1
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Leonard MK, Gwilliams L, Sellers KK, Chung JE, Xu D, Mischler G, Mesgarani N, Welkenhuysen M, Dutta B, Chang EF. Large-scale single-neuron speech sound encoding across the depth of human cortex. Nature 2024; 626:593-602. [PMID: 38093008 PMCID: PMC10866713 DOI: 10.1038/s41586-023-06839-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 11/06/2023] [Indexed: 01/31/2024]
Abstract
Understanding the neural basis of speech perception requires that we study the human brain both at the scale of the fundamental computational unit of neurons and in their organization across the depth of cortex. Here we used high-density Neuropixels arrays1-3 to record from 685 neurons across cortical layers at nine sites in a high-level auditory region that is critical for speech, the superior temporal gyrus4,5, while participants listened to spoken sentences. Single neurons encoded a wide range of speech sound cues, including features of consonants and vowels, relative vocal pitch, onsets, amplitude envelope and sequence statistics. Neurons at each cross-laminar recording exhibited dominant tuning to a primary speech feature while also containing a substantial proportion of neurons that encoded other features contributing to heterogeneous selectivity. Spatially, neurons at similar cortical depths tended to encode similar speech features. Activity across all cortical layers was predictive of high-frequency field potentials (electrocorticography), providing a neuronal origin for macroelectrode recordings from the cortical surface. Together, these results establish single-neuron tuning across the cortical laminae as an important dimension of speech encoding in human superior temporal gyrus.
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Affiliation(s)
- Matthew K Leonard
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Laura Gwilliams
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jason E Chung
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Duo Xu
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Gavin Mischler
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | - Nima Mesgarani
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | | | | | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
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2
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Sellers KK, Cohen JL, Khambhati AN, Fan JM, Lee AM, Chang EF, Krystal AD. Closed-loop neurostimulation for the treatment of psychiatric disorders. Neuropsychopharmacology 2024; 49:163-178. [PMID: 37369777 PMCID: PMC10700557 DOI: 10.1038/s41386-023-01631-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/31/2023] [Accepted: 06/02/2023] [Indexed: 06/29/2023]
Abstract
Despite increasing prevalence and huge personal and societal burden, psychiatric diseases still lack treatments which can control symptoms for a large fraction of patients. Increasing insight into the neurobiology underlying these diseases has demonstrated wide-ranging aberrant activity and functioning in multiple brain circuits and networks. Together with varied presentation and symptoms, this makes one-size-fits-all treatment a challenge. There has been a resurgence of interest in the use of neurostimulation as a treatment for psychiatric diseases. Initial studies using continuous open-loop stimulation, in which clinicians adjusted stimulation parameters during patient visits, showed promise but also mixed results. Given the periodic nature and fluctuations of symptoms often observed in psychiatric illnesses, the use of device-driven closed-loop stimulation may provide more effective therapy. The use of a biomarker, which is correlated with specific symptoms, to deliver stimulation only during symptomatic periods allows for the personalized therapy needed for such heterogeneous disorders. Here, we provide the reader with background motivating the use of closed-loop neurostimulation for the treatment of psychiatric disorders. We review foundational studies of open- and closed-loop neurostimulation for neuropsychiatric indications, focusing on deep brain stimulation, and discuss key considerations when designing and implementing closed-loop neurostimulation.
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Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joshua L Cohen
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joline M Fan
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | - A Moses Lee
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
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3
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Windolf C, Yu H, Paulk AC, Meszéna D, Muñoz W, Boussard J, Hardstone R, Caprara I, Jamali M, Kfir Y, Xu D, Chung JE, Sellers KK, Ye Z, Shaker J, Lebedeva A, Raghavan M, Trautmann E, Melin M, Couto J, Garcia S, Coughlin B, Horváth C, Fiáth R, Ulbert I, Movshon JA, Shadlen MN, Churchland MM, Churchland AK, Steinmetz NA, Chang EF, Schweitzer JS, Williams ZM, Cash SS, Paninski L, Varol E. DREDge: robust motion correction for high-density extracellular recordings across species. bioRxiv 2023:2023.10.24.563768. [PMID: 37961359 PMCID: PMC10634799 DOI: 10.1101/2023.10.24.563768] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
High-density microelectrode arrays (MEAs) have opened new possibilities for systems neuroscience in human and non-human animals, but brain tissue motion relative to the array poses a challenge for downstream analyses, particularly in human recordings. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm which is well suited for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from spikes in the action potential (AP) frequency band, DREDge enables automated tracking of motion at high temporal resolution in the local field potential (LFP) frequency band. In human intraoperative recordings, which often feature fast (period <1s) motion, DREDge correction in the LFP band enabled reliable recovery of evoked potentials, and significantly reduced single-unit spike shape variability and spike sorting error. Applying DREDge to recordings made during deep probe insertions in nonhuman primates demonstrated the possibility of tracking probe motion of centimeters across several brain regions while simultaneously mapping single unit electrophysiological features. DREDge reliably delivered improved motion correction in acute mouse recordings, especially in those made with an recent ultra-high density probe. We also implemented a procedure for applying DREDge to recordings made across tens of days in chronic implantations in mice, reliably yielding stable motion tracking despite changes in neural activity across experimental sessions. Together, these advances enable automated, scalable registration of electrophysiological data across multiple species, probe types, and drift cases, providing a stable foundation for downstream scientific analyses of these rich datasets.
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Affiliation(s)
- Charlie Windolf
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
| | - Han Yu
- Zuckerman Institute, Columbia University
- Department of Electrical Engineering, Columbia University
| | - Angelique C Paulk
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Domokos Meszéna
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - William Muñoz
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Julien Boussard
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
| | - Richard Hardstone
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Irene Caprara
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Mohsen Jamali
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Yoav Kfir
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Duo Xu
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Jason E Chung
- Department of Neurological Surgery, University of California San Francisco
| | - Kristin K Sellers
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Zhiwen Ye
- Department of Biological Structure, University of Washington
| | - Jordan Shaker
- Department of Biological Structure, University of Washington
| | | | | | - Eric Trautmann
- Department of Neuroscience, Columbia University Medical Center
- Zuckerman Institute, Columbia University
- Grossman Center for the Statistics of Mind, Columbia University
| | - Max Melin
- David Geffen School of Medicine, University of California Los Angeles
| | - João Couto
- David Geffen School of Medicine, University of California Los Angeles
| | - Samuel Garcia
- Centre National de la Recherche Scientifique, Centre de Recherche en Neurosciences de Lyon
| | - Brian Coughlin
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Csaba Horváth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Richárd Fiáth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - István Ulbert
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | | | - Michael N Shadlen
- Zuckerman Institute, Columbia University
- Howard Hughes Medical Institute
| | | | - Anne K Churchland
- David Geffen School of Medicine, University of California Los Angeles
| | | | - Edward F Chang
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Jeffrey S Schweitzer
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Sydney S Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Liam Paninski
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
- Department of Neuroscience, Columbia University Medical Center
- Grossman Center for the Statistics of Mind, Columbia University
| | - Erdem Varol
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
- Department of Computer Science & Engineering, New York University
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4
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Sellers KK, Khambhati AN, Stapper N, Fan JM, Rao VR, Scangos KW, Chang EF, Krystal AD. Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder. J Vis Exp 2023. [PMID: 37486114 DOI: 10.3791/65177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2023] Open
Abstract
Deep brain stimulation involves the administration of electrical stimulation to targeted brain regions for therapeutic benefit. In the context of major depressive disorder (MDD), most studies to date have administered continuous or open-loop stimulation with promising but mixed results. One factor contributing to these mixed results may stem from when the stimulation is applied. Stimulation administration specific to high-symptom states in a personalized and responsive manner may be more effective at reducing symptoms compared to continuous stimulation and may avoid diminished therapeutic effects related to habituation. Additionally, a lower total duration of stimulation per day is advantageous for reducing device energy consumption. This protocol describes an experimental workflow using a chronically implanted neurostimulation device to achieve closed-loop stimulation for individuals with treatment-refractory MDD. This paradigm hinges on determining a patient-specific neural biomarker that is related to states of high symptoms and programming the device detectors, such that stimulation is triggered by this read-out of symptom state. The described procedures include how to obtain neural recordings concurrent with patient symptom reports, how to use these data in a state-space model approach to differentiate low- and high-symptom states and corresponding neural features, and how to subsequently program and tune the device to deliver closed-loop stimulation therapy.
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Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco; Weill Institute for Neurosciences, University of California, San Francisco;
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California, San Francisco; Weill Institute for Neurosciences, University of California, San Francisco
| | - Noah Stapper
- Weill Institute for Neurosciences, University of California, San Francisco; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
| | - Joline M Fan
- Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology, University of California, San Francisco
| | - Vikram R Rao
- Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology, University of California, San Francisco
| | - Katherine W Scangos
- Weill Institute for Neurosciences, University of California, San Francisco; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco; Weill Institute for Neurosciences, University of California, San Francisco
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
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5
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Fan JM, Lee AM, Sellers KK, Woodworth K, Makhoul GS, Liu TX, Henderson C, Astudillo Maya DA, Martinez R, Zamanian H, Speidel BA, Khambhati AN, Rao VR, Sugrue LP, Scangos KW, Chang EF, Krystal AD. Intracranial electrical stimulation of corticolimbic sites modulates arousal in humans. Brain Stimul 2023; 16:1072-1082. [PMID: 37385540 PMCID: PMC10634663 DOI: 10.1016/j.brs.2023.06.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 06/23/2023] [Accepted: 06/26/2023] [Indexed: 07/01/2023] Open
Abstract
BACKGROUND Humans routinely shift their sleepiness and wakefulness levels in response to emotional factors. The diversity of emotional factors that modulates sleep-wake levels suggests that the ascending arousal network may be intimately linked with networks that mediate mood. Indeed, while animal studies have identified select limbic structures that play a role in sleep-wake regulation, the breadth of corticolimbic structures that directly modulates arousal in humans remains unknown. OBJECTIVE We investigated whether select regional activation of the corticolimbic network through direct electrical stimulation can modulate sleep-wake levels in humans, as measured by subjective experience and behavior. METHODS We performed intensive inpatient stimulation mapping in two human participants with treatment resistant depression, who underwent intracranial implantation with multi-site, bilateral depth electrodes. Stimulation responses of sleep-wake levels were measured by subjective surveys (i.e. Stanford Sleepiness Scale and visual-analog scale of energy) and a behavioral arousal score. Biomarker analyses of sleep-wake levels were performed by assessing spectral power features of resting-state electrophysiology. RESULTS Our findings demonstrated three regions whereby direct stimulation modulated arousal, including the orbitofrontal cortex (OFC), subgenual cingulate (SGC), and, most robustly, ventral capsule (VC). Modulation of sleep-wake levels was frequency-specific: 100Hz OFC, SGC, and VC stimulation promoted wakefulness, whereas 1Hz OFC stimulation increased sleepiness. Sleep-wake levels were correlated with gamma activity across broad brain regions. CONCLUSIONS Our findings provide evidence for the overlapping circuitry between arousal and mood regulation in humans. Furthermore, our findings open the door to new treatment targets and the consideration of therapeutic neurostimulation for sleep-wake disorders.
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Affiliation(s)
- Joline M Fan
- Department of Neurology, University of California, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
| | - A Moses Lee
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Kristin K Sellers
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Kai Woodworth
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Ghassan S Makhoul
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Tony X Liu
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Catherine Henderson
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Daniela A Astudillo Maya
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Rebecca Martinez
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Hashem Zamanian
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Benjamin A Speidel
- Department of Neurology, University of California, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Ankit N Khambhati
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Vikram R Rao
- Department of Neurology, University of California, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Leo P Sugrue
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA
| | - Katherine W Scangos
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Edward F Chang
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
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6
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Sellers KK, Stapper N, Astudillo Maya DA, Henderson C, Khambhati AN, Fan JM, Rao VR, Scangos KW, Chang EF, Krystal AD. Changes in intracranial neurophysiology associated with acute COVID-19 infection. Clin Neurophysiol 2023; 148:29-31. [PMID: 36791656 PMCID: PMC9896881 DOI: 10.1016/j.clinph.2023.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 01/28/2023] [Indexed: 02/05/2023]
Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
| | - Noah Stapper
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Daniela A Astudillo Maya
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Catherine Henderson
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Joline M Fan
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Vikram R Rao
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Katherine W Scangos
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
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7
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Fan JM, Khambhati AN, Sellers KK, Stapper N, Maya DA, Kunwar E, Henderson C, Sugrue LP, Scangos KW, Chang EF, Rao VR, Krystal AD. Epileptiform discharges triggered with direct electrical stimulation for treatment-resistant depression: Factors that modulate risk and treatment considerations. Brain Stimul 2023; 16:462-465. [PMID: 36773780 PMCID: PMC10627048 DOI: 10.1016/j.brs.2023.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 02/05/2023] [Indexed: 02/11/2023] Open
Affiliation(s)
- Joline M Fan
- Department of Neurology, University of California, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
| | - Ankit N Khambhati
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Kristin K Sellers
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Noah Stapper
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | | | - Elysha Kunwar
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | | | - Leo P Sugrue
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Katherine W Scangos
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Edward F Chang
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Neurosurgery, University of California, San Francisco, CA, USA
| | - Vikram R Rao
- Department of Neurology, University of California, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA
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8
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Chung JE, Sellers KK, Leonard MK, Gwilliams L, Xu D, Dougherty ME, Kharazia V, Metzger SL, Welkenhuysen M, Dutta B, Chang EF. High-density single-unit human cortical recordings using the Neuropixels probe. Neuron 2022; 110:2409-2421.e3. [PMID: 35679860 DOI: 10.1016/j.neuron.2022.05.007] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 04/10/2022] [Accepted: 05/10/2022] [Indexed: 10/18/2022]
Abstract
The action potential is a fundamental unit of neural computation. Even though significant advances have been made in recording large numbers of individual neurons in animal models, translation of these methodologies to humans has been limited because of clinical constraints and electrode reliability. Here, we present a reliable method for intraoperative recording of dozens of neurons in humans using the Neuropixels probe, yielding up to ∼100 simultaneously recorded single units. Most single units were active within 1 min of reaching target depth. The motion of the electrode array had a strong inverse correlation with yield, identifying a major challenge and opportunity to further increase the probe utility. Cell pairs active close in time were spatially closer in most recordings, demonstrating the power to resolve complex cortical dynamics. Altogether, this approach provides access to population single-unit activity across the depth of human neocortex at scales previously only accessible in animal models.
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Affiliation(s)
- Jason E Chung
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Matthew K Leonard
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Laura Gwilliams
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Duo Xu
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Maximilian E Dougherty
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Viktor Kharazia
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Sean L Metzger
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA; University of California Berkeley, University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA 94720, USA
| | | | | | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA.
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9
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Prosky J, Cagle J, Sellers KK, Gilron R, de Hemptinne C, Schmitgen A, Starr PA, Chang EF, Shirvalkar P. Practical Closed-Loop Strategies for Deep Brain Stimulation: Lessons From Chronic Pain. Front Neurosci 2022; 15:762097. [PMID: 34975374 PMCID: PMC8716790 DOI: 10.3389/fnins.2021.762097] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 11/24/2021] [Indexed: 11/22/2022] Open
Abstract
Deep brain stimulation (DBS) is a plausible therapy for various neuropsychiatric disorders, though continuous tonic stimulation without regard to underlying physiology (open-loop) has had variable success. Recently available DBS devices can sense neural signals which, in turn, can be used to control stimulation in a closed-loop mode. Closed-loop DBS strategies may mitigate many drawbacks of open-loop stimulation and provide more personalized therapy. These devices contain many adjustable parameters that control how the closed-loop system operates, which need to be optimized using a combination of empirically and clinically informed decision making. We offer a practical guide for the implementation of a closed-loop DBS system, using examples from patients with chronic pain. Focusing on two research devices from Medtronic, the Activa PC+S and Summit RC+S, we provide pragmatic details on implementing closed- loop programming from a clinician’s perspective. Specifically, by combining our understanding of chronic pain with data-driven heuristics, we describe how to tune key parameters to handle feature selection, state thresholding, and stimulation artifacts. Finally, we discuss logistical and practical considerations that clinicians must be aware of when programming closed-loop devices.
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Affiliation(s)
- Jordan Prosky
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.,UCSF Weill Institute for Neurosciences, San Francisco, CA, United States
| | - Jackson Cagle
- Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.,UCSF Weill Institute for Neurosciences, San Francisco, CA, United States
| | - Ro'ee Gilron
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Cora de Hemptinne
- Department of Neurology, University of Florida, Gainesville, FL, United States.,Normal Fixel Institute for Neurological Diseases, Gainesville, FL, United States
| | - Ashlyn Schmitgen
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.,UCSF Weill Institute for Neurosciences, San Francisco, CA, United States
| | - Philip A Starr
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.,UCSF Weill Institute for Neurosciences, San Francisco, CA, United States.,UCSF Department of Physiology, San Francisco, CA, United States
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.,UCSF Weill Institute for Neurosciences, San Francisco, CA, United States.,UCSF Department of Physiology, San Francisco, CA, United States
| | - Prasad Shirvalkar
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.,UCSF Weill Institute for Neurosciences, San Francisco, CA, United States.,Division of Pain Medicine, UCSF Department of Anesthesiology and Perioperative Care, San Francisco, CA, United States.,UCSF Department of Neurology, San Francisco, CA, United States
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10
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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 DOI: 10.1038/s41591-021-01480-w] [Citation(s) in RCA: 147] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 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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11
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Sellers KK, Chung JE, Zhou J, Triplett MG, Dawes HE, Haque R, Chang EF. Thin-film microfabrication and intraoperative testing of µECoG and iEEG depth arrays for sense and stimulation. J Neural Eng 2021; 18:10.1088/1741-2552/ac1984. [PMID: 34330113 PMCID: PMC10495194 DOI: 10.1088/1741-2552/ac1984] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 07/30/2021] [Indexed: 11/11/2022]
Abstract
Objective.Intracranial neural recordings and electrical stimulation are tools used in an increasing range of applications, including intraoperative clinical mapping and monitoring, therapeutic neuromodulation, and brain computer interface control and feedback. However, many of these applications suffer from a lack of spatial specificity and localization, both in terms of sensed neural signal and applied stimulation. This stems from limited manufacturing processes of commercial-off-the-shelf (COTS) arrays unable to accommodate increased channel density, higher channel count, and smaller contact size.Approach.Here, we describe a manufacturing and assembly approach using thin-film microfabrication for 32-channel high density subdural micro-electrocorticography (µECoG) surface arrays (contacts 1.2 mm diameter, 2 mm pitch) and intracranial electroencephalography (iEEG) depth arrays (contacts 0.5 mm × 1.5 mm, pitch 0.8 mm × 2.5 mm). Crucially, we tackle the translational hurdle and test these arrays during intraoperative studies conducted in four humans under regulatory approval.Main results.We demonstrate that the higher-density contacts provide additional unique information across the recording span compared to the density of COTS arrays which typically have electrode pitch of 8 mm or greater; 4 mm in case of specially ordered arrays. Our intracranial stimulation study results reveal that refined spatial targeting of stimulation elicits evoked potentials with differing spatial spread.Significance.Thin-film,μECoG and iEEG depth arrays offer a promising substrate for advancing a number of clinical and research applications reliant on high-resolution neural sensing and intracranial stimulation.
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Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States of America
- These authors contributed equally
| | - Jason E Chung
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States of America
- These authors contributed equally
| | - Jenny Zhou
- Lawrence Livermore National Laboratories, Livermore, CA, United States of America
| | - Michael G Triplett
- Lawrence Livermore National Laboratories, Livermore, CA, United States of America
| | - Heather E Dawes
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States of America
| | - Razi Haque
- Lawrence Livermore National Laboratories, Livermore, CA, United States of America
| | - Edward F Chang
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States of America
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12
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Sellers KK, Gilron R, Anso J, Louie KH, Shirvalkar PR, Chang EF, Little SJ, Starr PA. Analysis-rcs-data: Open-Source Toolbox for the Ingestion, Time-Alignment, and Visualization of Sense and Stimulation Data From the Medtronic Summit RC+S System. Front Hum Neurosci 2021; 15:714256. [PMID: 34322004 PMCID: PMC8312257 DOI: 10.3389/fnhum.2021.714256] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 06/22/2021] [Indexed: 12/15/2022] Open
Abstract
Closed-loop neurostimulation is a promising therapy being tested and clinically implemented in a growing number of neurological and psychiatric indications. This therapy is enabled by chronically implanted, bidirectional devices including the Medtronic Summit RC+S system. In order to successfully optimize therapy for patients implanted with these devices, analyses must be conducted offline on the recorded neural data, in order to inform optimal sense and stimulation parameters. The file format, volume, and complexity of raw data from these devices necessitate conversion, parsing, and time reconstruction ahead of time-frequency analyses and modeling common to standard neuroscientific analyses. Here, we provide an open-source toolbox written in Matlab which takes raw files from the Summit RC+S and transforms these data into a standardized format amenable to conventional analyses. Furthermore, we provide a plotting tool which can aid in the visualization of multiple data streams and sense, stimulation, and therapy settings. Finally, we describe an analysis module which replicates RC+S on-board power computations, a functionality which can accelerate biomarker discovery. This toolbox aims to accelerate the research and clinical advances made possible by longitudinal neural recordings and adaptive neurostimulation in people with neurological and psychiatric illnesses.
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Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Ro'ee Gilron
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Juan Anso
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Kenneth H Louie
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Prasad R Shirvalkar
- Department of Anesthesiology (Pain Management), Neurology, and Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Simon J Little
- Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Philip A Starr
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
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13
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Crawford ED, Acosta I, Ahyong V, Anderson EC, Arevalo S, Asarnow D, Axelrod S, Ayscue P, Azimi CS, Azumaya CM, Bachl S, Bachmutsky I, Bhaduri A, Brown JB, Batson J, Behnert A, Boileau RM, Bollam SR, Bonny AR, Booth D, Borja MJB, Brown D, Buie B, Burnett CE, Byrnes LE, Cabral KA, Cabrera JP, Caldera S, Canales G, Castañeda GR, Chan AP, Chang CR, Charles-Orszag A, Cheung C, Chio U, Chow ED, Citron YR, Cohen A, Cohn LB, Chiu C, Cole MA, Conrad DN, Constantino A, Cote A, Crayton-Hall T, Darmanis S, Detweiler AM, Dial RL, Dong S, Duarte EM, Dynerman D, Egger R, Fanton A, Frumm SM, Fu BXH, Garcia VE, Garcia J, Gladkova C, Goldman M, Gomez-Sjoberg R, Gordon MG, Grove JCR, Gupta S, Haddjeri-Hopkins A, Hadley P, Haliburton J, Hao SL, Hartoularos G, Herrera N, Hilberg M, Ho KYE, Hoppe N, Hosseinzadeh S, Howard CJ, Hussmann JA, Hwang E, Ingebrigtsen D, Jackson JR, Jowhar ZM, Kain D, Kim JYS, Kistler A, Kreutzfeld O, Kulsuptrakul J, Kung AF, Langelier C, Laurie MT, Lee L, Leng K, Leon KE, Leonetti MD, Levan SR, Li S, Li AW, Liu J, Lubin HS, Lyden A, Mann J, Mann S, Margulis G, Marquez DM, Marsh BP, Martyn C, McCarthy EE, McGeever A, Merriman AF, Meyer LK, Miller S, Moore MK, Mowery CT, Mukhtar T, Mwakibete LL, Narez N, Neff NF, Osso LA, Oviedo D, Peng S, Phelps M, Phong K, Picard P, Pieper LM, Pincha N, Pisco AO, Pogson A, Pourmal S, Puccinelli RR, Puschnik AS, Rackaityte E, Raghavan P, Raghavan M, Reese J, Replogle JM, Retallack H, Reyes H, Rose D, Rosenberg MF, Sanchez-Guerrero E, Sattler SM, Savy L, See SK, Sellers KK, Serpa PH, Sheehy M, Sheu J, Silas S, Streithorst JA, Strickland J, Stryke D, Sunshine S, Suslow P, Sutanto R, Tamura S, Tan M, Tan J, Tang A, Tato CM, Taylor JC, Tenvooren I, Thompson EM, Thornborrow EC, Tse E, Tung T, Turner ML, Turner VS, Turnham RE, Turocy MJ, Vaidyanathan TV, Vainchtein ID, Vanaerschot M, Vazquez SE, Wandler AM, Wapniarski A, Webber JT, Weinberg ZY, Westbrook A, Wong AW, Wong E, Worthington G, Xie F, Xu A, Yamamoto T, Yang Y, Yarza F, Zaltsman Y, Zheng T, DeRisi JL. Rapid deployment of SARS-CoV-2 testing: The CLIAHUB. PLoS Pathog 2020; 16:e1008966. [PMID: 33112933 PMCID: PMC7592773 DOI: 10.1371/journal.ppat.1008966] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Emily D. Crawford
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
- University of California San Francisco, Department of Microbiology and Immunology, San Francisco, California, United States of America
| | - Irene Acosta
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Vida Ahyong
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Erika C. Anderson
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Shaun Arevalo
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Daniel Asarnow
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Shannon Axelrod
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Patrick Ayscue
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Camillia S. Azimi
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Caleigh M. Azumaya
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Stefanie Bachl
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Iris Bachmutsky
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Aparna Bhaduri
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Jeremy Bancroft Brown
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Joshua Batson
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Astrid Behnert
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Ryan M. Boileau
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Saumya R. Bollam
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Alain R. Bonny
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - David Booth
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | | | - David Brown
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Bryan Buie
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Cassandra E. Burnett
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Lauren E. Byrnes
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Katelyn A. Cabral
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
- University of California San Francisco, Institute for Neurodegenerative Diseases, San Francisco, California, United States of America
| | - Joana P. Cabrera
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Saharai Caldera
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
- University of California San Francisco, Division of Infectious Disease, San Francisco, California, United States of America
| | - Gabriela Canales
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | | | - Agnes Protacio Chan
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Christopher R. Chang
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Arthur Charles-Orszag
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
- Howard Hughes Medical Institute, Chevy Chase, Maryland, United States of America
| | - Carly Cheung
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Unseng Chio
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Eric D. Chow
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - Y. Rose Citron
- University of California, Berkeley, California, United States of America
| | - Allison Cohen
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Lillian B. Cohn
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
- University of California San Francisco, Department of Experimental Medicine, San Francisco, California, United States of America
| | - Charles Chiu
- University of California San Francisco, Department of Laboratory Medicine, San Francisco, California, United States of America
| | - Mitchel A. Cole
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Daniel N. Conrad
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Angela Constantino
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Andrew Cote
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | | | - Spyros Darmanis
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | | | - Rebekah L. Dial
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - Shen Dong
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Elias M. Duarte
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - David Dynerman
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Rebecca Egger
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Alison Fanton
- University of California, Berkeley, California, United States of America
| | - Stacey M. Frumm
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Becky Xu Hua Fu
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Valentina E. Garcia
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - Julie Garcia
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Christina Gladkova
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
- Howard Hughes Medical Institute, Chevy Chase, Maryland, United States of America
| | - Miriam Goldman
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | | | - M. Grace Gordon
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - James C. R. Grove
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Shweta Gupta
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Alexis Haddjeri-Hopkins
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Pierce Hadley
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
- University of California San Francisco, Institute for Neurodegenerative Diseases, San Francisco, California, United States of America
| | - John Haliburton
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Samantha L. Hao
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - George Hartoularos
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Nadia Herrera
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Melissa Hilberg
- University of California San Francisco, Department of Laboratory Medicine, San Francisco, California, United States of America
| | - Kit Ying E. Ho
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Nicholas Hoppe
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | | | - Conor J. Howard
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Jeffrey A. Hussmann
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Elizabeth Hwang
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Danielle Ingebrigtsen
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Julia R. Jackson
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Ziad M. Jowhar
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Danielle Kain
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - James Y. S. Kim
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Amy Kistler
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Oriana Kreutzfeld
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | | | - Andrew F. Kung
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Charles Langelier
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
- University of California San Francisco, Division of Infectious Disease, San Francisco, California, United States of America
| | - Matthew T. Laurie
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - Lena Lee
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Kun Leng
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Kristoffer E. Leon
- Gladstone Institute, San Francisco, California, United States of America
| | - Manuel D. Leonetti
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Sophia R. Levan
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Sam Li
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - Aileen W. Li
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Jamin Liu
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - Heidi S. Lubin
- eSix Development, Oakland, California, United States of America
| | - Amy Lyden
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Jennifer Mann
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Sabrina Mann
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Gorica Margulis
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Diana M. Marquez
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Bryan P. Marsh
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Calla Martyn
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Elizabeth E. McCarthy
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Aaron McGeever
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | | | - Lauren K. Meyer
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Steve Miller
- University of California San Francisco, Department of Laboratory Medicine, San Francisco, California, United States of America
| | - Megan K. Moore
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Cody T. Mowery
- Gladstone Institute, San Francisco, California, United States of America
| | - Tanzila Mukhtar
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | | | - Noelle Narez
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Norma F. Neff
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Lindsay A. Osso
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Diter Oviedo
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Suping Peng
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Maira Phelps
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Kiet Phong
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Peter Picard
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Lindsey M. Pieper
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Neha Pincha
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | | | - Angela Pogson
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Sergei Pourmal
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | | | | | - Elze Rackaityte
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - Preethi Raghavan
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Madhura Raghavan
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - James Reese
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Joseph M. Replogle
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Hanna Retallack
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - Helen Reyes
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Donald Rose
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Marci F. Rosenberg
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | | | - Sydney M. Sattler
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Laura Savy
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Stephanie K. See
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Kristin K. Sellers
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Paula Hayakawa Serpa
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
- University of California San Francisco, Division of Infectious Disease, San Francisco, California, United States of America
| | - Maureen Sheehy
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Jonathan Sheu
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Sukrit Silas
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Jessica A. Streithorst
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Jack Strickland
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Doug Stryke
- University of California San Francisco, Department of Laboratory Medicine, San Francisco, California, United States of America
| | - Sara Sunshine
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - Peter Suslow
- University of California San Francisco, Department of Laboratory Medicine, San Francisco, California, United States of America
| | - Renaldo Sutanto
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Serena Tamura
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Michelle Tan
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Jiongyi Tan
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Alice Tang
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Cristina M. Tato
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Jack C. Taylor
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Iliana Tenvooren
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Erin M. Thompson
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Edward C. Thornborrow
- University of California San Francisco, Department of Laboratory Medicine, San Francisco, California, United States of America
| | - Eric Tse
- Joint Bioengineering Graduate Program, University of California, Berkeley, California, United States of America
| | - Tony Tung
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Marc L. Turner
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Victoria S. Turner
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Rigney E. Turnham
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Mary J. Turocy
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Trisha V. Vaidyanathan
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Ilia D. Vainchtein
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Manu Vanaerschot
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Sara E. Vazquez
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
| | - Anica M. Wandler
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Anne Wapniarski
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - James T. Webber
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Zara Y. Weinberg
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Alexandra Westbrook
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Allison W. Wong
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Emily Wong
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Gajus Worthington
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | - Fang Xie
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Albert Xu
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Terrina Yamamoto
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Ying Yang
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Fauna Yarza
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Yefim Zaltsman
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Tina Zheng
- University of California San Francisco, School of Medicine, San Francisco, California, United States of America
| | - Joseph L. DeRisi
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
- University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America
- * E-mail:
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14
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Shirvalkar P, Sellers KK, Schmitgen A, Prosky J, Joseph I, Starr PA, Chang EF. A Deep Brain Stimulation Trial Period for Treating Chronic Pain. J Clin Med 2020; 9:jcm9103155. [PMID: 33003443 PMCID: PMC7600449 DOI: 10.3390/jcm9103155] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 09/22/2020] [Accepted: 09/25/2020] [Indexed: 12/17/2022] Open
Abstract
Early studies of deep brain stimulation (DBS) for various neurological disorders involved a temporary trial period where implanted electrodes were externalized, in which the electrical contacts exiting the patient's brain are connected to external stimulation equipment, so that stimulation efficacy could be determined before permanent implant. As the optimal brain target sites for various diseases (i.e., Parkinson's disease, essential tremor) became better established, such trial periods have fallen out of favor. However, deep brain stimulation trial periods are experiencing a modern resurgence for at least two reasons: (1) studies of newer indications such as depression or chronic pain aim to identify new targets and (2) a growing interest in adaptive DBS tools necessitates neurophysiological recordings, which are often done in the peri-surgical period. In this review, we consider the possible approaches, benefits, and risks of such inpatient trial periods with a specific focus on developing new DBS therapies for chronic pain.
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Affiliation(s)
- Prasad Shirvalkar
- Department of Anesthesiology (Pain Management), University of California San Francisco, San Francisco, CA 94143, USA;
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (K.K.S.); (A.S.); (I.J.); (P.A.S.); (E.F.C.)
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
- Correspondence:
| | - Kristin K. Sellers
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (K.K.S.); (A.S.); (I.J.); (P.A.S.); (E.F.C.)
| | - Ashlyn Schmitgen
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (K.K.S.); (A.S.); (I.J.); (P.A.S.); (E.F.C.)
| | - Jordan Prosky
- Department of Anesthesiology (Pain Management), University of California San Francisco, San Francisco, CA 94143, USA;
| | - Isabella Joseph
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (K.K.S.); (A.S.); (I.J.); (P.A.S.); (E.F.C.)
| | - Philip A. Starr
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (K.K.S.); (A.S.); (I.J.); (P.A.S.); (E.F.C.)
| | - Edward F. Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (K.K.S.); (A.S.); (I.J.); (P.A.S.); (E.F.C.)
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15
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Scangos KW, Ahmad HS, Shafi A, Sellers KK, Dawes HE, Krystal A, Chang EF. Pilot Study of An Intracranial Electroencephalography Biomarker of Depressive Symptoms in Epilepsy. J Neuropsychiatry Clin Neurosci 2020; 32:185-190. [PMID: 31394989 PMCID: PMC7429560 DOI: 10.1176/appi.neuropsych.19030081] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVES Adult patients with epilepsy have an increased prevalence of major depressive disorder (MDD). Intracranial EEG (iEEG) captured during extended inpatient monitoring of patients with treatment-resistant epilepsy offers a particularly promising method to study MDD networks in epilepsy. METHODS The authors used 24 hours of resting-state iEEG to examine the neural activity patterns within corticolimbic structures that reflected the presence of depressive symptoms in 13 adults with medication-refractory epilepsy. Principal component analysis was performed on the z-scored mean relative power in five standard frequency bands averaged across electrodes within a region. RESULTS Principal component 3 was a statistically significant predictor of the presence of depressive symptoms (R2=0.35, p=0.014). A balanced logistic classifier model using principal component 3 alone correctly classified 78% of patients as belonging to the group with a high burden of depressive symptoms or a control group with minimal depressive symptoms (sensitivity, 75%; specificity, 80%; area under the curve=0.8, leave-one-out cross validation). Classification was dependent on beta power throughout the corticolimbic network and low-frequency cingulate power. CONCLUSIONS These finding suggest, for the first time, that neural features across circuits involved in epilepsy may distinguish patients who have depressive symptoms from those who do not. Larger studies are required to validate these findings and to assess their diagnostic utility in MDD.
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16
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Rao VR, Sellers KK, Wallace DL, Lee MB, Bijanzadeh M, Sani OG, Yang Y, Shanechi MM, Dawes HE, Chang EF. Direct Electrical Stimulation of Lateral Orbitofrontal Cortex Acutely Improves Mood in Individuals with Symptoms of Depression. Curr Biol 2018; 28:3893-3902.e4. [DOI: 10.1016/j.cub.2018.10.026] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Revised: 09/16/2018] [Accepted: 10/10/2018] [Indexed: 11/30/2022]
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17
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Li Y, Yu C, Zhou ZC, Stitt I, Sellers KK, Gilmore JH, Frohlich F. Early Development of Network Oscillations in the Ferret Visual Cortex. Sci Rep 2017; 7:17766. [PMID: 29259184 PMCID: PMC5736753 DOI: 10.1038/s41598-017-17502-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 11/27/2017] [Indexed: 01/25/2023] Open
Abstract
Although oscillations during development have been characterized in a wide range of neural systems, little is known about the interaction between these network oscillations and neuronal spiking, and the interactions among different oscillation frequencies. Here we recorded the spontaneous and visual-elicited local field potential (LFP) and multi-unit activity (MUA) in the visual cortex of freely-moving juvenile ferrets before and after eye-opening. We found that both the spontaneous and visually-elicited LFP power was increased after eye-opening, especially in higher frequency bands (>30 Hz). Spike LFP phase coupling was decreased for lower frequency bands (theta and alpha) but slightly increased for higher frequencies (high-gamma band). A similar shift towards faster frequencies also occurred for phase-amplitude coupling; with maturation, the coupling of the theta/alpha/beta band amplitude to the delta phase was decreased and the high-gamma amplitude coupling to theta/alpha phase was increased. This shift towards higher frequencies was also reflected in the visual responses; the LFP oscillation became more entrained by visual stimulation with higher frequencies (>10 Hz). Taken together, these results suggest gamma oscillation as a signature of the maturation of cortical circuitry.
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Affiliation(s)
- Yuhui Li
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Chunxiu Yu
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Zhe Charles Zhou
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.,Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Iain Stitt
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kristin K Sellers
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.,Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Flavio Frohlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. .,Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. .,Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. .,Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. .,Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. .,Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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18
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Sellers KK, Yu C, Zhou ZC, Stitt I, Li Y, Radtke-Schuller S, Alagapan S, Fröhlich F. Oscillatory Dynamics in the Frontoparietal Attention Network during Sustained Attention in the Ferret. Cell Rep 2017; 16:2864-2874. [PMID: 27626658 DOI: 10.1016/j.celrep.2016.08.055] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2016] [Revised: 07/15/2016] [Accepted: 08/17/2016] [Indexed: 01/08/2023] Open
Abstract
Sustained attention requires the coordination of neural activity across multiple cortical areas in the frontoparietal network, in particular the prefrontal cortex (PFC) and posterior parietal cortex (PPC). Previous work has demonstrated that activity in these brain regions is coordinated by neuronal oscillations of the local field potential (LFP). However, the underlying coordination of activity in terms of organization of single unit (SU) spiking activity has remained poorly understood, particularly in the freely moving animal. We found that long-range functional connectivity between anatomically connected PFC and PPC was mediated by oscillations in the theta frequency band. SU activity in PFC was phase locked to theta oscillations in PPC, and spiking activity in PFC and PPC was locked to local high-gamma activity. Together, our results support a model in which frequency-specific synchronization mediates functional connectivity between and within PFC and PPC of the frontoparietal attention network in the freely moving animal.
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Affiliation(s)
- Kristin K Sellers
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Chunxiu Yu
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhe Charles Zhou
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Iain Stitt
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yuhui Li
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Susanne Radtke-Schuller
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Sankaraleengam Alagapan
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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19
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Wollstadt P, Sellers KK, Rudelt L, Priesemann V, Hutt A, Fröhlich F, Wibral M. Breakdown of local information processing may underlie isoflurane anesthesia effects. PLoS Comput Biol 2017; 13:e1005511. [PMID: 28570661 PMCID: PMC5453425 DOI: 10.1371/journal.pcbi.1005511] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 04/11/2017] [Indexed: 02/07/2023] Open
Abstract
The disruption of coupling between brain areas has been suggested as the mechanism underlying loss of consciousness in anesthesia. This hypothesis has been tested previously by measuring the information transfer between brain areas, and by taking reduced information transfer as a proxy for decoupling. Yet, information transfer is a function of the amount of information available in the information source—such that transfer decreases even for unchanged coupling when less source information is available. Therefore, we reconsidered past interpretations of reduced information transfer as a sign of decoupling, and asked whether impaired local information processing leads to a loss of information transfer. An important prediction of this alternative hypothesis is that changes in locally available information (signal entropy) should be at least as pronounced as changes in information transfer. We tested this prediction by recording local field potentials in two ferrets after administration of isoflurane in concentrations of 0.0%, 0.5%, and 1.0%. We found strong decreases in the source entropy under isoflurane in area V1 and the prefrontal cortex (PFC)—as predicted by our alternative hypothesis. The decrease in source entropy was stronger in PFC compared to V1. Information transfer between V1 and PFC was reduced bidirectionally, but with a stronger decrease from PFC to V1. This links the stronger decrease in information transfer to the stronger decrease in source entropy—suggesting reduced source entropy reduces information transfer. This conclusion fits the observation that the synaptic targets of isoflurane are located in local cortical circuits rather than on the synapses formed by interareal axonal projections. Thus, changes in information transfer under isoflurane seem to be a consequence of changes in local processing more than of decoupling between brain areas. We suggest that source entropy changes must be considered whenever interpreting changes in information transfer as decoupling. Currently we do not understand how anesthesia leads to loss of consciousness (LOC). One popular idea is that we loose consciousness when brain areas lose their ability to communicate with each other–as anesthetics might interrupt transmission on nerve fibers coupling them. This idea has been tested by measuring the amount of information transferred between brain areas, and taking this transfer to reflect the coupling itself. Yet, information that isn’t available in the source area can’t be transferred to a target. Hence, the decreases in information transfer could be related to less information being available in the source, rather than to a decoupling. We tested this possibility measuring the information available in source brain areas and found that it decreased under isoflurane anesthesia. In addition, a stronger decrease in source information lead to a stronger decrease of the information transfered. Thus, the input to the connection between brain areas determined the communicated information, not the strength of the coupling (which would result in a stronger decrease in the target). We suggest that interrupted information processing within brain areas has an important contribution to LOC, and should be focused on more in attempts to understand loss of consciousness under anesthesia.
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Affiliation(s)
- Patricia Wollstadt
- MEG Unit, Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
- * E-mail: (PW); (VP)
| | - Kristin K. Sellers
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Lucas Rudelt
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
| | - Viola Priesemann
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Bernstein Center for Computational Neuroscience, BCCN, Göttingen, Germany
- * E-mail: (PW); (VP)
| | - Axel Hutt
- Deutscher Wetterdienst, Section FE 12 - Data Assimilation, Offenbach/Main, Germany
- Department of Mathematics and Statistics, University of Reading, Reading, United Kingdom
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michael Wibral
- MEG Unit, Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
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20
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Wollstadt P, Sellers KK, Hutt A, Frohlich F, Wibral M. Anesthesia-related changes in information transfer may be caused by reduction in local information generation. Annu Int Conf IEEE Eng Med Biol Soc 2016; 2015:4045-8. [PMID: 26737182 DOI: 10.1109/embc.2015.7319282] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
In anesthesia research it is an open question how general anesthetics lead to loss of consciousness (LOC). It has been proposed that LOC may be caused by the disruption of cortical information processing, preventing information integration. Therefore, recent studies investigating information processing under anesthesia focused on changes in information transfer, measured by transfer entropy (TE). However, often this complex technique was not applied rigorously, using time series in symbolic representation, or using TE differences without accounting for neural conduction delays, or without accounting for signal history. Here, we used current best-practice in TE estimation to investigate information transfer under anesthesia: We conducted simultaneous recordings in primary visual cortex (V1) and prefrontal cortex (PFC) of head-fixed ferrets in a dark environment under different levels of anesthesia (awake, 0.5% isoflurane, 1.0 % isoflurane). To elucidate reasons for changes in TE, we further quantified information processing within brain areas by estimating active information storage (AIS) as an estimator of predictable information, and Lempel-Ziv complexity (LZC) as an estimator of signal entropy. Under anesthesia, we found a reduction in information transfer (TE) between PFC and V1 with a stronger reduction for the feedback direction (PFC to V1), validating previous results. Furthermore, entropy (LZC) was reduced and activity became more predictable as indicated by higher values of AIS. We conclude that higher anesthesia concentrations indeed lead to reduced inter-areal information transfer, which may be partly caused by decreases in local entropy and increases in local predictability. In revealing a possible reason for reduced TE that is potentially independent of inter-areal coupling, we demonstrate the value of directly quantifying information processing in addition to focusing on dynamic properties such as coupling strength.
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21
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Zhou ZC, Salzwedel AP, Radtke-Schuller S, Li Y, Sellers KK, Gilmore JH, Shih YYI, Fröhlich F, Gao W. Resting state network topology of the ferret brain. Neuroimage 2016; 143:70-81. [PMID: 27596024 DOI: 10.1016/j.neuroimage.2016.09.003] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2016] [Revised: 08/17/2016] [Accepted: 09/01/2016] [Indexed: 12/22/2022] Open
Abstract
Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4T MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function.
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Affiliation(s)
- Zhe Charles Zhou
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Andrew P Salzwedel
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Susanne Radtke-Schuller
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Yuhui Li
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Kristin K Sellers
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Yen-Yu Ian Shih
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Small Animal Imaging Facility, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Wei Gao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.
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Tošić T, Sellers KK, Fröhlich F, Fedotenkova M, Beim Graben P, Hutt A. Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots. Front Syst Neurosci 2016; 9:184. [PMID: 26834580 PMCID: PMC4712310 DOI: 10.3389/fnsys.2015.00184] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 12/18/2015] [Indexed: 01/27/2023] Open
Abstract
For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain.
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Affiliation(s)
- Tamara Tošić
- Team Neurosys, InriaVillers-lès-Nancy, France; Loria, Centre National de la Recherche Scientifique, UMR no 7503Villers-lès-Nancy, France; Université de Lorraine, Loria, UMR no 7503Villers-lès-Nancy, France
| | - Kristin K Sellers
- Department of Psychiatry, University of North Carolina at Chapel HillChapel Hill, NC, USA; Neurobiology Curriculum, University of North Carolina at Chapel HillChapel Hill, NC, USA
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel HillChapel Hill, NC, USA; Neurobiology Curriculum, University of North Carolina at Chapel HillChapel Hill, NC, USA; Department of Cell Biology and Physiology, University of North Carolina at Chapel HillChapel Hill, NC, USA; Department of Biomedical Engineering, University of North Carolina at Chapel HillChapel Hill, NC, USA; Neuroscience Center, University of North Carolina at Chapel HillChapel Hill, NC, USA
| | - Mariia Fedotenkova
- Team Neurosys, InriaVillers-lès-Nancy, France; Loria, Centre National de la Recherche Scientifique, UMR no 7503Villers-lès-Nancy, France; Université de Lorraine, Loria, UMR no 7503Villers-lès-Nancy, France
| | - Peter Beim Graben
- Department of German Studies and LinguisticsBerlin, Germany; Bernstein Center for Computational NeuroscienceBerlin, Germany
| | - Axel Hutt
- Team Neurosys, InriaVillers-lès-Nancy, France; Loria, Centre National de la Recherche Scientifique, UMR no 7503Villers-lès-Nancy, France; Université de Lorraine, Loria, UMR no 7503Villers-lès-Nancy, France
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23
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Yu C, Sellers KK, Radtke-Schuller S, Lu J, Xing L, Ghukasyan V, Li Y, Shih YYI, Murrow R, Fröhlich F. Structural and functional connectivity between the lateral posterior-pulvinar complex and primary visual cortex in the ferret. Eur J Neurosci 2016; 43:230-44. [PMID: 26505737 DOI: 10.1111/ejn.13116] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2015] [Revised: 10/15/2015] [Accepted: 10/22/2015] [Indexed: 02/01/2023]
Abstract
The role of higher-order thalamic structures in sensory processing remains poorly understood. Here, we used the ferret (Mustela putorius furo) as a novel model species for the study of the lateral posterior (LP)-pulvinar complex and its structural and functional connectivity with area 17 [primary visual cortex (V1)]. We found reciprocal anatomical connections between the lateral part of the LP nucleus of the LP-pulvinar complex (LPl) and V1. In order to investigate the role of this feedback loop between LPl and V1 in shaping network activity, we determined the functional interactions between LPl and the supragranular, granular and infragranular layers of V1 by recording multiunit activity and local field potentials. Coherence was strongest between LPl and the supragranular V1, with the most distinct peaks in the delta and alpha frequency bands. Inter-area interaction measured by spike-phase coupling identified the delta frequency band being dominated by the infragranular V1 and multiple frequency bands that were most pronounced in the supragranular V1. This inter-area coupling was differentially modulated by full-field synthetic and naturalistic visual stimulation. We also found that visual responses in LPl were distinct from those in V1 in terms of their reliability. Together, our data support a model of multiple communication channels between LPl and the layers of V1 that are enabled by oscillations in different frequency bands. This demonstration of anatomical and functional connectivity between LPl and V1 in ferrets provides a roadmap for studying the interaction dynamics during behaviour, and a template for identifying the activity dynamics of other thalamo-cortical feedback loops.
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Affiliation(s)
- Chunxiu Yu
- Department of Psychiatry, University of North Carolina at Chapel Hill, 115 Mason Farm Road, NRB 4109F, Chapel Hill, NC, 27599, USA
| | - Kristin K Sellers
- Department of Psychiatry, University of North Carolina at Chapel Hill, 115 Mason Farm Road, NRB 4109F, Chapel Hill, NC, 27599, USA.,Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Susanne Radtke-Schuller
- Department of Psychiatry, University of North Carolina at Chapel Hill, 115 Mason Farm Road, NRB 4109F, Chapel Hill, NC, 27599, USA
| | - Jinghao Lu
- Department of Psychiatry, University of North Carolina at Chapel Hill, 115 Mason Farm Road, NRB 4109F, Chapel Hill, NC, 27599, USA
| | - Lei Xing
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Vladimir Ghukasyan
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yuhui Li
- Department of Psychiatry, University of North Carolina at Chapel Hill, 115 Mason Farm Road, NRB 4109F, Chapel Hill, NC, 27599, USA
| | - Yen-Yu I Shih
- Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Richard Murrow
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Neurosurgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, 115 Mason Farm Road, NRB 4109F, Chapel Hill, NC, 27599, USA.,Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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24
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Tošić T, Graben PB, Sellers KK, Fröhlich F, Hutt A. Dynamics analysis of neural univariate time series by recurrence plots. BMC Neurosci 2015. [PMCID: PMC4697542 DOI: 10.1186/1471-2202-16-s1-p105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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25
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Sellers KK, Mellin JM, Lustenberger CM, Boyle MR, Lee WH, Peterchev AV, Fröhlich F. Transcranial direct current stimulation (tDCS) of frontal cortex decreases performance on the WAIS-IV intelligence test. Behav Brain Res 2015; 290:32-44. [PMID: 25934490 DOI: 10.1016/j.bbr.2015.04.031] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2014] [Revised: 04/14/2015] [Accepted: 04/19/2015] [Indexed: 01/23/2023]
Abstract
Transcranial direct current stimulation (tDCS) modulates excitability of motor cortex. However, there is conflicting evidence about the efficacy of this non-invasive brain stimulation modality to modulate performance on cognitive tasks. Previous work has tested the effect of tDCS on specific facets of cognition and executive processing. However, no randomized, double-blind, sham-controlled study has looked at the effects of tDCS on a comprehensive battery of cognitive processes. The objective of this study was to test if tDCS had an effect on performance on a comprehensive assay of cognitive processes, a standardized intelligence quotient (IQ) test. The study consisted of two substudies and followed a double-blind, between-subjects, sham-controlled design. In total, 41 healthy adult participants were included in the final analysis. These participants completed the Wechsler Adult Intelligence Scale, Fourth Edition (WAIS-IV) as a baseline measure. At least one week later, participants in substudy 1 received either bilateral tDCS (anodes over both F4 and F3, cathode over Cz, 2 mA at each anode for 20 min) or active sham tDCS (2 mA for 40 s), and participants in substudy 2 received either right or left tDCS (anode over either F4 or F3, cathode over Cz, 2 mA for 20 min). In both studies, the WAIS-IV was immediately administered following stimulation to assess for performance differences induced by bilateral and unilateral tDCS. Compared to sham stimulation, right, left, and bilateral tDCS reduced improvement between sessions on Full Scale IQ and the Perceptual Reasoning Index. This demonstration that frontal tDCS selectively degraded improvement on specific metrics of the WAIS-IV raises important questions about the often proposed role of tDCS in cognitive enhancement.
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Affiliation(s)
- Kristin K Sellers
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill NC 27599; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill NC 27599
| | - Juliann M Mellin
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill NC 27599
| | | | - Michael R Boyle
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill NC 27599; Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill NC 27599
| | - Won Hee Lee
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York NY 10029
| | - Angel V Peterchev
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham NC 27710; Department of Biomedical Engineering, Duke University, Durham NC 27710; Department of Electrical and Computer Engineering, Duke University, Durham NC 27710
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill NC 27599; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill NC 27599; Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill NC 27599; Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill NC 27599; Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill NC 27599; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill NC 27599.
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26
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Sellers KK, Bennett DV, Hutt A, Williams JH, Fröhlich F. Awake vs. anesthetized: layer-specific sensory processing in visual cortex and functional connectivity between cortical areas. J Neurophysiol 2015; 113:3798-815. [PMID: 25833839 DOI: 10.1152/jn.00923.2014] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Accepted: 03/30/2015] [Indexed: 01/03/2023] Open
Abstract
During general anesthesia, global brain activity and behavioral state are profoundly altered. Yet it remains mostly unknown how anesthetics alter sensory processing across cortical layers and modulate functional cortico-cortical connectivity. To address this gap in knowledge of the micro- and mesoscale effects of anesthetics on sensory processing in the cortical microcircuit, we recorded multiunit activity and local field potential in awake and anesthetized ferrets (Mustela putoris furo) during sensory stimulation. To understand how anesthetics alter sensory processing in a primary sensory area and the representation of sensory input in higher-order association areas, we studied the local sensory responses and long-range functional connectivity of primary visual cortex (V1) and prefrontal cortex (PFC). Isoflurane combined with xylazine provided general anesthesia for all anesthetized recordings. We found that anesthetics altered the duration of sensory-evoked responses, disrupted the response dynamics across cortical layers, suppressed both multimodal interactions in V1 and sensory responses in PFC, and reduced functional cortico-cortical connectivity between V1 and PFC. Together, the present findings demonstrate altered sensory responses and impaired functional network connectivity during anesthesia at the level of multiunit activity and local field potential across cortical layers.
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Affiliation(s)
- Kristin K Sellers
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Davis V Bennett
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Axel Hutt
- INRIA CR Nancy-Grand Est, Team Neurosys, Villers-les-Nancy, France
| | - James H Williams
- Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; and Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
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27
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Abstract
Cognitive impairment represents one of the most debilitating and most difficult symptom to treat of many psychiatric illnesses. Human neurophysiology studies have suggested that specific pathologies of cortical network activity correlate with cognitive impairment. However, we lack demonstration of causal relationships between specific network activity patterns and cognitive capabilities and treatment modalities that directly target impaired network dynamics of cognition. Transcranial alternating current stimulation (tACS), a novel non-invasive brain stimulation approach, may provide a crucial tool to tackle these challenges. Here, we propose that tACS can be used to elucidate the causal role of cortical synchronization in cognition and, eventually, to enhance pathologically weakened synchrony that may underlie cognitive deficits. To accelerate such development of tACS as a treatment for cognitive deficits, we discuss studies on tACS and cognition performed in healthy participants, according to the Research Domain Criteria of the National Institute of Mental Health.
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Affiliation(s)
- Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill NC 27599, USA
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28
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Sellers KK, Bennett DV, Fröhlich F. Frequency-band signatures of visual responses to naturalistic input in ferret primary visual cortex during free viewing. Brain Res 2014; 1598:31-45. [PMID: 25498982 DOI: 10.1016/j.brainres.2014.12.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2014] [Revised: 10/30/2014] [Accepted: 12/06/2014] [Indexed: 01/09/2023]
Abstract
Neuronal firing responses in visual cortex reflect the statistics of visual input and emerge from the interaction with endogenous network dynamics. Artificial visual stimuli presented to animals in which the network dynamics were constrained by anesthetic agents or trained behavioral tasks have provided fundamental understanding of how individual neurons in primary visual cortex respond to input. In contrast, very little is known about the mesoscale network dynamics and their relationship to microscopic spiking activity in the awake animal during free viewing of naturalistic visual input. To address this gap in knowledge, we recorded local field potential (LFP) and multiunit activity (MUA) simultaneously in all layers of primary visual cortex (V1) of awake, freely viewing ferrets presented with naturalistic visual input (nature movie clips). We found that naturalistic visual stimuli modulated the entire oscillation spectrum; low frequency oscillations were mostly suppressed whereas higher frequency oscillations were enhanced. In average across all cortical layers, stimulus-induced change in delta and alpha power negatively correlated with the MUA responses, whereas sensory-evoked increases in gamma power positively correlated with MUA responses. The time-course of the band-limited power in these frequency bands provided evidence for a model in which naturalistic visual input switched V1 between two distinct, endogenously present activity states defined by the power of low (delta, alpha) and high (gamma) frequency oscillatory activity. Therefore, the two mesoscale activity states delineated in this study may define the degree of engagement of the circuit with the processing of sensory input.
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Affiliation(s)
- Kristin K Sellers
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Davis V Bennett
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.
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29
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Sellers KK, Bennett DV, Hutt A, Fröhlich F. Anesthesia differentially modulates spontaneous network dynamics by cortical area and layer. J Neurophysiol 2013; 110:2739-51. [PMID: 24047911 DOI: 10.1152/jn.00404.2013] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Anesthesia is widely used in medicine and research to achieve altered states of consciousness and cognition. Whereas changes to macroscopic cortical activity patterns by anesthesia measured at the spatial resolution of electroencephalography have been widely studied, modulation of mesoscopic and microscopic network dynamics by anesthesia remain poorly understood. To address this gap in knowledge, we recorded spontaneous mesoscopic (local field potential) and microscopic (multiunit activity) network dynamics in primary visual cortex (V1) and prefrontal cortex (PFC) of awake and isoflurane anesthetized ferrets (Mustela putoris furo). This approach allowed for examination of activity as a function of cortical area, cortical layer, and anesthetic depth with much higher spatial and temporal resolution than in previous studies. We hypothesized that a primary sensory area and an association cortical area would exhibit different patterns of network modulation by anesthesia due to their different functional roles. Indeed, we found effects specific to cortical area and cortical layer. V1 exhibited minimal changes in rhythmic structure with anesthesia but differential modulation of input layer IV. In contrast, anesthesia profoundly altered spectral power in PFC, with more uniform modulation across cortical layers. Our results demonstrate that anesthesia modulates spontaneous cortical activity in an area- and layer-specific manner. These finding provide the basis for 1) refining anesthesia monitoring algorithms, 2) reevaluating the large number of systems neuroscience studies performed in anesthetized animals, and 3) increasing our understanding of differential dynamics across cortical layers and areas.
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Affiliation(s)
- Kristin K Sellers
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
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