we sought to determine the clinical impact of prospective genomic profiling for these IDH-wildtype diffuse astrocytic gliomas lacking high-grade histologic features but with molecular profile of glioblastoma. METHODS Clinical management and outcomes were analyzed for 38 consecutive adult patients with IDH-wildtype diffuse astrocytic gliomas lacking necrosis or microvascular proliferation on histologic examination that were genomically profiled on a prospective clinical basis revealing criteria for an integrated diagnosis of "diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma, WHO grade IV" per cIMPACT-NOW criteria. RESULTS We identified that this diagnosis consists of two divergent clinical scenarios based on integration of radiologic, histologic, and genomic features that we term "early/evolving" and "undersampled" glioblastoma, IDH-wildtype. We found that prospective genomically guided identification of early/evolving and undersampled IDH-wildtype glioblastoma resulted in more aggressive patient management and improved clinical outcomes compared to a biologically matched historical control patient cohort receiving standard-of-care therapy based on histomorphologic diagnosis alone. CONCLUSIONS These results support routine use of genomic and/or epigenomic profiling to accurately classify glial neoplasms, as these assays not only improve diagnostic classification but critically lead to more appropriate patient management that can improve clinical outcomes.
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Affiliation(s)
- Yalan Zhang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Calixto-Hope G Lucas
- Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Jacob S Young
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Ramin A Morshed
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Lucie McCoy
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Nancy Ann Oberheim Bush
- Division of Neuro-Oncology, Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Jennie W Taylor
- Division of Neuro-Oncology, Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Mariza Daras
- Division of Neuro-Oncology, Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Nicholas A Butowski
- Division of Neuro-Oncology, Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Javier E Villanueva-Meyer
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Soonmee Cha
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Margaret Wrensch
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - John K Wiencke
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Julieann C Lee
- Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Melike Pekmezci
- Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Joanna J Phillips
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
- Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Arie Perry
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
- Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Andrew W Bollen
- Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Manish K Aghi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Philip Theodosopoulos
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Shawn L Hervey-Jumper
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Mitchel S Berger
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Jennifer L Clarke
- Division of Neuro-Oncology, Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
- Division of Neuro-Oncology, Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - David A Solomon
- Department of Pathology, University of California, San Francisco, San Francisco, California, USA
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