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Huang H, Ojeda Valencia G, Gregg NM, Osman GM, Montoya MN, Worrell GA, Miller KJ, Hermes D. CARLA: Adjusted common average referencing for cortico-cortical evoked potential data. J Neurosci Methods 2024; 407:110153. [PMID: 38710234 PMCID: PMC11149384 DOI: 10.1016/j.jneumeth.2024.110153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 02/22/2024] [Accepted: 04/27/2024] [Indexed: 05/08/2024]
Abstract
Human brain connectivity can be mapped by single pulse electrical stimulation during intracranial EEG measurements. The raw cortico-cortical evoked potentials (CCEP) are often contaminated by noise. Common average referencing (CAR) removes common noise and preserves response shapes but can introduce bias from responsive channels. We address this issue with an adjusted, adaptive CAR algorithm termed "CAR by Least Anticorrelation (CARLA)". CARLA was tested on simulated CCEP data and real CCEP data collected from four human participants. In CARLA, the channels are ordered by increasing mean cross-trial covariance, and iteratively added to the common average until anticorrelation between any single channel and all re-referenced channels reaches a minimum, as a measure of shared noise. We simulated CCEP data with true responses in 0-45 of 50 total channels. We quantified CARLA's error and found that it erroneously included 0 (median) truly responsive channels in the common average with ≤42 responsive channels, and erroneously excluded ≤2.5 (median) unresponsive channels at all responsiveness levels. On real CCEP data, signal quality was quantified with the mean R2 between all pairs of channels, which represents inter-channel dependency and is low for well-referenced data. CARLA re-referencing produced significantly lower mean R2 than standard CAR, CAR using a fixed bottom quartile of channels by covariance, and no re-referencing. CARLA minimizes bias in re-referenced CCEP data by adaptively selecting the optimal subset of non-responsive channels. It showed high specificity and sensitivity on simulated CCEP data and lowered inter-channel dependency compared to CAR on real CCEP data.
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Affiliation(s)
- Harvey Huang
- Mayo Clinic Medical Scientist Training Program, Rochester, MN, USA.
| | | | | | - Gamaleldin M Osman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA; Division of Child Neurology, Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, USA
| | - Morgan N Montoya
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Gregory A Worrell
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Kai J Miller
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA; Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Dora Hermes
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA; Department of Radiology, Mayo Clinic, Rochester, MN 55901, USA.
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2
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Lyu D, Stiger J, Lusk Z, Buch V, Parvizi J. Causal Cortical and Thalamic Connections in the Human Brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.22.600166. [PMID: 38979261 PMCID: PMC11230252 DOI: 10.1101/2024.06.22.600166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
The brain's functional architecture is intricately shaped by causal connections between its cortical and subcortical structures. Here, we studied 27 participants with 4864 electrodes implanted across the anterior, mediodorsal, and pulvinar thalamic regions, and the cortex. Using data from electrical stimulation procedures and a data-driven approach informed by neurophysiological standards, we dissociated three unique spectral patterns generated by the perturbation of a given brain area. Among these, a novel waveform emerged, marked by delayed-onset slow oscillations in both ipsilateral and contralateral cortices following thalamic stimulations, suggesting a mechanism by which a thalamic site can influence bilateral cortical activity. Moreover, cortical stimulations evoked earlier signals in the thalamus than in other connected cortical areas suggesting that the thalamus receives a copy of signals before they are exchanged across the cortex. Our causal connectivity data can be used to inform biologically-inspired computational models of the functional architecture of the brain.
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3
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Hajnal B, Szabó JP, Tóth E, Keller CJ, Wittner L, Mehta AD, Erőss L, Ulbert I, Fabó D, Entz L. Intracortical mechanisms of single pulse electrical stimulation (SPES) evoked excitations and inhibitions in humans. Sci Rep 2024; 14:13784. [PMID: 38877093 PMCID: PMC11178858 DOI: 10.1038/s41598-024-62433-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 05/16/2024] [Indexed: 06/16/2024] Open
Abstract
Cortico-cortical evoked potentials (CCEPs) elicited by single-pulse electric stimulation (SPES) are widely used to assess effective connectivity between cortical areas and are also implemented in the presurgical evaluation of epileptic patients. Nevertheless, the cortical generators underlying the various components of CCEPs in humans have not yet been elucidated. Our aim was to describe the laminar pattern arising under SPES evoked CCEP components (P1, N1, P2, N2, P3) and to evaluate the similarities between N2 and the downstate of sleep slow waves. We used intra-cortical laminar microelectrodes (LMEs) to record CCEPs evoked by 10 mA bipolar 0.5 Hz electric pulses in seven patients with medically intractable epilepsy implanted with subdural grids. Based on the laminar profile of CCEPs, the latency of components is not layer-dependent, however their rate of appearance varies across cortical depth and stimulation distance, while the seizure onset zone does not seem to affect the emergence of components. Early neural excitation primarily engages middle and deep layers, propagating to the superficial layers, followed by mainly superficial inhibition, concluding in a sleep slow wave-like inhibition and excitation sequence.
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Affiliation(s)
- Boglárka Hajnal
- Epilepsy Center, Clinic for Neurosurgery and Neurointervention, Semmelweis University, Budapest, 1145, Hungary
- János Szentágothai Neurosciences Program, Semmelweis University School of PhD Studies, Budapest, 1083, Hungary
| | - Johanna Petra Szabó
- Epilepsy Center, Clinic for Neurosurgery and Neurointervention, Semmelweis University, Budapest, 1145, Hungary
- János Szentágothai Neurosciences Program, Semmelweis University School of PhD Studies, Budapest, 1083, Hungary
- Lendület Laboratory of Systems Neuroscience, HUN-REN Institute of Experimental Medicine, Budapest, 1083, Hungary
| | - Emília Tóth
- Epilepsy and Cognitive Neurophysiology Laboratory, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Corey J Keller
- Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
- Department of Neurosurgery, Hofstra North Shore LIJ School of Medicine and Feinstein Institute of Medical Research, 300 Community Drive, Manhasset, NY, 11030, USA
- Department of Neuroscience, Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, 94304, USA
| | - Lucia Wittner
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, HUN-REN, Budapest, 1117, Hungary
- Department of Information Technology and Bionics, Péter Pázmány Catholic University, Budapest, 1083, Hungary
| | - Ashesh D Mehta
- Department of Neurosurgery, Hofstra North Shore LIJ School of Medicine and Feinstein Institute of Medical Research, 300 Community Drive, Manhasset, NY, 11030, USA
| | - Loránd Erőss
- Department of Functional Neurosurgery, Clinic for Neurosurgery and Neurointervention, Semmelweis University, Budapest, 1145, Hungary
| | - István Ulbert
- Epilepsy Center, Clinic for Neurosurgery and Neurointervention, Semmelweis University, Budapest, 1145, Hungary
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, HUN-REN, Budapest, 1117, Hungary
- Department of Information Technology and Bionics, Péter Pázmány Catholic University, Budapest, 1083, Hungary
| | - Dániel Fabó
- Epilepsy Center, Clinic for Neurosurgery and Neurointervention, Semmelweis University, Budapest, 1145, Hungary.
| | - László Entz
- Department of Functional Neurosurgery, Clinic for Neurosurgery and Neurointervention, Semmelweis University, Budapest, 1145, Hungary
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4
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Parvizi J, Lyu D, Stieger J, Lusk Z, Buch V. Causal Cortical and Thalamic Connections in the Human Brain. RESEARCH SQUARE 2024:rs.3.rs-4366486. [PMID: 38853954 PMCID: PMC11160924 DOI: 10.21203/rs.3.rs-4366486/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
The brain's functional architecture is intricately shaped by causal connections between its cortical and subcortical structures. Here, we studied 27 participants with 4864 electrodes implanted across the anterior, mediodorsal, and pulvinar thalamic regions, and the cortex. Using data from electrical stimulation procedures and a data-driven approach informed by neurophysiological standards, we dissociated three unique spectral patterns generated by the perturbation of a given brain area. Among these, a novel waveform emerged, marked by delayed-onset slow oscillations in both ipsilateral and contralateral cortices following thalamic stimulations, suggesting a mechanism by which a thalamic site can influence bilateral cortical activity. Moreover, cortical stimulations evoked earlier signals in the thalamus than in other connected cortical areas suggesting that the thalamus receives a copy of signals before they are exchanged across the cortex. Our causal connectivity data can be used to inform biologically-inspired computational models of the functional architecture of the brain.
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5
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Wang JB, Hassan U, Bruss JE, Oya H, Uitermarkt BD, Trapp NT, Gander PE, Howard MA, Keller CJ, Boes AD. Effects of transcranial magnetic stimulation on the human brain recorded with intracranial electrocorticography. Mol Psychiatry 2024; 29:1228-1240. [PMID: 38317012 DOI: 10.1038/s41380-024-02405-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 12/19/2023] [Accepted: 01/02/2024] [Indexed: 02/07/2024]
Abstract
Transcranial magnetic stimulation (TMS) is increasingly used as a noninvasive technique for neuromodulation in research and clinical applications, yet its mechanisms are not well understood. Here, we present the neurophysiological effects of TMS using intracranial electrocorticography (iEEG) in neurosurgical patients. We first evaluated safety in a gel-based phantom. We then performed TMS-iEEG in 22 neurosurgical participants with no adverse events. We next evaluated intracranial responses to single pulses of TMS to the dorsolateral prefrontal cortex (dlPFC) (N = 10, 1414 electrodes). We demonstrate that TMS is capable of inducing evoked potentials both locally within the dlPFC and in downstream regions functionally connected to the dlPFC, including the anterior cingulate and insular cortex. These downstream effects were not observed when stimulating other distant brain regions. Intracranial dlPFC electrical stimulation had similar timing and downstream effects as TMS. These findings support the safety and promise of TMS-iEEG in humans to examine local and network-level effects of TMS with higher spatiotemporal resolution than currently available methods.
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Affiliation(s)
- Jeffrey B Wang
- Biophysics Graduate Program, Stanford University Medical Center, Stanford, CA, 94305, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, CA, 94305, USA
| | - Umair Hassan
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, CA, 94305, USA
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Joel E Bruss
- Department of Neurology, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA
- Department of Pediatrics, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA
| | - Hiroyuki Oya
- Department of Neurosurgery, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA
| | - Brandt D Uitermarkt
- Department of Pediatrics, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA
| | - Nicholas T Trapp
- Department of Psychiatry, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, 52242, USA
| | - Phillip E Gander
- Department of Neurosurgery, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA
- Department of Radiology, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA
| | - Matthew A Howard
- Department of Neurosurgery, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA
| | - Corey J Keller
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, CA, 94305, USA
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Aaron D Boes
- Department of Neurology, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA.
- Department of Pediatrics, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA.
- Department of Psychiatry, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, USA.
- Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, 52242, USA.
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6
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Seidel K, Wermelinger J, Alvarez-Abut P, Deletis V, Raabe A, Zhang D, Schucht P. Cortico-cortical evoked potentials of language tracts in minimally invasive glioma surgery guided by Penfield stimulation. Clin Neurophysiol 2024; 161:256-267. [PMID: 38521679 DOI: 10.1016/j.clinph.2023.12.136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 11/19/2023] [Accepted: 12/23/2023] [Indexed: 03/25/2024]
Abstract
OBJECTIVE We investigated the feasibility of recording cortico-cortical evoked potentials (CCEPs) in patients with low- and high-grade glioma. We compared CCEPs during awake and asleep surgery, as well as those stimulated from the functional Broca area and recorded from the functional Wernicke area (BtW), and vice versa (WtB). We also analyzed CCEP properties according to tumor location, histopathology, and aphasia. METHODS We included 20 patients who underwent minimally invasive surgery in an asleep-awake-asleep setting. Strip electrode placement was guided by classical Penfield stimulation of positive language sites and fiber tracking of the arcuate fascicle. CCEPs were elicited with alternating monophasic single pulses of 1.1 Hz frequency and recorded as averaged signals. Intraoperatively, there was no post-processing of the signal. RESULTS Ninety-seven CCEPs from 19 patients were analyzed. There was no significant difference in CCEP properties when comparing awake versus asleep, nor BtW versus WtB. CCEP amplitude and latency were affected by tumor location and histopathology. CCEP features after tumor resection correlated with short- and long-term postoperative aphasia. CONCLUSION CCEP recordings are feasible during minimally invasive surgery. CCEPs might be surrogate markers for altered connectivity of the language tracts. SIGNIFICANCE This study may guide the incorporation of CCEPs into intraoperative neurophysiological monitoring.
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Affiliation(s)
- Kathleen Seidel
- Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
| | - Jonathan Wermelinger
- Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Pablo Alvarez-Abut
- Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Vedran Deletis
- Department of Neurosurgery, University Hospital Dubrava, Zagreb, Croatia; Albert Einstein College of Medicine, New York, NY, USA
| | - Andreas Raabe
- Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - David Zhang
- Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Philippe Schucht
- Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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7
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Russo S, Claar L, Marks L, Krishnan G, Furregoni G, Zauli FM, Hassan G, Solbiati M, d’Orio P, Mikulan E, Sarasso S, Rosanova M, Sartori I, Bazhenov M, Pigorini A, Massimini M, Koch C, Rembado I. Thalamic feedback shapes brain responses evoked by cortical stimulation in mice and humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578243. [PMID: 38352535 PMCID: PMC10862802 DOI: 10.1101/2024.01.31.578243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Cortical stimulation with single pulses is a common technique in clinical practice and research. However, we still do not understand the extent to which it engages subcortical circuits which contribute to the associated evoked potentials (EPs). Here we find that cortical stimulation generates remarkably similar EPs in humans and mice, with a late component similarly modulated by the subject's behavioral state. We optogenetically dissect the underlying circuit in mice, demonstrating that the late component of these EPs is caused by a thalamic hyperpolarization and rebound. The magnitude of this late component correlates with the bursting frequency and synchronicity of thalamic neurons, modulated by the subject's behavioral state. A simulation of the thalamo-cortical circuit highlights that both intrinsic thalamic currents as well as cortical and thalamic GABAergic neurons contribute to this response profile. We conclude that the cortical stimulation engages cortico-thalamo-cortical circuits highly preserved across different species and stimulation modalities.
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Affiliation(s)
- Simone Russo
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
- Department of Philosophy ‘Piero Martinetti’, University of Milan, Milan, Italy
- Brain and Consciousness, Allen Institute, Seattle, United States
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Leslie Claar
- Brain and Consciousness, Allen Institute, Seattle, United States
| | - Lydia Marks
- Brain and Consciousness, Allen Institute, Seattle, United States
| | - Giri Krishnan
- Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Giulia Furregoni
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
| | - Flavia Maria Zauli
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
- Department of Philosophy ‘Piero Martinetti’, University of Milan, Milan, Italy
- ASST Grande Ospedale Metropolitano Niguarda, “C. Munari” Epilepsy Surgery Centre, Department of Neuroscience, Italy
| | - Gabriel Hassan
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
- Department of Philosophy ‘Piero Martinetti’, University of Milan, Milan, Italy
| | - Michela Solbiati
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
- ASST Grande Ospedale Metropolitano Niguarda, “C. Munari” Epilepsy Surgery Centre, Department of Neuroscience, Italy
| | - Piergiorgio d’Orio
- ASST Grande Ospedale Metropolitano Niguarda, “C. Munari” Epilepsy Surgery Centre, Department of Neuroscience, Italy
- University of Parma, Parma 43121, Italy
| | - Ezequiel Mikulan
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
| | - Simone Sarasso
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
| | - Ivana Sartori
- ASST Grande Ospedale Metropolitano Niguarda, “C. Munari” Epilepsy Surgery Centre, Department of Neuroscience, Italy
| | - Maxim Bazhenov
- Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
- Neurosciences Graduate Program, University of California San Diego, La Jolla, CA, 92093, USA
| | - Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan 20122, Italy
- UOC Maxillo-facial Surgery and dentistry, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
- Istituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan 20122, Italy
- Azrieli Program in Brain, Mind and Consciousness, Canadian Institute for Advanced Research (CIFAR), Toronto, Ontario M5G 1M1, Canada
| | - Christof Koch
- Brain and Consciousness, Allen Institute, Seattle, United States
| | - Irene Rembado
- Brain and Consciousness, Allen Institute, Seattle, United States
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8
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Adkisson PW, Steinhardt CR, Fridman GY. Galvanic vs. pulsatile effects on decision-making networks: reshaping the neural activation landscape. J Neural Eng 2024; 21:026021. [PMID: 38518369 DOI: 10.1088/1741-2552/ad36e2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 03/22/2024] [Indexed: 03/24/2024]
Abstract
Objective. Primarily due to safety concerns, biphasic pulsatile stimulation (PS) is the present standard for electrical excitation of neural tissue with a diverse set of applications. While pulses have been shown to be effective to achieve functional outcomes, they have well-known deficits. Due to recent technical advances, galvanic stimulation (GS), delivery of current for extended periods of time (>1 s), has re-emerged as an alternative to PS.Approach. In this paper, we use a winner-take-all decision-making cortical network model to investigate differences between pulsatile and GS in the context of a perceptual decision-making task.Main results. Based on previous work, we hypothesized that GS would produce more spatiotemporally distributed, network-sensitive neural responses, while PS would produce highly synchronized activation of a limited group of neurons. Our results in-silico support these hypotheses for low-amplitude GS but deviate when galvanic amplitudes are large enough to directly activate or block nearby neurons.Significance. We conclude that with careful parametrization, GS could overcome some limitations of PS to deliver more naturalistic firing patterns in the group of targeted neurons.
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Affiliation(s)
- Paul W Adkisson
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, United States of America
| | - Cynthia R Steinhardt
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, United States of America
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, United States of America
- Simons Society of Fellows, Simons Foundation, New York, NY 10010, United States of America
| | - Gene Y Fridman
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, United States of America
- Department of Otolaryngology Head and Neck Surgery, Johns Hopkins University, Baltimore, MD 21205, United States of America
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9
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Seas A, Noor MS, Choi KS, Veerakumar A, Obatusin M, Dahill-Fuchel J, Tiruvadi V, Xu E, Riva-Posse P, Rozell CJ, Mayberg HS, McIntyre CC, Waters AC, Howell B. Subcallosal cingulate deep brain stimulation evokes two distinct cortical responses via differential white matter activation. Proc Natl Acad Sci U S A 2024; 121:e2314918121. [PMID: 38527192 PMCID: PMC10998591 DOI: 10.1073/pnas.2314918121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 02/20/2024] [Indexed: 03/27/2024] Open
Abstract
Subcallosal cingulate (SCC) deep brain stimulation (DBS) is an emerging therapy for refractory depression. Good clinical outcomes are associated with the activation of white matter adjacent to the SCC. This activation produces a signature cortical evoked potential (EP), but it is unclear which of the many pathways in the vicinity of SCC is responsible for driving this response. Individualized biophysical models were built to achieve selective engagement of two target bundles: either the forceps minor (FM) or cingulum bundle (CB). Unilateral 2 Hz stimulation was performed in seven patients with treatment-resistant depression who responded to SCC DBS, and EPs were recorded using 256-sensor scalp electroencephalography. Two distinct EPs were observed: a 120 ms symmetric response spanning both hemispheres and a 60 ms asymmetrical EP. Activation of FM correlated with the symmetrical EPs, while activation of CB was correlated with the asymmetrical EPs. These results support prior model predictions that these two pathways are predominantly activated by clinical SCC DBS and provide first evidence of a link between cortical EPs and selective fiber bundle activation.
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Affiliation(s)
- Andreas Seas
- Department of Biomedical Engineering, Duke University, Durham, NC27708
- Department of Neurosurgery, Duke University, Durham, NC27708
| | - M. Sohail Noor
- Department of Biomedical Engineering, Duke University, Durham, NC27708
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH10900
| | - Ki Sueng Choi
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY10029
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA30329
| | - Ashan Veerakumar
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA30329
| | - Mosadoluwa Obatusin
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY10029
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA30329
| | - Jacob Dahill-Fuchel
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY10029
| | - Vineet Tiruvadi
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA30329
| | - Elisa Xu
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY10029
| | - Patricio Riva-Posse
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA30329
| | - Christopher J. Rozell
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA30332
| | - Helen S. Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY10029
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA30329
| | - Cameron C. McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC27708
- Department of Neurosurgery, Duke University, Durham, NC27708
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH10900
| | - Allison C. Waters
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY10029
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA30329
| | - Bryan Howell
- Department of Biomedical Engineering, Duke University, Durham, NC27708
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH10900
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10
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Man V, Cockburn J, Flouty O, Gander PE, Sawada M, Kovach CK, Kawasaki H, Oya H, Howard Iii MA, O'Doherty JP. Temporally organized representations of reward and risk in the human brain. Nat Commun 2024; 15:2162. [PMID: 38461343 PMCID: PMC10924934 DOI: 10.1038/s41467-024-46094-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 02/13/2024] [Indexed: 03/11/2024] Open
Abstract
The value and uncertainty associated with choice alternatives constitute critical features relevant for decisions. However, the manner in which reward and risk representations are temporally organized in the brain remains elusive. Here we leverage the spatiotemporal precision of intracranial electroencephalography, along with a simple card game designed to elicit the unfolding computation of a set of reward and risk variables, to uncover this temporal organization. Reward outcome representations across wide-spread regions follow a sequential order along the anteroposterior axis of the brain. In contrast, expected value can be decoded from multiple regions at the same time, and error signals in both reward and risk domains reflect a mixture of sequential and parallel encoding. We further highlight the role of the anterior insula in generalizing between reward prediction error and risk prediction error codes. Together our results emphasize the importance of neural dynamics for understanding value-based decisions under uncertainty.
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Affiliation(s)
- Vincent Man
- Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, 91125, USA.
| | - Jeffrey Cockburn
- Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Oliver Flouty
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL, 33606, USA
| | - Phillip E Gander
- Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
- Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA, 52242, USA
| | - Masahiro Sawada
- Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
| | - Christopher K Kovach
- Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
- Department of Neurosurgery, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Hiroto Kawasaki
- Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
| | - Hiroyuki Oya
- Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
- Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA, 52242, USA
| | - Matthew A Howard Iii
- Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
- Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA, 52242, USA
| | - John P O'Doherty
- Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, 91125, USA
- Computation and Neural Systems, California Institute of Technology, Pasadena, CA, 91125, USA
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11
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Gregg NM, Valencia GO, Huang H, Lundstrom BN, Van Gompel JJ, Miller KJ, Worrell GA, Hermes D. Thalamic stimulation induced changes in effective connectivity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.03.24303480. [PMID: 38496621 PMCID: PMC10942513 DOI: 10.1101/2024.03.03.24303480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Deep brain stimulation (DBS) is a viable treatment for a variety of neurological conditions, however, the mechanisms through which DBS modulates large-scale brain networks are unresolved. Clinical effects of DBS are observed over multiple timescales. In some conditions, such as Parkinson's disease and essential tremor, clinical improvement is observed within seconds. In many other conditions, such as epilepsy, central pain, dystonia, neuropsychiatric conditions or Tourette syndrome, the DBS related effects are believed to require neuroplasticity or reorganization and often take hours to months to observe. To optimize DBS parameters, it is therefore essential to develop electrophysiological biomarkers that characterize whether DBS settings are successfully engaging and modulating the network involved in the disease of interest. In this study, 10 individuals with drug resistant epilepsy undergoing intracranial stereotactic EEG including a thalamus electrode underwent a trial of repetitive thalamic stimulation. We evaluated thalamocortical effective connectivity using single pulse electrical stimulation, both at baseline and following a 145 Hz stimulation treatment trial. We found that when high frequency stimulation was delivered for >1.5 hours, the evoked potentials measured from remote regions were significantly reduced in amplitude and the degree of modulation was proportional to the strength of baseline connectivity. When stimulation was delivered for shorter time periods, results were more variable. These findings suggest that changes in effective connectivity in the network targeted with DBS accumulate over hours of DBS. Stimulation evoked potentials provide an electrophysiological biomarker that allows for efficient data-driven characterization of neuromodulation effects, which could enable new objective approaches for individualized DBS optimization.
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Affiliation(s)
| | | | - Harvey Huang
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester MN
| | | | | | - Kai J. Miller
- Department of Neurosurgery, Mayo Clinic, Rochester MN
| | | | - Dora Hermes
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester MN
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12
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Kobayashi K, Taylor KN, Shahabi H, Krishnan B, Joshi A, Mackow MJ, Feldman L, Zamzam O, Medani T, Bulacio J, Alexopoulos AV, Najm I, Bingaman W, Leahy RM, Nair DR. Effective connectivity relates seizure outcome to electrode placement in responsive neurostimulation. Brain Commun 2024; 6:fcae035. [PMID: 38390255 PMCID: PMC10882982 DOI: 10.1093/braincomms/fcae035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 09/06/2023] [Accepted: 02/19/2024] [Indexed: 02/24/2024] Open
Abstract
Responsive neurostimulation is a closed-loop neuromodulation therapy for drug resistant focal epilepsy. Responsive neurostimulation electrodes are placed near ictal onset zones so as to enable detection of epileptiform activity and deliver electrical stimulation. There is no standard approach for determining the optimal placement of responsive neurostimulation electrodes. Clinicians make this determination based on presurgical tests, such as MRI, EEG, magnetoencephalography, ictal single-photon emission computed tomography and intracranial EEG. Currently functional connectivity measures are not being used in determining the placement of responsive neurostimulation electrodes. Cortico-cortical evoked potentials are a measure of effective functional connectivity. Cortico-cortical evoked potentials are generated by direct single-pulse electrical stimulation and can be used to investigate cortico-cortical connections in vivo. We hypothesized that the presence of high amplitude cortico-cortical evoked potentials, recorded during intracranial EEG monitoring, near the eventual responsive neurostimulation contact sites is predictive of better outcomes from its therapy. We retrospectively reviewed 12 patients in whom cortico-cortical evoked potentials were obtained during stereoelectroencephalography evaluation and subsequently underwent responsive neurostimulation therapy. We studied the relationship between cortico-cortical evoked potentials, the eventual responsive neurostimulation electrode locations and seizure reduction. Directional connectivity indicated by cortico-cortical evoked potentials can categorize stereoelectroencephalography electrodes as either receiver nodes/in-degree (an area of greater inward connectivity) or projection nodes/out-degree (greater outward connectivity). The follow-up period for seizure reduction ranged from 1.3-4.8 years (median 2.7) after responsive neurostimulation therapy started. Stereoelectroencephalography electrodes closest to the eventual responsive neurostimulation contact site tended to show larger in-degree cortico-cortical evoked potentials, especially for the early latency cortico-cortical evoked potentials period (10-60 ms period) in six out of 12 patients. Stereoelectroencephalography electrodes closest to the responsive neurostimulation contacts (≤5 mm) also had greater significant out-degree in the early cortico-cortical evoked potentials latency period than those further away (≥10 mm) (P < 0.05). Additionally, significant correlation was noted between in-degree cortico-cortical evoked potentials and greater seizure reduction with responsive neurostimulation therapy at its most effective period (P < 0.05). These findings suggest that functional connectivity determined by cortico-cortical evoked potentials may provide additional information that could help guide the optimal placement of responsive neurostimulation electrodes.
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Affiliation(s)
- Katsuya Kobayashi
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Kenneth N Taylor
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Hossein Shahabi
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Balu Krishnan
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Anand Joshi
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Michael J Mackow
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Lauren Feldman
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Omar Zamzam
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Takfarinas Medani
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Juan Bulacio
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | | | - Imad Najm
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - William Bingaman
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Richard M Leahy
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Dileep R Nair
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
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13
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Yang B, Zhao B, Li C, Mo J, Guo Z, Li Z, Yao Y, Fan X, Cai D, Sang L, Zheng Z, Gao D, Zhao X, Wang X, Zhang C, Hu W, Shao X, Zhang J, Zhang K. Localizing seizure onset zone by a cortico-cortical evoked potentials-based machine learning approach in focal epilepsy. Clin Neurophysiol 2024; 158:103-113. [PMID: 38218076 DOI: 10.1016/j.clinph.2023.12.135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 12/03/2023] [Accepted: 12/19/2023] [Indexed: 01/15/2024]
Abstract
OBJECTIVE We aimed to develop a new approach for identifying the localization of the seizure onset zone (SOZ) based on corticocortical evoked potentials (CCEPs) and to compare the connectivity patterns in patients with different clinical phenotypes. METHODS Fifty patients who underwent stereoelectroencephalography and CCEP procedures were included. Logistic regression was used in the model, and six CCEP metrics were input as features: root mean square of the first peak (N1RMS) and second peak (N2RMS), peak latency, onset latency, width duration, and area. RESULTS The area under the curve (AUC) for localizing the SOZ ranged from 0.88 to 0.93. The N1RMS values in the hippocampus sclerosis (HS) group were greater than that of the focal cortical dysplasia (FCD) IIa group (p < 0.001), independent of the distance between the recorded and stimulated sites. The sensitivity of localization was higher in the seizure-free group than in the non-seizure-free group (p = 0.036). CONCLUSIONS This new method can be used to predict the SOZ localization in various focal epilepsy phenotypes. SIGNIFICANCE This study proposed a machine-learning approach for localizing the SOZ. Moreover, we examined how clinical phenotypes impact large-scale abnormality of the epileptogenic networks.
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Affiliation(s)
- Bowen Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chao Li
- Department of Radiology, Third Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhihao Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zilin Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yuan Yao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiuliang Fan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Du Cai
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lin Sang
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Zhong Zheng
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Dongmei Gao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xuemin Zhao
- Department of Neurophysiology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiaoqiu Shao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
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14
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Xie T, Foutz TJ, Adamek M, Swift JR, Inman CS, Manns JR, Leuthardt EC, Willie JT, Brunner P. Single-pulse electrical stimulation artifact removal using the novel matching pursuit-based artifact reconstruction and removal method (MPARRM). J Neural Eng 2023; 20:066036. [PMID: 38063368 PMCID: PMC10751949 DOI: 10.1088/1741-2552/ad1385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 11/02/2023] [Accepted: 12/07/2023] [Indexed: 12/28/2023]
Abstract
Objective.Single-pulse electrical stimulation (SPES) has been widely used to probe effective connectivity. However, analysis of the neural response is often confounded by stimulation artifacts. We developed a novel matching pursuit-based artifact reconstruction and removal method (MPARRM) capable of removing artifacts from stimulation-artifact-affected electrophysiological signals.Approach.To validate MPARRM across a wide range of potential stimulation artifact types, we performed a bench-top experiment in which we suspended electrodes in a saline solution to generate 110 types of real-world stimulation artifacts. We then added the generated stimulation artifacts to ground truth signals (stereoelectroencephalography signals from nine human subjects recorded during a receptive speech task), applied MPARRM to the combined signal, and compared the resultant denoised signal with the ground truth signal. We further applied MPARRM to artifact-affected neural signals recorded from the hippocampus while performing SPES on the ipsilateral basolateral amygdala in nine human subjects.Main results.MPARRM could remove stimulation artifacts without introducing spectral leakage or temporal spread. It accommodated variable stimulation parameters and recovered the early response to SPES within a wide range of frequency bands. Specifically, in the early response period (5-10 ms following stimulation onset), we found that the broadband gamma power (70-170 Hz) of the denoised signal was highly correlated with the ground truth signal (R=0.98±0.02, Pearson), and the broadband gamma activity of the denoised signal faithfully revealed the responses to the auditory stimuli within the ground truth signal with94%±1.47%sensitivity and99%±1.01%specificity. We further found that MPARRM could reveal the expected temporal progression of broadband gamma activity along the anterior-posterior axis of the hippocampus in response to the ipsilateral amygdala stimulation.Significance.MPARRM could faithfully remove SPES artifacts without confounding the electrophysiological signal components, especially during the early-response period. This method can facilitate the understanding of the neural response mechanisms of SPES.
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Affiliation(s)
- Tao Xie
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States of America
- National Center for Adaptive Neurotechnologies, St. Louis, MO, United States of America
| | - Thomas J Foutz
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Markus Adamek
- National Center for Adaptive Neurotechnologies, St. Louis, MO, United States of America
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States of America
| | - James R Swift
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States of America
- National Center for Adaptive Neurotechnologies, St. Louis, MO, United States of America
| | - Cory S Inman
- Department of Psychology, University of Utah, Salt Lake City, UT, United States of America
| | - Joseph R Manns
- Department of Psychology, Emory University, Atlanta, GA, United States of America
| | - Eric C Leuthardt
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Jon T Willie
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States of America
- National Center for Adaptive Neurotechnologies, St. Louis, MO, United States of America
| | - Peter Brunner
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States of America
- National Center for Adaptive Neurotechnologies, St. Louis, MO, United States of America
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15
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Novitskaya Y, Dümpelmann M, Schulze-Bonhage A. Physiological and pathological neuronal connectivity in the living human brain based on intracranial EEG signals: the current state of research. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3:1297345. [PMID: 38107334 PMCID: PMC10723837 DOI: 10.3389/fnetp.2023.1297345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 11/17/2023] [Indexed: 12/19/2023]
Abstract
Over the past decades, studies of human brain networks have received growing attention as the assessment and modelling of connectivity in the brain is a topic of high impact with potential application in the understanding of human brain organization under both physiological as well as various pathological conditions. Under specific diagnostic settings, human neuronal signal can be obtained from intracranial EEG (iEEG) recording in epilepsy patients that allows gaining insight into the functional organisation of living human brain. There are two approaches to assess brain connectivity in the iEEG-based signal: evaluation of spontaneous neuronal oscillations during ongoing physiological and pathological brain activity, and analysis of the electrophysiological cortico-cortical neuronal responses, evoked by single pulse electrical stimulation (SPES). Both methods have their own advantages and limitations. The paper outlines available methodological approaches and provides an overview of current findings in studies of physiological and pathological human brain networks, based on intracranial EEG recordings.
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Affiliation(s)
- Yulia Novitskaya
- Epilepsy Center, Department of Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Matthias Dümpelmann
- Epilepsy Center, Department of Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Microsystems Engineering (IMTEK), University of Freiburg, Freiburg, Germany
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Department of Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Center for Basics in NeuroModulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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16
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Munot S, Kim N, Huang Y, Keller CJ. Direct cortical stimulation induces short-term plasticity of neural oscillations in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.15.567302. [PMID: 38014071 PMCID: PMC10680685 DOI: 10.1101/2023.11.15.567302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Patterned brain stimulation is commonly employed as a tool for eliciting plasticity in brain circuits and treating neuropsychiatric disorders. Although widely used in clinical settings, there remains a limited understanding of how stimulation-induced plasticity influences neural oscillations and their interplay with the underlying baseline functional architecture. To address this question, we applied 15 minutes of 10Hz focal electrical simulation, a pattern identical to 'excitatory' repetitive transcranial magnetic stimulation (rTMS), to 14 medically-intractable epilepsy patients undergoing intracranial electroencephalographic (iEEG). We quantified the spectral features of the cortico-cortical evoked potential (CCEPs) in these patients before and after stimulation. We hypothesized that for a given region the temporal and spectral components of the CCEP predicted the location and degree of stimulation-induced plasticity. Across patients, low frequency power (alpha and beta) showed the broadest change, while the magnitude of change was stronger in high frequencies (beta and gamma). Next we demonstrated that regions with stronger baseline evoked spectral responses were more likely to undergo plasticity after stimulation. These findings were specific to a given frequency in a specific temporal window. Post-stimulation power changes were driven by the interaction between direction of change in baseline power and temporal window of change. Finally, regions exhibiting early increases and late decreases in evoked baseline power exhibited power changes after stimulation and were independent of stimulation location. Together, these findings that time-frequency baseline features predict post-stimulation plasticity effects demonstrate properties akin to Hebbian learning in humans and extend this theory to the temporal and spectral window of interest. These findings can help improve our understanding of human brain plasticity and lead to more effective brain stimulation techniques. Significance Statement Brain stimulation is increasingly used to treat neuropsychiatric disorders by inducing changes in neural activity at specific brain regions. Despite their effectiveness, how these changes occur, specifically in the spectral domain, is unknown. To better understand how brain oscillations change after patterned stimulation, we performed focused stimulation in epilepsy patients and measured intracranial brain recordings. We found strong and predictable changes in brain oscillations (plasticity) after patterned stimulation. Specifically, low frequencies showing widespread effects and high frequencies exhibiting a greater magnitude of change. These changes were directly related to the temporal and spectral structure of brain responses prior to stimulation. Our study reveals that baseline brain activity patterns can predict how stimulation will induce plasticity in the spectral domain. These findings can help improve our understanding of human brain plasticity and lead to more effective brain stimulation techniques. Highlights We applied 15 minutes of repetitive 10Hz focal electrical stimulation and assessed the evoked brain-wide spectral changes with intracranial EEG.10Hz stimulation induced short-term plasticity in low frequency alpha evoked power broadly across regions and time windows and high frequency (beta, gamma) power specifically in early evoked time windows (10-50ms).Across patients, frequency bands, and time windows, brain regions with stronger baseline evoked power were more likely to undergo greater spectral changes after 10Hz stimulation.Post-stimulation spectral changes were specific; that is, for a given frequency band in a specific time window, baseline evoked power predicted post-stimulation change in the same frequency band and time window.Post-stimulation spectral change was driven by an interaction between direction of change and temporal window of baseline power; that is, regions exhibiting baseline evoked early (10-100ms) increases and late (100-200ms) decreases in power correlated with observed post-stimulation spectral changes.These results were independent of stimulation location.
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17
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Ojeda Valencia G, Gregg NM, Huang H, Lundstrom BN, Brinkmann BH, Pal Attia T, Van Gompel JJ, Bernstein MA, In MH, Huston J, Worrell GA, Miller KJ, Hermes D. Signatures of Electrical Stimulation Driven Network Interactions in the Human Limbic System. J Neurosci 2023; 43:6697-6711. [PMID: 37620159 PMCID: PMC10538586 DOI: 10.1523/jneurosci.2201-22.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 08/04/2023] [Accepted: 08/08/2023] [Indexed: 08/26/2023] Open
Abstract
Stimulation-evoked signals are starting to be used as biomarkers to indicate the state and health of brain networks. The human limbic network, often targeted for brain stimulation therapy, is involved in emotion and memory processing. Previous anatomic, neurophysiological, and functional studies suggest distinct subsystems within the limbic network (Rolls, 2015). Studies using intracranial electrical stimulation, however, have emphasized the similarities of the evoked waveforms across the limbic network. We test whether these subsystems have distinct stimulation-driven signatures. In eight patients (four male, four female) with drug-resistant epilepsy, we stimulated the limbic system with single-pulse electrical stimulation. Reliable corticocortical evoked potentials (CCEPs) were measured between hippocampus and the posterior cingulate cortex (PCC) and between the amygdala and the anterior cingulate cortex (ACC). However, the CCEP waveform in the PCC after hippocampal stimulation showed a unique and reliable morphology, which we term the "limbic Hippocampus-Anterior nucleus of the thalamus-Posterior cingulate, HAP-wave." This limbic HAP-wave was visually distinct and separately decoded from the CCEP waveform in ACC after amygdala stimulation. Diffusion MRI data show that the measured end points in the PCC overlap with the end points of the parolfactory cingulum bundle rather than the parahippocampal cingulum, suggesting that the limbic HAP-wave may travel through fornix, mammillary bodies, and the anterior nucleus of the thalamus (ANT). This was further confirmed by stimulating the ANT, which evoked the same limbic HAP-wave but with an earlier latency. Limbic subsystems have unique stimulation-evoked signatures that may be used in the future to help network pathology diagnosis.SIGNIFICANCE STATEMENT The limbic system is often compromised in diverse clinical conditions, such as epilepsy or Alzheimer's disease, and characterizing its typical circuit responses may provide diagnostic insight. Stimulation-evoked waveforms have been used in the motor system to diagnose circuit pathology. We translate this framework to limbic subsystems using human intracranial stereo EEG (sEEG) recordings that measure deeper brain areas. Our sEEG recordings describe a stimulation-evoked waveform characteristic to the memory and spatial subsystem of the limbic network that we term the "limbic HAP-wave." The limbic HAP-wave follows anatomic white matter pathways from hippocampus to thalamus to the posterior cingulum and shows promise as a distinct biomarker of signaling in the human brain memory and spatial limbic network.
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Affiliation(s)
- Gabriela Ojeda Valencia
- Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Nicholas M Gregg
- Department of Neurology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Harvey Huang
- Mayo Clinic Medical Scientist Training Program, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Brian N Lundstrom
- Department of Neurology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | | | - Tal Pal Attia
- Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Jamie J Van Gompel
- Department of Neurologic Surgery, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Matt A Bernstein
- Department of Radiology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Myung-Ho In
- Department of Radiology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - John Huston
- Department of Radiology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Gregory A Worrell
- Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota 55902
- Department of Neurology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Kai J Miller
- Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota 55902
- Department of Neurologic Surgery, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Dora Hermes
- Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota 55902
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18
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Seguin C, Sporns O, Zalesky A. Brain network communication: concepts, models and applications. Nat Rev Neurosci 2023; 24:557-574. [PMID: 37438433 DOI: 10.1038/s41583-023-00718-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/08/2023] [Indexed: 07/14/2023]
Abstract
Understanding communication and information processing in nervous systems is a central goal of neuroscience. Over the past two decades, advances in connectomics and network neuroscience have opened new avenues for investigating polysynaptic communication in complex brain networks. Recent work has brought into question the mainstay assumption that connectome signalling occurs exclusively via shortest paths, resulting in a sprawling constellation of alternative network communication models. This Review surveys the latest developments in models of brain network communication. We begin by drawing a conceptual link between the mathematics of graph theory and biological aspects of neural signalling such as transmission delays and metabolic cost. We organize key network communication models and measures into a taxonomy, aimed at helping researchers navigate the growing number of concepts and methods in the literature. The taxonomy highlights the pros, cons and interpretations of different conceptualizations of connectome signalling. We showcase the utility of network communication models as a flexible, interpretable and tractable framework to study brain function by reviewing prominent applications in basic, cognitive and clinical neurosciences. Finally, we provide recommendations to guide the future development, application and validation of network communication models.
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Affiliation(s)
- Caio Seguin
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia.
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Program in Cognitive Science, Indiana University, Bloomington, IN, USA
- Indiana University Network Science Institute, Indiana University, Bloomington, IN, USA
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, Melbourne School of Engineering, University of Melbourne, Melbourne, Victoria, Australia
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19
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Barbosa DAN, Gattas S, Salgado JS, Kuijper FM, Wang AR, Huang Y, Kakusa B, Leuze C, Luczak A, Rapp P, Malenka RC, Hermes D, Miller KJ, Heifets BD, Bohon C, McNab JA, Halpern CH. An orexigenic subnetwork within the human hippocampus. Nature 2023; 621:381-388. [PMID: 37648849 PMCID: PMC10499606 DOI: 10.1038/s41586-023-06459-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 07/20/2023] [Indexed: 09/01/2023]
Abstract
Only recently have more specific circuit-probing techniques become available to inform previous reports implicating the rodent hippocampus in orexigenic appetitive processing1-4. This function has been reported to be mediated at least in part by lateral hypothalamic inputs, including those involving orexigenic lateral hypothalamic neuropeptides, such as melanin-concentrating hormone5,6. This circuit, however, remains elusive in humans. Here we combine tractography, intracranial electrophysiology, cortico-subcortical evoked potentials, and brain-clearing 3D histology to identify an orexigenic circuit involving the lateral hypothalamus and converging in a hippocampal subregion. We found that low-frequency power is modulated by sweet-fat food cues, and this modulation was specific to the dorsolateral hippocampus. Structural and functional analyses of this circuit in a human cohort exhibiting dysregulated eating behaviour revealed connectivity that was inversely related to body mass index. Collectively, this multimodal approach describes an orexigenic subnetwork within the human hippocampus implicated in obesity and related eating disorders.
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Affiliation(s)
- Daniel A N Barbosa
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sandra Gattas
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, USA
| | - Juliana S Salgado
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Fiene Marie Kuijper
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA
- Université Paris Cité, Paris, France
- Assistance Publique des Hôpitaux de Paris, Paris, France
| | - Allan R Wang
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA
| | - Yuhao Huang
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA
| | - Bina Kakusa
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA
| | - Christoph Leuze
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Artur Luczak
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada
| | - Paul Rapp
- Department of Military & Emergency Medicine, Uniformed Services University, Bethesda, MD, USA
| | - Robert C Malenka
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Nancy Pritzker Laboratory, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Dora Hermes
- Department of Physiology & Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Kai J Miller
- Department of Neurosurgery, Mayo Clinic, Rochester, MN, USA
| | - Boris D Heifets
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Cara Bohon
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Jennifer A McNab
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Casey H Halpern
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Surgery, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA.
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20
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Parmigiani S, Ross JM, Cline CC, Minasi CB, Gogulski J, Keller CJ. Reliability and Validity of Transcranial Magnetic Stimulation-Electroencephalography Biomarkers. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:805-814. [PMID: 36894435 PMCID: PMC10276171 DOI: 10.1016/j.bpsc.2022.12.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 11/15/2022] [Accepted: 12/11/2022] [Indexed: 12/23/2022]
Abstract
Noninvasive brain stimulation and neuroimaging have revolutionized human neuroscience with a multitude of applications, including diagnostic subtyping, treatment optimization, and relapse prediction. It is therefore particularly relevant to identify robust and clinically valuable brain biomarkers linking symptoms to their underlying neural mechanisms. Brain biomarkers must be reproducible (i.e., have internal reliability) across similar experiments within a laboratory and be generalizable (i.e., have external reliability) across experimental setups, laboratories, brain regions, and disease states. However, reliability (internal and external) is not alone sufficient; biomarkers also must have validity. Validity describes closeness to a true measure of the underlying neural signal or disease state. We propose that these metrics, reliability and validity, should be evaluated and optimized before any biomarker is used to inform treatment decisions. Here, we discuss these metrics with respect to causal brain connectivity biomarkers from coupling transcranial magnetic stimulation (TMS) with electroencephalography (EEG). We discuss controversies around TMS-EEG stemming from the multiple large off-target components (noise) and relatively weak genuine brain responses (signal), as is unfortunately often the case in noninvasive human neuroscience. We review the current state of TMS-EEG recordings, which consist of a mix of reliable noise and unreliable signal. We describe methods for evaluating TMS-EEG biomarkers, including how to assess internal and external reliability across facilities, cognitive states, brain networks, and disorders and how to validate these biomarkers using invasive neural recordings or treatment response. We provide recommendations to increase reliability and validity, discuss lessons learned, and suggest future directions for the field.
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Affiliation(s)
- Sara Parmigiani
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, California; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, California; Wu Tsai Neuroscience Institute, Stanford, California
| | - Jessica M Ross
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, California; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, California; Wu Tsai Neuroscience Institute, Stanford, California
| | - Christopher C Cline
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, California; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, California; Wu Tsai Neuroscience Institute, Stanford, California
| | - Christopher B Minasi
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, California; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, California; Wu Tsai Neuroscience Institute, Stanford, California
| | - Juha Gogulski
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, California; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, California; Wu Tsai Neuroscience Institute, Stanford, California; Department of Clinical Neurophysiology, HUS Diagnostic Center, Clinical Neurosciences, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Corey J Keller
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, California; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, California; Wu Tsai Neuroscience Institute, Stanford, California.
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21
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Bernabei JM, Li A, Revell AY, Smith RJ, Gunnarsdottir KM, Ong IZ, Davis KA, Sinha N, Sarma S, Litt B. Quantitative approaches to guide epilepsy surgery from intracranial EEG. Brain 2023; 146:2248-2258. [PMID: 36623936 PMCID: PMC10232272 DOI: 10.1093/brain/awad007] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 12/11/2022] [Accepted: 12/28/2022] [Indexed: 01/11/2023] Open
Abstract
Over the past 10 years, the drive to improve outcomes from epilepsy surgery has stimulated widespread interest in methods to quantitatively guide epilepsy surgery from intracranial EEG (iEEG). Many patients fail to achieve seizure freedom, in part due to the challenges in subjective iEEG interpretation. To address this clinical need, quantitative iEEG analytics have been developed using a variety of approaches, spanning studies of seizures, interictal periods, and their transitions, and encompass a range of techniques including electrographic signal analysis, dynamical systems modeling, machine learning and graph theory. Unfortunately, many methods fail to generalize to new data and are sensitive to differences in pathology and electrode placement. Here, we critically review selected literature on computational methods of identifying the epileptogenic zone from iEEG. We highlight shared methodological challenges common to many studies in this field and propose ways that they can be addressed. One fundamental common pitfall is a lack of open-source, high-quality data, which we specifically address by sharing a centralized high-quality, well-annotated, multicentre dataset consisting of >100 patients to support larger and more rigorous studies. Ultimately, we provide a road map to help these tools reach clinical trials and hope to improve the lives of future patients.
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Affiliation(s)
- John M Bernabei
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Adam Li
- Department of Computer Science, Columbia University, New York, NY 10027, USA
| | - Andrew Y Revell
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rachel J Smith
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL 35294, USA
- Neuroengineering Program, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Kristin M Gunnarsdottir
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Ian Z Ong
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kathryn A Davis
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nishant Sinha
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sridevi Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Brian Litt
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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22
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Cornblath EJ, Lucas A, Armstrong C, Greenblatt AS, Stein JM, Hadar PN, Raghupathi R, Marsh E, Litt B, Davis KA, Conrad EC. Quantifying trial-by-trial variability during cortico-cortical evoked potential mapping of epileptogenic tissue. Epilepsia 2023; 64:1021-1034. [PMID: 36728906 PMCID: PMC10480141 DOI: 10.1111/epi.17528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 01/31/2023] [Accepted: 02/01/2023] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Measuring cortico-cortical evoked potentials (CCEPs) is a promising tool for mapping epileptic networks, but it is not known how variability in brain state and stimulation technique might impact the use of CCEPs for epilepsy localization. We test the hypotheses that (1) CCEPs demonstrate systematic variability across trials and (2) CCEP amplitudes depend on the timing of stimulation with respect to endogenous, low-frequency oscillations. METHODS We studied 11 patients who underwent CCEP mapping after stereo-electroencephalography electrode implantation for surgical evaluation of drug-resistant epilepsy. Evoked potentials were measured from all electrodes after each pulse of a 30 s, 1 Hz bipolar stimulation train. We quantified monotonic trends, phase dependence, and standard deviation (SD) of N1 (15-50 ms post-stimulation) and N2 (50-300 ms post-stimulation) amplitudes across the 30 stimulation trials for each patient. We used linear regression to quantify the relationship between measures of CCEP variability and the clinical seizure-onset zone (SOZ) or interictal spike rates. RESULTS We found that N1 and N2 waveforms exhibited both positive and negative monotonic trends in amplitude across trials. SOZ electrodes and electrodes with high interictal spike rates had lower N1 and N2 amplitudes with higher SD across trials. Monotonic trends of N1 and N2 amplitude were more positive when stimulating from an area with higher interictal spike rate. We also found intermittent synchronization of trial-level N1 amplitude with low-frequency phase in the hippocampus, which did not localize the SOZ. SIGNIFICANCE These findings suggest that standard approaches for CCEP mapping, which involve computing a trial-averaged response over a .2-1 Hz stimulation train, may be masking inter-trial variability that localizes to epileptogenic tissue. We also found that CCEP N1 amplitudes synchronize with ongoing low-frequency oscillations in the hippocampus. Further targeted experiments are needed to determine whether phase-locked stimulation could have a role in localizing epileptogenic tissue.
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Affiliation(s)
- Eli J. Cornblath
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Alfredo Lucas
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, Pennsylvania, USA
| | - Caren Armstrong
- Pediatric Epilepsy Program, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Adam S. Greenblatt
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Joel M. Stein
- Department of Radiology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Peter N. Hadar
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ramya Raghupathi
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Eric Marsh
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Pediatric Epilepsy Program, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Department of Pediatrics, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Brian Litt
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Kathryn A. Davis
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Erin C. Conrad
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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23
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Campbell JM, Davis TS, Anderson DN, Arain A, Inman CS, Smith EH, Rolston JD. Subsets of cortico-cortical evoked potentials propagate as traveling waves. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.27.534002. [PMID: 37034691 PMCID: PMC10081214 DOI: 10.1101/2023.03.27.534002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Emerging evidence suggests that the temporal dynamics of cortico-cortical evoked potentials (CCEPs) may be used to characterize the patterns of information flow between and within brain networks. At present, however, the spatiotemporal dynamics of CCEP propagation cortically and subcortically are incompletely understood. We hypothesized that CCEPs propagate as an evoked traveling wave emanating from the site of stimulation. To elicit CCEPs, we applied single-pulse stimulation to stereoelectroencephalography (SEEG) electrodes implanted in 21 adult patients with intractable epilepsy. For each robust CCEP, we measured the timing of the maximal descent in evoked local field potentials and broadband high-gamma power (70-150 Hz) envelopes relative to the distance between the recording and stimulation contacts using three different metrics (i.e., Euclidean distance, path length, geodesic distance), representing direct, subcortical, and transcortical propagation, respectively. Many evoked responses to single-pulse electrical stimulation appear to propagate as traveling waves (~17-30%), even in the sparsely sampled, three-dimensional SEEG space. These results provide new insights into the spatiotemporal dynamics of CCEP propagation.
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Affiliation(s)
- Justin M. Campbell
- MD-PhD Program, School of Medicine, University of Utah, Salt Lake City, UT, USA
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Tyler S. Davis
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Daria Nesterovich Anderson
- School of Biomedical Engineering, Faculty of Engineering, University of Sydney, Sydney, New South Wales, Australia
| | - Amir Arain
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
| | - Cory S. Inman
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Psychology, University of Utah, Salt Lake City, UT, USA
| | - Elliot H. Smith
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - John D. Rolston
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
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24
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Sawada M, Adolphs R, Dlouhy BJ, Jenison RL, Rhone AE, Kovach CK, Greenlee JDW, Howard Iii MA, Oya H. Mapping effective connectivity of human amygdala subdivisions with intracranial stimulation. Nat Commun 2022; 13:4909. [PMID: 35987994 PMCID: PMC9392722 DOI: 10.1038/s41467-022-32644-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 08/08/2022] [Indexed: 01/21/2023] Open
Abstract
The primate amygdala is a complex consisting of over a dozen nuclei that have been implicated in a host of cognitive functions, individual differences, and psychiatric illnesses. These functions are implemented through distinct connectivity profiles, which have been documented in animals but remain largely unknown in humans. Here we present results from 25 neurosurgical patients who had concurrent electrical stimulation of the amygdala with intracranial electroencephalography (electrical stimulation tract-tracing; es-TT), or fMRI (electrical stimulation fMRI; es-fMRI), methods providing strong inferences about effective connectivity of amygdala subdivisions with the rest of the brain. We quantified functional connectivity with medial and lateral amygdala, the temporal order of these connections on the timescale of milliseconds, and also detail second-order effective connectivity among the key nodes. These findings provide a uniquely detailed characterization of human amygdala functional connectivity that will inform functional neuroimaging studies in healthy and clinical populations.
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Affiliation(s)
- Masahiro Sawada
- Department of Neurosurgery, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
- Department of Neurosurgery, Tazuke Kofukai Medical Research Institute and Kitano Hospital, Osaka, Japan
| | - Ralph Adolphs
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA
| | - Brian J Dlouhy
- Department of Neurosurgery, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, USA
| | - Rick L Jenison
- Department of Neuroscience, University of Wisconsin - Madison, Madison, WI, USA
| | - Ariane E Rhone
- Department of Neurosurgery, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Christopher K Kovach
- Department of Neurosurgery, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Jeremy D W Greenlee
- Department of Neurosurgery, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, USA
| | - Matthew A Howard Iii
- Department of Neurosurgery, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, USA
- Pappajohn Biomedical Institute, University of Iowa, Iowa City, IA, USA
| | - Hiroyuki Oya
- Department of Neurosurgery, Carver College of Medicine, University of Iowa, Iowa City, IA, USA.
- Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, USA.
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25
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Smith EE, Choi KS, Veerakumar A, Obatusin M, Howell B, Smith AH, Tiruvadi V, Crowell AL, Riva-Posse P, Alagapan S, Rozell CJ, Mayberg HS, Waters AC. Time-frequency signatures evoked by single-pulse deep brain stimulation to the subcallosal cingulate. Front Hum Neurosci 2022; 16:939258. [PMID: 36061500 PMCID: PMC9433578 DOI: 10.3389/fnhum.2022.939258] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 07/25/2022] [Indexed: 11/17/2022] Open
Abstract
Precision targeting of specific white matter bundles that traverse the subcallosal cingulate (SCC) has been linked to efficacy of deep brain stimulation (DBS) for treatment resistant depression (TRD). Methods to confirm optimal target engagement in this heterogenous region are now critical to establish an objective treatment protocol. As yet unexamined are the time-frequency features of the SCC evoked potential (SCC-EP), including spectral power and phase-clustering. We examined these spectral features—evoked power and phase clustering—in a sample of TRD patients (n = 8) with implanted SCC stimulators. Electroencephalogram (EEG) was recorded during wakeful rest. Location of electrical stimulation in the SCC target region was the experimental manipulation. EEG was analyzed at the surface level with an average reference for a cluster of frontal sensors and at a time window identified by prior study (50–150 ms). Morlet wavelets generated indices of evoked power and inter-trial phase clustering. Enhanced phase clustering at theta frequency (4–7 Hz) was observed in every subject and was significantly correlated with SCC-EP magnitude, but only during left SCC stimulation. Stimulation to dorsal SCC evinced stronger phase clustering than ventral SCC. There was a weak correlation between phase clustering and white matter density. An increase in evoked delta power (2–4 Hz) was also coincident with SCC-EP, but was less consistent across participants. DBS evoked time-frequency features index mm-scale changes to the location of stimulation in the SCC target region and correlate with structural characteristics implicated in treatment optimization. Results also imply a shared generative mechanism (inter-trial phase clustering) between evoked potentials evinced by electrical stimulation and evoked potentials evinced by auditory/visual stimuli and behavioral tasks. Understanding how current injection impacts downstream cortical activity is essential to building new technologies that adapt treatment parameters to individual differences in neurophysiology.
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Affiliation(s)
| | - Ki Sueng Choi
- Departments of Psychiatry, Neuroscience, Neurology, Neurosurgery and Radiology, Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Ashan Veerakumar
- Department of Psychiatry, Schulich School of Medicine and Dentistry, London, ON, Canada
| | - Mosadoluwa Obatusin
- Departments of Psychiatry, Neuroscience, Neurology, Neurosurgery and Radiology, Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Bryan Howell
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
| | - Andrew H. Smith
- Departments of Psychiatry, Neuroscience, Neurology, Neurosurgery and Radiology, Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Vineet Tiruvadi
- Emory University School of Medicine, Atlanta, GA, United States
- Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA, United States
| | - Andrea L. Crowell
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Patricio Riva-Posse
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Sankaraleengam Alagapan
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Christopher J. Rozell
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Helen S. Mayberg
- Departments of Psychiatry, Neuroscience, Neurology, Neurosurgery and Radiology, Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Allison C. Waters
- Departments of Psychiatry, Neuroscience, Neurology, Neurosurgery and Radiology, Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- *Correspondence: Allison C. Waters,
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26
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Luo L, Chen G, Li S, Wang J, Wang Q, Fang F. Distinct roles of theta and gamma rhythms in inter-areal interaction in human visual cortex revealed by cortico-cortical evoked potentials. Brain Stimul 2022; 15:1048-1050. [PMID: 35931379 DOI: 10.1016/j.brs.2022.07.056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 07/26/2022] [Accepted: 07/28/2022] [Indexed: 11/02/2022] Open
Affiliation(s)
- Lu Luo
- School of Psychology, Beijing Sport University, Beijing, 100084, China
| | - Guanpeng Chen
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100871, China; IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Siqi Li
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, East China Normal University, Shanghai, 200062, China; NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai, 200062, China
| | - Jing Wang
- Department of Neurology, Sanbo Brain Hospital, Capital Medical University, Beijing, 100093, China
| | - Qian Wang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100871, China; IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
| | - Fang Fang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100871, China; IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
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27
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Anesthetic modulations dissociate neuroelectric characteristics between sensory-evoked and spontaneous activities across bilateral rat somatosensory cortical laminae. Sci Rep 2022; 12:11661. [PMID: 35804171 PMCID: PMC9270342 DOI: 10.1038/s41598-022-13759-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Accepted: 05/27/2022] [Indexed: 11/09/2022] Open
Abstract
Spontaneous neural activity has been widely adopted to construct functional connectivity (FC) amongst distant brain regions. Although informative, the functional role and signaling mechanism of the resting state FC are not intuitive as those in stimulus/task-evoked activity. In order to bridge the gap, we investigated anesthetic modulation of both resting-state and sensory-evoked activities. We used two well-studied GABAergic anesthetics of varying dose (isoflurane: 0.5–2.0% and α-chloralose: 30 and 60 mg/kg∙h) and recorded changes in electrophysiology using a pair of laminar electrode arrays that encompass the entire depth of the bilateral somatosensory cortices (S1fl) in rats. Specifically, the study focused to describe how varying anesthesia conditions affect the resting state activities and resultant FC between bilateral hemispheres in comparison to those obtained by evoked responses. As results, isoflurane decreased the amplitude of evoked responses in a dose-dependent manner mostly due to the habituation of repetitive responses. However, α-chloralose rather intensified the amplitude without exhibiting habituation. No such diverging trend was observed for the spontaneous activity, in which both anesthetics increased the signal power. For α-chloralose, overall FC was similar to that obtained with the lowest dose of isoflurane at 0.5% while higher doses of isoflurane displayed increased FC. Interestingly, only α-chloralose elicited relatively much greater increases in the ipsi-stimulus evoked response (i.e., in S1fl ipsilateral to the stimulated forelimb) than those associated with the contra-stimulus response, suggesting enhanced neuronal excitability. Taken together, the findings demonstrate modulation of the FC profiles by anesthesia is highly non-linear, possibly with a distinct underlying mechanism that affects either resting state or evoked activities differently. Further, the current study warrants thorough investigation of the basal neuronal states prior to the interpretation of resting state FC and evoked activities for accurate understanding of neural signal processing and circuitry.
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Moorjani S, Walvekar S, Fetz EE, Perlmutter SI. Movement-dependent electrical stimulation for volitional strengthening of cortical connections in behaving monkeys. Proc Natl Acad Sci U S A 2022; 119:e2116321119. [PMID: 35759657 PMCID: PMC9271159 DOI: 10.1073/pnas.2116321119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 04/29/2022] [Indexed: 12/30/2022] Open
Abstract
Correlated activity of neurons can lead to long-term strengthening or weakening of the connections between them. In addition, the behavioral context, imparted by execution of physical movements or the presence of a reward, can modulate the plasticity induced by Hebbian mechanisms. In the present study, we have combined behavior and induced neuronal correlations to strengthen connections in the motor cortex of adult behaving monkeys. Correlated activity was induced using an electrical-conditioning protocol in which stimuli gated by voluntary movements were used to produce coactivation of neurons at motor-cortical sites involved in those movements. Delivery of movement-dependent stimulation resulted in small increases in the strength of associated cortical connections immediately after conditioning. Remarkably, when paired with further repetition of the movements that gated the conditioning stimuli, there were substantially larger gains in the strength of cortical connections, which occurred in a use-dependent manner, without delivery of additional conditioning stimulation. In the absence of such movements, little change was observed in the strength of motor-cortical connections. Performance of the motor behavior in the absence of conditioning also did not produce any changes in connectivity. Our results show that combining movement-gated stimulation with further natural use of the "conditioned" pathways after stimulation ends can produce use-dependent strengthening of connections in adult primates, highlighting an important role for behavior in cortical plasticity. Our data also provide strong support for combining movement-gated stimulation with use-dependent physical rehabilitation for strengthening connections weakened by a stroke or spinal cord injury.
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Affiliation(s)
- Samira Moorjani
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195
- Washington National Primate Research Center, University of Washington, Seattle, WA 98195
- Center for Neurotechnology, University of Washington, Seattle, WA 98195
| | - Sarita Walvekar
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195
- Washington National Primate Research Center, University of Washington, Seattle, WA 98195
| | - Eberhard E Fetz
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195
- Washington National Primate Research Center, University of Washington, Seattle, WA 98195
- Center for Neurotechnology, University of Washington, Seattle, WA 98195
| | - Steve I Perlmutter
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195
- Washington National Primate Research Center, University of Washington, Seattle, WA 98195
- Center for Neurotechnology, University of Washington, Seattle, WA 98195
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Mercier MR, Dubarry AS, Tadel F, Avanzini P, Axmacher N, Cellier D, Vecchio MD, Hamilton LS, Hermes D, Kahana MJ, Knight RT, Llorens A, Megevand P, Melloni L, Miller KJ, Piai V, Puce A, Ramsey NF, Schwiedrzik CM, Smith SE, Stolk A, Swann NC, Vansteensel MJ, Voytek B, Wang L, Lachaux JP, Oostenveld R. Advances in human intracranial electroencephalography research, guidelines and good practices. Neuroimage 2022; 260:119438. [PMID: 35792291 DOI: 10.1016/j.neuroimage.2022.119438] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 05/23/2022] [Accepted: 06/30/2022] [Indexed: 12/11/2022] Open
Abstract
Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.
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Adkisson P, Fridman GY, Steinhardt CR. Difference in Network Effects of Pulsatile and Galvanic Stimulation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:3093-3099. [PMID: 36086346 DOI: 10.1109/embc48229.2022.9871812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Biphasic pulsatile stimulation is the present standard for neural prosthetic use, and it is used to understand connectivity and functionality of the brain in brain mapping studies. While pulses have been shown to drive behavioral changes, such as biasing decision making, they have deficits. For example, cochlear implants restore hearing but lack the ability to restore pitch perception. Recent work shows that pulses produce artificial synchrony in networks of neurons and non-linear changes in firing rate with pulse amplitude. Studies also show galvanic stimulation, delivery of current for extended periods of time, produces more naturalistic behavioral responses than pulses. In this paper, we use a winner-take-all decision-making network model to investigate differences between pulsatile and galvanic stimulation at the single neuron and network level while accurately modeling the effects of pulses on neurons for the first time. Results show pulses bias spike timing and make neurons more resistive to natural network inputs than galvanic stimulation at an equivalent current amplitude. Clinical Relevance- This establishes that pulsatile stimulation may disrupt natural spike timing and network-level interactions while certain parameterizations of galvanic stimulation avoid these effects and can drive network firing more naturally.
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Vlachos I, Kugiumtzis D, Paluš M. Phase-based causality analysis with partial mutual information from mixed embedding. CHAOS (WOODBURY, N.Y.) 2022; 32:053111. [PMID: 35649985 DOI: 10.1063/5.0087910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 04/18/2022] [Indexed: 06/15/2023]
Abstract
Instantaneous phases extracted from multivariate time series can retain information about the relationships between the underlying mechanisms that generate the series. Although phases have been widely used in the study of nondirectional coupling and connectivity, they have not found similar appeal in the study of causality. Herein, we present a new method for phase-based causality analysis, which combines ideas from the mixed embedding technique and the information-theoretic approach to causality in coupled oscillatory systems. We then use the introduced method to investigate causality in simulated datasets of bivariate, unidirectionally paired systems from combinations of Rössler, Lorenz, van der Pol, and Mackey-Glass equations. We observe that causality analysis using the phases can capture the true causal relation for coupling strength smaller than the analysis based on the amplitudes can capture. On the other hand, the causality estimation based on the phases tends to have larger variability, which is attributed more to the phase extraction process than the actual phase-based causality method. In addition, an application on real electroencephalographic data from an experiment on elicited human emotional states reinforces the usefulness of phases in causality identification.
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Affiliation(s)
- Ioannis Vlachos
- Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece
| | - Dimitris Kugiumtzis
- Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece
| | - Milan Paluš
- Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou věží 2, 182 07 Prague 8, Czech Republic
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32
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Patel P, Khalighinejad B, Herrero JL, Bickel S, Mehta AD, Mesgarani N. Improved Speech Hearing in Noise with Invasive Electrical Brain Stimulation. J Neurosci 2022; 42:3648-3658. [PMID: 35347046 PMCID: PMC9053855 DOI: 10.1523/jneurosci.1468-21.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 01/19/2022] [Accepted: 01/20/2022] [Indexed: 12/02/2022] Open
Abstract
Speech perception in noise is a challenging everyday task with which many listeners have difficulty. Here, we report a case in which electrical brain stimulation of implanted intracranial electrodes in the left planum temporale (PT) of a neurosurgical patient significantly and reliably improved subjective quality (up to 50%) and objective intelligibility (up to 97%) of speech in noise perception. Stimulation resulted in a selective enhancement of speech sounds compared with the background noises. The receptive fields of the PT sites whose stimulation improved speech perception were tuned to spectrally broad and rapidly changing sounds. Corticocortical evoked potential analysis revealed that the PT sites were located between the sites in Heschl's gyrus and the superior temporal gyrus. Moreover, the discriminability of speech from nonspeech sounds increased in population neural responses from Heschl's gyrus to the PT to the superior temporal gyrus sites. These findings causally implicate the PT in background noise suppression and may point to a novel potential neuroprosthetic solution to assist in the challenging task of speech perception in noise.SIGNIFICANCE STATEMENT Speech perception in noise remains a challenging task for many individuals. Here, we present a case in which the electrical brain stimulation of intracranially implanted electrodes in the planum temporale of a neurosurgical patient significantly improved both the subjective quality (up to 50%) and objective intelligibility (up to 97%) of speech perception in noise. Stimulation resulted in a selective enhancement of speech sounds compared with the background noises. Our local and network-level functional analyses placed the planum temporale sites in between the sites in the primary auditory areas in Heschl's gyrus and nonprimary auditory areas in the superior temporal gyrus. These findings causally implicate planum temporale in acoustic scene analysis and suggest potential neuroprosthetic applications to assist hearing in noise.
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Affiliation(s)
- Prachi Patel
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, New York 10027
- Department of Electrical Engineering, Columbia University, New York, New York 10027
| | - Bahar Khalighinejad
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, New York 10027
- Department of Electrical Engineering, Columbia University, New York, New York 10027
| | - Jose L Herrero
- Hofstra Northwell School of Medicine, New York, New York 11549
- Feinstein Institute for Medical Research, New York, New York 11030
| | - Stephan Bickel
- Hofstra Northwell School of Medicine, New York, New York 11549
- Feinstein Institute for Medical Research, New York, New York 11030
| | - Ashesh D Mehta
- Hofstra Northwell School of Medicine, New York, New York 11549
- Feinstein Institute for Medical Research, New York, New York 11030
| | - Nima Mesgarani
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, New York 10027
- Department of Electrical Engineering, Columbia University, New York, New York 10027
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Parmigiani S, Mikulan EP, Russo S, Sarasso S, Zauli FM, Rubino A, Cattani A, Fecchio M, Giampiccolo D, Lanzone J, D'Orio P, Del Vecchio M, Avanzini P, Nobili L, Sartori I, Massimini M, Pigorini A. Simultaneous stereo-EEG and high-density scalp EEG recordings to study the effects of intracerebral stimulation parameters. Brain Stimul 2022; 15:664-675. [PMID: 35421585 DOI: 10.1016/j.brs.2022.04.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 04/06/2022] [Accepted: 04/06/2022] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Cortico-cortical evoked potentials (CCEPs) recorded by stereo-electroencephalography (SEEG) are a valuable tool to investigate brain reactivity and effective connectivity. However, invasive recordings are spatially sparse since they depend on clinical needs. This sparsity hampers systematic comparisons across-subjects, the detection of the whole-brain effects of intracortical stimulation, as well as their relationships to the EEG responses evoked by non-invasive stimuli. OBJECTIVE To demonstrate that CCEPs recorded by high-density electroencephalography (hd-EEG) provide additional information with respect SEEG alone and to provide an open, curated dataset to allow for further exploration of their potential. METHODS The dataset encompasses SEEG and hd-EEG recordings simultaneously acquired during Single Pulse Electrical Stimulation (SPES) in drug-resistant epileptic patients (N = 36) in whom stimulations were delivered with different physical, geometrical, and topological parameters. Differences in CCEPs were assessed by amplitude, latency, and spectral measures. RESULTS While invasively and non-invasively recorded CCEPs were generally correlated, differences in pulse duration, angle and stimulated cortical area were better captured by hd-EEG. Further, intracranial stimulation evoked site-specific hd-EEG responses that reproduced the spectral features of EEG responses to transcranial magnetic stimulation (TMS). Notably, SPES, albeit unperceived by subjects, elicited scalp responses that were up to one order of magnitude larger than the responses typically evoked by sensory stimulation in awake humans. CONCLUSIONS CCEPs can be simultaneously recorded with SEEG and hd-EEG and the latter provides a reliable descriptor of the effects of SPES as well as a common reference to compare the whole-brain effects of intracortical stimulation to those of non-invasive transcranial or sensory stimulations in humans.
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Affiliation(s)
- S Parmigiani
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy
| | - E P Mikulan
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy
| | - S Russo
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy; Department of Philosophy "Piero Martinetti", Università degli Studi di Milano, Milan, Italy
| | - S Sarasso
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy
| | - F M Zauli
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy; Department of Philosophy "Piero Martinetti", Università degli Studi di Milano, Milan, Italy
| | - A Rubino
- "C. Munari" Epilepsy Surgery Centre, Department of Neuroscience, Niguarda Hospital, Milan, Italy
| | - A Cattani
- Department of Mathematics & Statistics, Boston University, Boston, MA, USA
| | - M Fecchio
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - D Giampiccolo
- Department of Neurosurgery, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, UK; Institute of Neurosciences, Cleveland Clinic London, London, UK
| | - J Lanzone
- Department of Systems Medicine, Neuroscience, University of Rome Tor Vergata, Rome, Italy; Istituti Clinici Scientifici Maugeri, IRCCS, Neurorehabilitation Department of Milano Institute, Milan, Italy
| | - P D'Orio
- "C. Munari" Epilepsy Surgery Centre, Department of Neuroscience, Niguarda Hospital, Milan, Italy; Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, Parma, Italy
| | - M Del Vecchio
- Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, Parma, Italy
| | - P Avanzini
- Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, Parma, Italy
| | - L Nobili
- Child Neuropsychiatry, IRCCS Istituto G. Gaslini, Genova, Italy
| | - I Sartori
- "C. Munari" Epilepsy Surgery Centre, Department of Neuroscience, Niguarda Hospital, Milan, Italy
| | - M Massimini
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy; Istituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan, Italy; Azrieli Program in Brain, Mind and Consciousness, Canadian Institute for Advanced Research, Toronto, Canada
| | - A Pigorini
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy; Department of Biomedical, V, Università degli Studi di Milano, Milan, Italy.
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Parvizi J, Veit MJ, Barbosa DA, Kucyi A, Perry C, Parker JJ, Shivacharan RS, Chen F, Yih J, Gross JJ, Fisher R, McNab JA, Falco-Walter J, Halpern CH. Complex negative emotions induced by electrical stimulation of the human hypothalamus. Brain Stimul 2022; 15:615-623. [DOI: 10.1016/j.brs.2022.04.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 03/21/2022] [Accepted: 04/05/2022] [Indexed: 11/02/2022] Open
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Scheid BH, Bernabei JM, Khambhati AN, Mouchtaris S, Jeschke J, Bassett DS, Becker D, Davis KA, Lucas T, Doyle W, Chang EF, Friedman D, Rao VR, Litt B. Intracranial electroencephalographic biomarker predicts effective responsive neurostimulation for epilepsy prior to treatment. Epilepsia 2022; 63:652-662. [PMID: 34997577 PMCID: PMC9887634 DOI: 10.1111/epi.17163] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 11/22/2021] [Accepted: 12/27/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Despite the overall success of responsive neurostimulation (RNS) therapy for drug-resistant focal epilepsy, clinical outcomes in individuals vary significantly and are hard to predict. Biomarkers that indicate the clinical efficacy of RNS-ideally before device implantation-are critically needed, but challenges include the intrinsic heterogeneity of the RNS patient population and variability in clinical management across epilepsy centers. The aim of this study is to use a multicenter dataset to evaluate a candidate biomarker from intracranial electroencephalographic (iEEG) recordings that predicts clinical outcome with subsequent RNS therapy. METHODS We assembled a federated dataset of iEEG recordings, collected prior to RNS implantation, from a retrospective cohort of 30 patients across three major epilepsy centers. Using ictal iEEG recordings, each center independently calculated network synchronizability, a candidate biomarker indicating the susceptibility of epileptic brain networks to RNS therapy. RESULTS Ictal measures of synchronizability in the high-γ band (95-105 Hz) significantly distinguish between good and poor RNS responders after at least 3 years of therapy under the current RNS therapy guidelines (area under the curve = .83). Additionally, ictal high-γ synchronizability is inversely associated with the degree of therapeutic response. SIGNIFICANCE This study provides a proof-of-concept roadmap for collaborative biomarker evaluation in federated data, where practical considerations impede full data sharing across centers. Our results suggest that network synchronizability can help predict therapeutic response to RNS therapy. With further validation, this biomarker could facilitate patient selection and help avert a costly, invasive intervention in patients who are unlikely to benefit.
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Affiliation(s)
- Brittany H. Scheid
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John M. Bernabei
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ankit N. Khambhati
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA,Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Sofia Mouchtaris
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jay Jeschke
- Comprehensive Epilepsy Center, NYU Langone Health, New York, New York, USA
| | - Dani S. Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Santa Fe Institute, Santa Fe, New Mexico, USA
| | - Danielle Becker
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kathryn A. Davis
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Timothy Lucas
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Werner Doyle
- Department of Neurosurgery, NYU Langone, New York, New York, USA
| | - Edward F. Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA,Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Daniel Friedman
- Comprehensive Epilepsy Center, NYU Langone Health, New York, New York, USA,Department of Neurology, NYU Langone, New York, New York, USA
| | - Vikram R. Rao
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Brian Litt
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Paulk AC, Zelmann R, Crocker B, Widge AS, Dougherty DD, Eskandar EN, Weisholtz DS, Richardson RM, Cosgrove GR, Williams ZM, Cash SS. Local and distant cortical responses to single pulse intracranial stimulation in the human brain are differentially modulated by specific stimulation parameters. Brain Stimul 2022; 15:491-508. [PMID: 35247646 PMCID: PMC8985164 DOI: 10.1016/j.brs.2022.02.017] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 02/23/2022] [Accepted: 02/24/2022] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Electrical neuromodulation via direct electrical stimulation (DES) is an increasingly common therapy for a wide variety of neuropsychiatric diseases. Unfortunately, therapeutic efficacy is inconsistent, likely due to our limited understanding of the relationship between the massive stimulation parameter space and brain tissue responses. OBJECTIVE To better understand how different parameters induce varied neural responses, we systematically examined single pulse-induced cortico-cortico evoked potentials (CCEP) as a function of stimulation amplitude, duration, brain region, and whether grey or white matter was stimulated. METHODS We measured voltage peak amplitudes and area under the curve (AUC) of intracranially recorded stimulation responses as a function of distance from the stimulation site, pulse width, current injected, location relative to grey and white matter, and brain region stimulated (N = 52, n = 719 stimulation sites). RESULTS Increasing stimulation pulse width increased responses near the stimulation location. Increasing stimulation amplitude (current) increased both evoked amplitudes and AUC nonlinearly. Locally (<15 mm), stimulation at the boundary between grey and white matter induced larger responses. In contrast, for distant sites (>15 mm), white matter stimulation consistently produced larger responses than stimulation in or near grey matter. The stimulation location-response curves followed different trends for cingulate, lateral frontal, and lateral temporal cortical stimulation. CONCLUSION These results demonstrate that a stronger local response may require stimulation in the grey-white boundary while stimulation in the white matter could be needed for network activation. Thus, stimulation parameters tailored for a specific anatomical-functional outcome may be key to advancing neuromodulatory therapy.
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Affiliation(s)
- Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
| | - Rina Zelmann
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Britni Crocker
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA; Harvard-MIT Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Alik S Widge
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, 02129, USA
| | - Darin D Dougherty
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, 02129, USA
| | - Emad N Eskandar
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Daniel S Weisholtz
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, 02114, USA
| | - R Mark Richardson
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, 02114, USA
| | - Ziv M Williams
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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Boulogne S, Pizzo F, Chatard B, Roehri N, Catenoix H, Ostrowsky‐Coste K, Giusiano B, Guenot M, Carron R, Bartolomei F, Rheims S. Functional connectivity and epileptogenicity of nodular heterotopias: A single‐pulse stimulation study. Epilepsia 2022; 63:961-973. [DOI: 10.1111/epi.17168] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 01/06/2022] [Accepted: 01/06/2022] [Indexed: 11/28/2022]
Affiliation(s)
- Sébastien Boulogne
- Department of Functional Neurology and Epileptology Hospices Civils de Lyon and University of Lyon Lyon France
- Lyon's Neurosciences Research Center INSERM U1028 CNRS 5292 Lyon France
- Lyon 1 University Villeurbanne France
| | - Francesca Pizzo
- Inserm, INS Institut de Neurosciences des Systèmes Aix Marseille University Marseille France
- Epileptology and Cerebral Rythmology Department Assistance Publique – Hôpitaux de Marseille Marseille France
| | - Benoit Chatard
- Lyon's Neurosciences Research Center INSERM U1028 CNRS 5292 Lyon France
| | - Nicolas Roehri
- Inserm, INS Institut de Neurosciences des Systèmes Aix Marseille University Marseille France
| | - Hélène Catenoix
- Department of Functional Neurology and Epileptology Hospices Civils de Lyon and University of Lyon Lyon France
- Lyon's Neurosciences Research Center INSERM U1028 CNRS 5292 Lyon France
| | - Karine Ostrowsky‐Coste
- Lyon's Neurosciences Research Center INSERM U1028 CNRS 5292 Lyon France
- Epileptology, Sleep Disorders and Functional Pediatric Neurology Hospices Civils de Lyon and University of Lyon Lyon France
| | - Bernard Giusiano
- Inserm, INS Institut de Neurosciences des Systèmes Aix Marseille University Marseille France
- Epileptology and Cerebral Rythmology Department Assistance Publique – Hôpitaux de Marseille Marseille France
| | - Marc Guenot
- Lyon's Neurosciences Research Center INSERM U1028 CNRS 5292 Lyon France
- Department of Functional Neurosurgery Hospices Civils de Lyon and University of Lyon Lyon France
| | - Romain Carron
- Department of Functional Neurosurgery Assistance Publique –Hôpitaux de Marseille Marseille France
| | - Fabrice Bartolomei
- Inserm, INS Institut de Neurosciences des Systèmes Aix Marseille University Marseille France
- Epileptology and Cerebral Rythmology Department Assistance Publique – Hôpitaux de Marseille Marseille France
| | - Sylvain Rheims
- Department of Functional Neurology and Epileptology Hospices Civils de Lyon and University of Lyon Lyon France
- Lyon's Neurosciences Research Center INSERM U1028 CNRS 5292 Lyon France
- Lyon 1 University Villeurbanne France
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38
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Titov O, Bykanov A, Pitskhelauri D, Danilov G. Neuromonitoring of the language pathways using cortico-cortical evoked potentials: a systematic review and meta-analysis. Neurosurg Rev 2022; 45:1883-1894. [PMID: 35031897 DOI: 10.1007/s10143-021-01718-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 11/18/2021] [Accepted: 12/08/2021] [Indexed: 10/19/2022]
Abstract
Cortico-cortical evoked potentials (CCEPs) are a surge in activity of one cortical zone caused by stimulation of another cortical zone. Recording of CCEP may be a useful method of intraoperative monitoring of the brain pathways, particularly of the language-related tracts. We aimed to conduct a systematic review and meta-analysis, dedicated to the clinical question: Does the CCEP recording effectively predict the postoperative speech deficits in neurosurgical patients? We conducted language-restricted PubMed, Google Scholar, Scopus, and Cochrane database search for eligible studies of CCEP published until March 2021. There were 4 articles (3 case series and 1 case report), which met our inclusion/exclusion criteria. A total of 32 patients (30 cases of tumors and 2 cavernomas) included in the analysis were divided into two cohorts - quantitative and qualitative, in accordance with the method of evaluating changes in the amplitude of CCEP after the lesion resection and postoperative alterations in speech function. Quantitative variables were studied using the Spearman rank correlation coefficient. Categorical variables were compared in groups by Fisher's exact test. We found a strong positive correlation between the decrease in the N1 wave amplitude and the severity of postoperative speech deficits (quantitative cohort: r = 0.57, p = 0.01; qualitative cohort: p = 0.02). Thus, the CCEP method using the N1 wave amplitude as a marker enables to effectively predict postoperative speech outcomes. Nevertheless, the low level of evidence for the included works indicated the necessity for additional research on this issue.
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Affiliation(s)
- Oleg Titov
- Burdenko Neurosurgery Center, Moscow, Russia. .,OPEN BRAIN - Neurosurgical Laboratory of Open Access, Moscow, Russia.
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39
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Fan JM, Lee AT, Kudo K, Ranasinghe KG, Morise H, Findlay AM, Kirsch HE, Chang EF, Nagarajan SS, Rao VR. Network connectivity predicts effectiveness of responsive neurostimulation in focal epilepsy. Brain Commun 2022; 4:fcac104. [PMID: 35611310 PMCID: PMC9123848 DOI: 10.1093/braincomms/fcac104] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/23/2022] [Accepted: 04/21/2022] [Indexed: 11/13/2022] Open
Abstract
Responsive neurostimulation is a promising treatment for drug-resistant focal epilepsy; however, clinical outcomes are highly variable across individuals. The therapeutic mechanism of responsive neurostimulation likely involves modulatory effects on brain networks; however, with no known biomarkers that predict clinical response, patient selection remains empiric. This study aimed to determine whether functional brain connectivity measured non-invasively prior to device implantation predicts clinical response to responsive neurostimulation therapy. Resting-state magnetoencephalography was obtained in 31 participants with subsequent responsive neurostimulation device implantation between 15 August 2014 and 1 October 2020. Functional connectivity was computed across multiple spatial scales (global, hemispheric, and lobar) using pre-implantation magnetoencephalography and normalized to maps of healthy controls. Normalized functional connectivity was investigated as a predictor of clinical response, defined as percent change in self-reported seizure frequency in the most recent year of clinic visits relative to pre-responsive neurostimulation baseline. Area under the receiver operating characteristic curve quantified the performance of functional connectivity in predicting responders (≥50% reduction in seizure frequency) and non-responders (<50%). Leave-one-out cross-validation was furthermore performed to characterize model performance. The relationship between seizure frequency reduction and frequency-specific functional connectivity was further assessed as a continuous measure. Across participants, stimulation was enabled for a median duration of 52.2 (interquartile range, 27.0-62.3) months. Demographics, seizure characteristics, and responsive neurostimulation lead configurations were matched across 22 responders and 9 non-responders. Global functional connectivity in the alpha and beta bands were lower in non-responders as compared with responders (alpha, pfdr < 0.001; beta, pfdr < 0.001). The classification of responsive neurostimulation outcome was improved by combining feature inputs; the best model incorporated four features (i.e. mean and dispersion of alpha and beta bands) and yielded an area under the receiver operating characteristic curve of 0.970 (0.919-1.00). The leave-one-out cross-validation analysis of this four-feature model yielded a sensitivity of 86.3%, specificity of 77.8%, positive predictive value of 90.5%, and negative predictive value of 70%. Global functional connectivity in alpha band correlated with seizure frequency reduction (alpha, P = 0.010). Global functional connectivity predicted responder status more strongly, as compared with hemispheric predictors. Lobar functional connectivity was not a predictor. These findings suggest that non-invasive functional connectivity may be a candidate personalized biomarker that has the potential to predict responsive neurostimulation effectiveness and to identify patients most likely to benefit from responsive neurostimulation therapy. Follow-up large-cohort, prospective studies are required to validate this biomarker. These findings furthermore support an emerging view that the therapeutic mechanism of responsive neurostimulation involves network-level effects in the brain.
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Affiliation(s)
- Joline M Fan
- Department of Neurology and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Anthony T Lee
- Department of Neurosurgery, University of California San Francisco, San Francisco, CA, USA
| | - Kiwamu Kudo
- Medical Imaging Center, Ricoh Company, Ltd., Kanazawa, Japan.,Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Kamalini G Ranasinghe
- Department of Neurology and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Hirofumi Morise
- Medical Imaging Center, Ricoh Company, Ltd., Kanazawa, Japan.,Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Anne M Findlay
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Heidi E Kirsch
- Department of Neurology and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.,Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Edward F Chang
- Department of Neurosurgery, University of California San Francisco, San Francisco, CA, USA
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Vikram R Rao
- Department of Neurology and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
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40
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Wendt K, Denison T, Foster G, Krinke L, Thomson A, Wilson S, Widge AS. Physiologically informed neuromodulation. J Neurol Sci 2021; 434:120121. [PMID: 34998239 PMCID: PMC8976285 DOI: 10.1016/j.jns.2021.120121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 12/19/2021] [Accepted: 12/21/2021] [Indexed: 01/09/2023]
Abstract
The rapid evolution of neuromodulation techniques includes an increasing amount of research into stimulation paradigms that are guided by patients' neurophysiology, to increase efficacy and responder rates. Treatment personalisation and target engagement have shown to be effective in fields such as Parkinson's disease, and closed-loop paradigms have been successfully implemented in cardiac defibrillators. Promising avenues are being explored for physiologically informed neuromodulation in psychiatry. Matching the stimulation frequency to individual brain rhythms has shown some promise in transcranial magnetic stimulation (TMS). Matching the phase of those rhythms may further enhance neuroplasticity, for instance when combining TMS with electroencephalographic (EEG) recordings. Resting-state EEG and event-related potentials may be useful to demonstrate connectivity between stimulation sites and connected areas. These techniques are available today to the psychiatrist to diagnose underlying sleep disorders, epilepsy, or lesions as contributing factors to the cause of depression. These technologies may also be useful in assessing the patient's brain network status prior to deciding on treatment options. Ongoing research using invasive recordings may allow for future identification of mood biomarkers and network structure. A core limitation is that biomarker research may currently be limited by the internal heterogeneity of psychiatric disorders according to the current DSM-based classifications. New approaches are being developed and may soon be validated. Finally, care must be taken when incorporating closed-loop capabilities into neuromodulation systems, by ensuring the safe operation of the system and understanding the physiological dynamics. Neurophysiological tools are rapidly evolving and will likely define the next generation of neuromodulation therapies.
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Affiliation(s)
- Karen Wendt
- Department of Engineering Science and MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
| | - Timothy Denison
- Department of Engineering Science and MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Gaynor Foster
- Welcony Inc., Plymouth, MN, United States of America
| | - Lothar Krinke
- Welcony Inc., Plymouth, MN, United States of America; Department of Neuroscience, School of Medicine, West Virginia University, Morgantown, WV, United States of America
| | - Alix Thomson
- Welcony Inc., Plymouth, MN, United States of America
| | - Saydra Wilson
- Department of Psychiatry and Behavioral Sciences, University of Minnesota-Twin Cities, Minneapolis, MN, United States of America
| | - Alik S Widge
- Department of Psychiatry and Behavioral Sciences, University of Minnesota-Twin Cities, Minneapolis, MN, United States of America; Medical Discovery Team on Additions, University of Minnesota, Minneapolis, MN, United States of America
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41
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Sonoda M, Silverstein BH, Jeong JW, Sugiura A, Nakai Y, Mitsuhashi T, Rothermel R, Luat AF, Sood S, Asano E. Six-dimensional dynamic tractography atlas of language connectivity in the developing brain. Brain 2021; 144:3340-3354. [PMID: 34849596 PMCID: PMC8677551 DOI: 10.1093/brain/awab225] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 05/23/2021] [Accepted: 06/05/2021] [Indexed: 11/12/2022] Open
Abstract
During a verbal conversation, our brain moves through a series of complex linguistic processing stages: sound decoding, semantic comprehension, retrieval of semantically coherent words, and overt production of speech outputs. Each process is thought to be supported by a network consisting of local and long-range connections bridging between major cortical areas. Both temporal and extratemporal lobe regions have functional compartments responsible for distinct language domains, including the perception and production of phonological and semantic components. This study provides quantitative evidence of how directly connected inter-lobar neocortical networks support distinct stages of linguistic processing across brain development. Novel six-dimensional tractography was used to intuitively visualize the strength and temporal dynamics of direct inter-lobar effective connectivity between cortical areas activated during each linguistic processing stage. We analysed 3401 non-epileptic intracranial electrode sites from 37 children with focal epilepsy (aged 5-20 years) who underwent extra-operative electrocorticography recording. Principal component analysis of auditory naming-related high-gamma modulations determined the relative involvement of each cortical area during each linguistic processing stage. To quantify direct effective connectivity, we delivered single-pulse electrical stimulation to 488 temporal and 1581 extratemporal lobe sites and measured the early cortico-cortical spectral responses at distant electrodes. Mixed model analyses determined the effects of naming-related high-gamma co-augmentation between connecting regions, age, and cerebral hemisphere on the strength of effective connectivity independent of epilepsy-related factors. Direct effective connectivity was strongest between extratemporal and temporal lobe site pairs, which were simultaneously activated between sentence offset and verbal response onset (i.e. response preparation period); this connectivity was approximately twice more robust than that with temporal lobe sites activated during stimulus listening or overt response. Conversely, extratemporal lobe sites activated during overt response were equally connected with temporal lobe language sites. Older age was associated with increased strength of inter-lobar effective connectivity especially between those activated during response preparation. The arcuate fasciculus supported approximately two-thirds of the direct effective connectivity pathways from temporal to extratemporal auditory language-related areas but only up to half of those in the opposite direction. The uncinate fasciculus consisted of <2% of those in the temporal-to-extratemporal direction and up to 6% of those in the opposite direction. We, for the first time, provided an atlas which quantifies and animates the strength, dynamics, and direction specificity of inter-lobar neural communications between language areas via the white matter pathways. Language-related effective connectivity may be strengthened in an age-dependent manner even after the age of 5.
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Affiliation(s)
- Masaki Sonoda
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
- Department of Neurosurgery, Yokohama City University, Yokohama, Kanagawa 2360004, Japan
| | - Brian H Silverstein
- Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA
| | - Jeong-Won Jeong
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
- Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA
- Department of Neurology, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
| | - Ayaka Sugiura
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
| | - Yasuo Nakai
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
- Department of Neurological Surgery, Wakayama Medical University, Wakayama, Wakayama 6418509, Japan
| | - Takumi Mitsuhashi
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
- Department of Neurosurgery, Juntendo University, School of Medicine, Tokyo, 1138421, Japan
| | - Robert Rothermel
- Department of Psychiatry, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
| | - Aimee F Luat
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
- Department of Neurology, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
- Department of Pediatrics, Central Michigan University, Mount Pleasant, MI 48858, USA
| | - Sandeep Sood
- Department of Neurosurgery, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
| | - Eishi Asano
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
- Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA
- Department of Neurology, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA
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42
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Hermann BP, Struck AF, Busch RM, Reyes A, Kaestner E, McDonald CR. Neurobehavioural comorbidities of epilepsy: towards a network-based precision taxonomy. Nat Rev Neurol 2021; 17:731-746. [PMID: 34552218 PMCID: PMC8900353 DOI: 10.1038/s41582-021-00555-z] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/10/2021] [Indexed: 02/06/2023]
Abstract
Cognitive and behavioural comorbidities are prevalent in childhood and adult epilepsies and impose a substantial human and economic burden. Over the past century, the classic approach to understanding the aetiology and course of these comorbidities has been through the prism of the medical taxonomy of epilepsy, including its causes, course, characteristics and syndromes. Although this 'lesion model' has long served as the organizing paradigm for the field, substantial challenges to this model have accumulated from diverse sources, including neuroimaging, neuropathology, neuropsychology and network science. Advances in patient stratification and phenotyping point towards a new taxonomy for the cognitive and behavioural comorbidities of epilepsy, which reflects the heterogeneity of their clinical presentation and raises the possibility of a precision medicine approach. As we discuss in this Review, these advances are informing the development of a revised aetiological paradigm that incorporates sophisticated neurobiological measures, genomics, comorbid disease, diversity and adversity, and resilience factors. We describe modifiable risk factors that could guide early identification, treatment and, ultimately, prevention of cognitive and broader neurobehavioural comorbidities in epilepsy and propose a road map to guide future research.
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Affiliation(s)
- Bruce P. Hermann
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.,
| | - Aaron F. Struck
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.,William S. Middleton Veterans Administration Hospital, Madison, WI, USA
| | - Robyn M. Busch
- Epilepsy Center and Department of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA.,Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Anny Reyes
- Department of Psychiatry and Center for Multimodal Imaging and Genetics, University of California, San Diego, San Diego, CA, USA
| | - Erik Kaestner
- Department of Psychiatry and Center for Multimodal Imaging and Genetics, University of California, San Diego, San Diego, CA, USA
| | - Carrie R. McDonald
- Department of Psychiatry and Center for Multimodal Imaging and Genetics, University of California, San Diego, San Diego, CA, USA
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43
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Temporal order of signal propagation within and across intrinsic brain networks. Proc Natl Acad Sci U S A 2021; 118:2105031118. [PMID: 34819365 DOI: 10.1073/pnas.2105031118] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/19/2021] [Indexed: 11/18/2022] Open
Abstract
We studied the temporal dynamics of activity within and across functional MRI (fMRI)-derived nodes of intrinsic resting-state networks of the human brain using intracranial electroencephalography (iEEG) and repeated single-pulse electrical stimulation (SPES) in neurosurgical subjects implanted with intracranial electrodes. We stimulated and recorded from 2,133 and 2,372 sites, respectively, in 29 subjects. We found that N1 and N2 segments of the evoked responses are associated with intra- and internetwork communications, respectively. In a separate cognitive experiment, evoked electrophysiological responses to visual target stimuli occurred with less temporal separation across pairs of electrodes that were located within the same fMRI-defined resting-state networks compared with those located across different resting-state networks. Our results suggest intranetwork prior to internetwork information processing at the subsecond timescale.
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44
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Lemaréchal JD, Jedynak M, Trebaul L, Boyer A, Tadel F, Bhattacharjee M, Deman P, Tuyisenge V, Ayoubian L, Hugues E, Chanteloup-Forêt B, Saubat C, Zouglech R, Reyes Mejia GC, Tourbier S, Hagmann P, Adam C, Barba C, Bartolomei F, Blauwblomme T, Curot J, Dubeau F, Francione S, Garcés M, Hirsch E, Landré E, Liu S, Maillard L, Metsähonkala EL, Mindruta I, Nica A, Pail M, Petrescu AM, Rheims S, Rocamora R, Schulze-Bonhage A, Szurhaj W, Taussig D, Valentin A, Wang H, Kahane P, George N, David O. A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials. Brain 2021; 145:1653-1667. [PMID: 35416942 PMCID: PMC9166555 DOI: 10.1093/brain/awab362] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 08/03/2021] [Accepted: 08/14/2021] [Indexed: 11/16/2022] Open
Abstract
Epilepsy presurgical investigation may include focal intracortical single-pulse electrical stimulations with depth electrodes, which induce cortico-cortical evoked potentials at distant sites because of white matter connectivity. Cortico-cortical evoked potentials provide a unique window on functional brain networks because they contain sufficient information to infer dynamical properties of large-scale brain connectivity, such as preferred directionality and propagation latencies. Here, we developed a biologically informed modelling approach to estimate the neural physiological parameters of brain functional networks from the cortico-cortical evoked potentials recorded in a large multicentric database. Specifically, we considered each cortico-cortical evoked potential as the output of a transient stimulus entering the stimulated region, which directly propagated to the recording region. Both regions were modelled as coupled neural mass models, the parameters of which were estimated from the first cortico-cortical evoked potential component, occurring before 80 ms, using dynamic causal modelling and Bayesian model inversion. This methodology was applied to the data of 780 patients with epilepsy from the F-TRACT database, providing a total of 34 354 bipolar stimulations and 774 445 cortico-cortical evoked potentials. The cortical mapping of the local excitatory and inhibitory synaptic time constants and of the axonal conduction delays between cortical regions was obtained at the population level using anatomy-based averaging procedures, based on the Lausanne2008 and the HCP-MMP1 parcellation schemes, containing 130 and 360 parcels, respectively. To rule out brain maturation effects, a separate analysis was performed for older (>15 years) and younger patients (<15 years). In the group of older subjects, we found that the cortico-cortical axonal conduction delays between parcels were globally short (median = 10.2 ms) and only 16% were larger than 20 ms. This was associated to a median velocity of 3.9 m/s. Although a general lengthening of these delays with the distance between the stimulating and recording contacts was observed across the cortex, some regions were less affected by this rule, such as the insula for which almost all efferent and afferent connections were faster than 10 ms. Synaptic time constants were found to be shorter in the sensorimotor, medial occipital and latero-temporal regions, than in other cortical areas. Finally, we found that axonal conduction delays were significantly larger in the group of subjects younger than 15 years, which corroborates that brain maturation increases the speed of brain dynamics. To our knowledge, this study is the first to provide a local estimation of axonal conduction delays and synaptic time constants across the whole human cortex in vivo, based on intracerebral electrophysiological recordings.
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Affiliation(s)
- Jean-Didier Lemaréchal
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, Centre MEG-EEG and Experimental Neurosurgery Team, F-75013 Paris, France.,Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France.,Aix Marseille Université, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Maciej Jedynak
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Lena Trebaul
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Anthony Boyer
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - François Tadel
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Manik Bhattacharjee
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Pierre Deman
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Viateur Tuyisenge
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Leila Ayoubian
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Etienne Hugues
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | | | - Carole Saubat
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Raouf Zouglech
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | | | - Sébastien Tourbier
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Claude Adam
- Department of Neurology, Epilepsy Unit, AP-HP, Hôpital de la Pitié Salpêtrière, F-75013 Paris, France
| | - Carmen Barba
- Neuroscience Department, Children's Hospital Meyer-University of Florence, Florence, Italy
| | - Fabrice Bartolomei
- Aix Marseille Université, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France.,Service de Neurophysiologie Clinique, APHM, Hôpitaux de la Timone, Marseille, France
| | - Thomas Blauwblomme
- Department of Pediatric Neurosurgery, Hôpital Necker-Enfants Malades, Université Paris V Descartes, Sorbonne Paris Cité, Paris, France
| | - Jonathan Curot
- Department of Neurophysiological Explorations, CerCo, CNRS, UMR5549, Centre Hospitalier Universitaire de Toulouse and University of Toulouse, Toulouse, France
| | - François Dubeau
- Montreal Neurological Institute and Hospital, Montreal, Canada
| | - Stefano Francione
- 'Claudio Munari' Centre for Epilepsy Surgery; Neuroscience Department, GOM, Niguarda, Milano, Italy
| | - Mercedes Garcés
- Multidisciplinary Epilepsy Unit, Hospital Universitario y Politécnico La Fe, Valencia, Spain
| | - Edouard Hirsch
- University Hospital, Department of Neurology, Strasbourg, France
| | | | - Sinclair Liu
- Canton Sanjiu Brain Hospital Epilepsy Center, Jinan University, Guangzhou, China
| | - Louis Maillard
- Centre Hospitalier Universitaire de Nancy, Nancy, France
| | | | - Ioana Mindruta
- Neurology Department, University Emergency Hospital, Bucharest, Romania
| | - Anca Nica
- Neurology Department, CIC 1414, Rennes University Hospital; LTSI, INSERM U 1099, F-35000 Rennes, France
| | - Martin Pail
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | | | - Sylvain Rheims
- Department of Functional Neurology and Epileptology, Hospices Civils de Lyon and Lyon's Neurosciences Research Center, INSERM U1028/CNRS UMR5292/Lyon 1 University, Lyon, France
| | - Rodrigo Rocamora
- Epilepsy Monitoring Unit, Department of Neurology, Hospital del Mar-IMIM, Barcelona, Spain
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - William Szurhaj
- Epilepsy Unit, Department of Clinical Neurophysiology, Lille University Medical Center, Lille, France
| | - Delphine Taussig
- Neurophysiology and Epilepsy Unit, Bicêtre Hospital, France.,Service de Neurochirurgie Pédiatrique, Fondation Rothschild, Paris, France
| | - Antonio Valentin
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), London, UK
| | - Haixiang Wang
- Yuquan Hospital Epilepsy Center, Tsinghua University, Beijing, China
| | - Philippe Kahane
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France.,Neurology Department, CHU Grenoble Alpes, Grenoble, France
| | - Nathalie George
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, Centre MEG-EEG and Experimental Neurosurgery Team, F-75013 Paris, France
| | - Olivier David
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France.,Aix Marseille Université, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
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45
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Electrocorticography reveals thalamic control of cortical dynamics following traumatic brain injury. Commun Biol 2021; 4:1210. [PMID: 34675341 PMCID: PMC8531397 DOI: 10.1038/s42003-021-02738-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 09/15/2021] [Indexed: 12/26/2022] Open
Abstract
The return of consciousness after traumatic brain injury (TBI) is associated with restoring complex cortical dynamics; however, it is unclear what interactions govern these complex dynamics. Here, we set out to uncover the mechanism underlying the return of consciousness by measuring local field potentials (LFP) using invasive electrophysiological recordings in patients recovering from TBI. We found that injury to the thalamus, and its efferent projections, on MRI were associated with repetitive and low complexity LFP signals from a highly structured phase space, resembling a low-dimensional ring attractor. But why do thalamic injuries in TBI patients result in a cortical attractor? We built a simplified thalamocortical model, which connotes that thalamic input facilitates the formation of cortical ensembles required for the return of cognitive function and the content of consciousness. These observations collectively support the view that thalamic input to the cortex enables rich cortical dynamics associated with consciousness.
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Scangos KW, Khambhati AN, Daly PM, Makhoul GS, Sugrue LP, Zamanian H, Liu TX, Rao VR, Sellers KK, Dawes HE, Starr PA, Krystal AD, Chang EF. Closed-loop neuromodulation in an individual with treatment-resistant depression. Nat Med 2021; 27:1696-1700. [PMID: 34608328 PMCID: PMC11219029 DOI: 10.1038/s41591-021-01480-w] [Citation(s) in RCA: 164] [Impact Index Per Article: 54.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 07/23/2021] [Indexed: 11/09/2022]
Abstract
Deep brain stimulation is a promising treatment for neuropsychiatric conditions such as major depression. It could be optimized by identifying neural biomarkers that trigger therapy selectively when symptom severity is elevated. We developed an approach that first used multi-day intracranial electrophysiology and focal electrical stimulation to identify a personalized symptom-specific biomarker and a treatment location where stimulation improved symptoms. We then implanted a chronic deep brain sensing and stimulation device and implemented a biomarker-driven closed-loop therapy in an individual with depression. Closed-loop therapy resulted in a rapid and sustained improvement in depression. Future work is required to determine if the results and approach of this n-of-1 study generalize to a broader population.
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Affiliation(s)
- Katherine W Scangos
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA.
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA.
| | - Ankit N Khambhati
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Neurosurgery, University of California, San Francisco, San Francisco, CA, USA
| | - Patrick M Daly
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Ghassan S Makhoul
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Leo P Sugrue
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Radiology, University of California, San Francisco, San Francisco, CA, USA
| | - Hashem Zamanian
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Tony X Liu
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Vikram R Rao
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Kristin K Sellers
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Neurosurgery, University of California, San Francisco, San Francisco, CA, USA
| | - Heather E Dawes
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Neurosurgery, University of California, San Francisco, San Francisco, CA, USA
| | - Philip A Starr
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Neurosurgery, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- Weill Institute for Neurosciences, University of California, San Francsico, CA, USA
- Department of Neurosurgery, University of California, San Francisco, San Francisco, CA, USA
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47
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Shahabi H, Taylor K, Hirfanoglu T, Koneru S, Bingaman W, Kobayashi K, Kobayashi M, Joshi A, Leahy RM, Mosher JC, Bulacio J, Nair D. Effective connectivity differs between focal cortical dysplasia types I and II. Epilepsia 2021; 62:2753-2765. [PMID: 34541666 DOI: 10.1111/epi.17064] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 08/26/2021] [Accepted: 08/26/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To determine whether brain connectivity differs between focal cortical dysplasia (FCD) types I and II. METHODS We compared cortico-cortical evoked potentials (CCEPs) as measures of effective brain connectivity in 25 FCD patients with drug-resistant focal epilepsy who underwent intracranial evaluation with stereo-electroencephalography (SEEG). We analyzed the amplitude and latency of CCEP responses following ictal-onset single-pulse electrical stimulation (iSPES). RESULTS In comparison to FCD type II, patients with type I demonstrated significantly larger responses in the electrodes near the ictal-onset zone (<50 mm). These findings persisted when controlling for the location of the epileptogenic zone, as noted in patients with temporal lobe epilepsies, as well as controlling for seizure type, as noted in patients with focal to bilateral tonic-clonic seizures (FBTCS). In type II, the root mean square (RMS) of CCEP responses dropped substantially from the early segment (10-60 ms) to the middle and late segments (60-600 ms). The middle and late CCEP latency segments showed the largest differences between FCD types I and II. SIGNIFICANCE Focal cortical dysplasia type I may have a greater degree of cortical hyperexcitability as compared with FCD type II. In addition, FCD type II displays a more restrictive area of hyperexcitability in both temporal and spatial domains. In patients with FBTCS and type I FCD, the increased amplitudes of RMS in the middle and late CCEP periods appear consistent with the cortico-thalamo-cortical network involvement of FBTCS. The notable differences in degree and extent of hyperexcitability may contribute to the different postsurgical seizure outcomes noted between these two pathological substrates.
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Affiliation(s)
- Hossein Shahabi
- Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, USA
| | - Kenneth Taylor
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Tugba Hirfanoglu
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Pediatric Neurology, School of Medicine, Gazi University, Ankara, Turkey
| | - Shreekanth Koneru
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - William Bingaman
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Katsuya Kobayashi
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Masako Kobayashi
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Anand Joshi
- Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, USA
| | - Richard M Leahy
- Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, USA
| | - John C Mosher
- University of Texas Health Sciences Center, Houston, TX, USA
| | - Juan Bulacio
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Dileep Nair
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
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48
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Miller KJ, Müller KR, Hermes D. Basis profile curve identification to understand electrical stimulation effects in human brain networks. PLoS Comput Biol 2021; 17:e1008710. [PMID: 34473701 PMCID: PMC8412306 DOI: 10.1371/journal.pcbi.1008710] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 07/21/2021] [Indexed: 11/21/2022] Open
Abstract
Brain networks can be explored by delivering brief pulses of electrical current in one area while measuring voltage responses in other areas. We propose a convergent paradigm to study brain dynamics, focusing on a single brain site to observe the average effect of stimulating each of many other brain sites. Viewed in this manner, visually-apparent motifs in the temporal response shape emerge from adjacent stimulation sites. This work constructs and illustrates a data-driven approach to determine characteristic spatiotemporal structure in these response shapes, summarized by a set of unique "basis profile curves" (BPCs). Each BPC may be mapped back to underlying anatomy in a natural way, quantifying projection strength from each stimulation site using simple metrics. Our technique is demonstrated for an array of implanted brain surface electrodes in a human patient. This framework enables straightforward interpretation of single-pulse brain stimulation data, and can be applied generically to explore the diverse milieu of interactions that comprise the connectome.
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Affiliation(s)
- Kai J. Miller
- Department of Neurological Surgery, Mayo Clinic, Rochester, Minnesota, United States of America
- Department of Biomedical Engineering & Physiology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Klaus-Robert Müller
- Google Research, Brain Team, Berlin, Germany
- Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Berlin, Germany
- Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea
- Max Planck Institute for Informatics, Saarbrücken, Germany
| | - Dora Hermes
- Department of Biomedical Engineering & Physiology, Mayo Clinic, Rochester, Minnesota, United States of America
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49
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Kudela P, Anderson WS. Impact of gyral geometry on cortical responses to surface electrical stimulation: insights from experimental and modeling studies. J Neural Eng 2021; 18. [PMID: 34407519 DOI: 10.1088/1741-2552/ac1ed3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 08/18/2021] [Indexed: 11/11/2022]
Abstract
Objective.Invasive simultaneous stimulation and recording from intracranial electrodes and microwire arrays were used to investigate direct cortical responses to single pulses of electrical stimulation in humans.Approach.Microwire contacts measured surface potentials in cortical microdomains at a distance of 2-6 mm from the intracranial electrode. Direct cortical responses to stimulation (<20 ms) consisted of a larger surface negative potentials.Main results. The latencies of these responses were directly or inversely correlated with distances between the intracranial electrode and microwire contacts. We hypothesize that surface negative potentials reflected local synchronous depolarization of apical dendrites of pyramidal neurons in cortical microdomains in the superficial cortical layer and resulted from the activation of gray matter axons that delivered excitatory inputs to apical dendrites after cortical stimulation. We further hypothesized that the positive or inverse distance-latency correlations of the recorded negative responses were measured depending on whether activation of neurons originated at one (crown) or multiple (crown, lip, bank) sites throughout the gyrus simultaneously. The inverse distance-latency correlations then reflected the spatiotemporal superposition of different nearby sources of neuronal recruitment in the gyrus. To prove this hypothesis, we built an anatomically informed and biophysically realistic cortical network model and simulated early responses of cortical neurons to electrical stimulation in this cortical network model. The model simulations yielded negative potentials in simulated microdomains in the cortical model consistent with those recorded from humans. The model predicted sensitivity of cortical responses to the alignment of the stimulating electrode and microwire array with respect to the cortical gyrus and confirmed that gyral geometry has a major impact on direct neuronal recruitment, the timing, and the time course of neuronal activation in cortical microdomains.Significance.In this work, we demonstrated how the high-resolution forward network models can be used for better understanding and detailed prediction of cortical stimulation effects. Accurate predictive modeling tools are needed for the progress of brain stimulation therapies.
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Affiliation(s)
- Pawel Kudela
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Meyer 8-181, 600 North Wolfe St, Baltimore, MD 21287, United States of America
| | - William S Anderson
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Meyer 8-181, 600 North Wolfe St, Baltimore, MD 21287, United States of America
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50
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Mariani V, Balestrini S, Gozzo F, Pelliccia V, Mai R, Francione S, Sartori I, Cardinale F, Tassi L. Intracerebral electrical stimulations of the temporal lobe: A stereoelectroencephalography study. Eur J Neurosci 2021; 54:5368-5383. [PMID: 34192818 DOI: 10.1111/ejn.15377] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 06/06/2021] [Accepted: 06/17/2021] [Indexed: 11/28/2022]
Abstract
The functional anatomy of the anteromesial portion of the temporal lobe and its involvement in epilepsy can be explored by means of intracerebral electrical stimulations. Here, we aimed to expand the knowledge of its physiological and pathophysiological symptoms by conducting the first large-sample systematic analysis of 1529 electrical stimulations of this anatomical region. We retrospectively analysed all clinical manifestations induced by intracerebral electrical stimulations in 173 patients with drug-resistant focal epilepsy with at least one electrode implanted in this area. We found that high-frequency stimulations were more likely to evoke electroclinical manifestations (p < .0001) and also provoked 'false positive' seizures. Multimodal symptoms were associated with EEG electrical modification (after discharge) (p < .0001). Visual symptoms were not associated with after discharge (p = .0002) and were mainly evoked by stimulation of the hippocampus (p = .009) and of the parahippocampal gyrus (p = .0212). 'False positive seizures' can be evoked by stimulation of the hippocampus, parahippocampal gyrus and amygdala, likely due to their intrinsic low epileptogenic threshold. Visual symptoms evoked in the hippocampus and parahippocampal gyrus, without EEG changes, are physiological symptoms and suggest involvement of these areas in the visual ventral stream. Our findings provide meaningful guidance in the interpretation of intracranial EEG studies of the temporal lobe.
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Affiliation(s)
- Valeria Mariani
- Neurology and Stroke Unit Divison, Circolo Hospital ASST Settelaghi University of Insubria, Varese, Italy.,"Claudio Munari" Epilepsy Surgery Centre, ASST GOM Niguarda, Milan, Italy
| | - Simona Balestrini
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology and Chalfont Centre for Epilepsy, London, UK.,Neuroscience Department, Meyer Children's Hospital-University of Florence, Florence, Italy
| | - Francesca Gozzo
- "Claudio Munari" Epilepsy Surgery Centre, ASST GOM Niguarda, Milan, Italy
| | - Veronica Pelliccia
- "Claudio Munari" Epilepsy Surgery Centre, ASST GOM Niguarda, Milan, Italy
| | - Roberto Mai
- "Claudio Munari" Epilepsy Surgery Centre, ASST GOM Niguarda, Milan, Italy
| | - Stefano Francione
- "Claudio Munari" Epilepsy Surgery Centre, ASST GOM Niguarda, Milan, Italy
| | - Ivana Sartori
- "Claudio Munari" Epilepsy Surgery Centre, ASST GOM Niguarda, Milan, Italy
| | | | - Laura Tassi
- "Claudio Munari" Epilepsy Surgery Centre, ASST GOM Niguarda, Milan, Italy
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