Corey Keller, MD, PhD
Assistant Professor of Psychiatry and Behavioral Sciences (Public Mental Health and Population Sciences)
Bio
Dr. Keller is an Assistant Professor of Psychiatry and Behavioral Sciences at Stanford University and an Assistant Professor at the Veterans Affairs PaloAlto Health Care System (VAPAHCS). He is a member of Stanford Bio-X and the Wu Tsai Neurosciences Institute. Dr. Keller received his MD and PhD in neuroscience from the Medical Scientist Training Program at Albert Einstein College of Medicine. He completed his residency in psychiatry at Stanford University Medical Center focused on interventional psychiatry. Dr Keller has received several grants including the F31, T32, K23, DP5 Early Independence Award, SBIR, and R01 awards. He co-developed a fully automated non-invasive brain mapping technique used across industry and academia, and has run two clinical trials (NCT01829165 and NCT02843373) collecting over 1500 participants across ten clinical centers. Dr. Keller has extensive experience in the assessment and management of individuals with treatment-resistant depression. He has developed methodology for capturing the neurophysiology of human brain networks and the effect of stimulation through invasive and non-invasive electrophysiology.
The overarching goal of Dr. Keller’s Laboratory, the Stanford Precision Neurotherapeutics Lab (precisionneuro.stanford.edu) is to improve brain stimulation treatment for neurological and psychiatric disease. His lab focuses on understanding the neural mechanisms of how brain stimulation technologies induce alter brain circuits in an effort to develop novel, personalized, and more effective brain stimulation treatments. His lab combines invasive and noninvasive human electrophysiology to answer these critical questions.
Academic Appointments
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Assistant Professor - University Medical Line, Psychiatry and Behavioral Sciences
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Member, Bio-X
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Member, Wu Tsai Neurosciences Institute
Honors & Awards
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NIH Director's Early Independence Award (DP5), NIH (2019)
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BWF Career Awards for Medical Scientists (CAMS), Burroughs Wellcome Fund (2019)
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NIH K23 Mentored Patient-Oriented Research Career Development Award, NIMH (2019)
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NIMH T32 Postdoctoral Fellowship, Stanford University (2018)
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Alpha Omega Alpha Medical Honor Society, Alpha Omega Alpha (2018)
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Collaborative Research Fellowship, Stanford Society of Physician Scholars (2018)
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Career Development Institute for Psychiatry, Stanford University (2018)
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Outstanding Resident Award, NIMH (2017)
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New Investigator Award, American Society of Clinical Psychopharmacology (2017)
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Travel Fellowship, Winter Conference on Brain Research (2016)
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Early Career Investigator Travel Award, Society of Biological Psychiatry (2016)
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Postgraduate Research Award, Alpha Omega Alpha (2016)
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Fellowship for Clinical Trials, American Society of Clinical Psychopharmacology (2016)
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Collaborative Research Fellowship, Stanford Society of Physician Scholars (2015)
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Medical School Scholar, Society of Biological Psychiatry (2015)
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Senior Research Fellowship, Albert Einstein College of Medicine (2014)
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Combining Clinical and Research Careers in Neuroscience Travel Award, NINDS (2014)
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Endowed Scholarship Fund, Neural Systems and Behavior Course (2013)
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Medical Scientist Training Program Pre-Doctoral Fellowship, Ruth L. Kirschstein National Research Service Award (2011-2015)
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Pre-Doctoral Research Training Fellowship, Epilepsy Foundation (2010-2011)
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Grant for Summer Research, Albert Einstein College of Medicine (2009)
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Master’s Thesis Highest Honors, Tufts University (2009)
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Magna Cum Laude and Senior Thesis Highest Honors, Tufts University (2007)
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Eta Kappa Nu – Electrical Engineering Honors Society, Tufts University (2007)
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Dean’s List Honors, Tufts University (2004-2007)
Boards, Advisory Committees, Professional Organizations
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Board of Directors, Clinical TMS Society (2023 - Present)
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Associate Member, American College of Neuropsychopharmacology (ACNP) (2023 - Present)
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Diplomate, American Board of Psychiatry and Neurology (2019 - Present)
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Research and Scientific Oversight, International Neuromodulation Society (2016 - Present)
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Research Committee Member, Clinical TMS Society (2017 - Present)
Professional Education
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Post-doctoral Fellowship, Stanford University, Neuroscience (2019)
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Residency, Stanford University, Psychiatry (2019)
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MD, Albert Einstein College of Medicine, Medicine (2015)
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PhD, Albert Einstein College of Medicine, Neuroscience (2015)
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MS, Tufts University, Biomedical Engineering (2009)
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BS, Tufts University, Electrical Engineering (2007)
Patents
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Corey Keller, Amit Etkin, Wei Wu. "United States Patent 41243-520P01US, Patent Pending Use of a brain-based signal for predicting and guiding brain stimulation treatment in depression"
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Corey Keller, Amit Etkin, Wei Wu. "United States Patent 41243-520P02US, Patent Pending Artifact Rejection for Transcranial Magnetic Stimulation Electroencephalogram Data."
Current Research and Scholarly Interests
The overarching goal of Dr. Keller’s Laboratory, Stanford Precision Neurotherapeutics Lab (precisionneuro.stanford.edu) is to improve brain stimulation treatment for neurological and psychiatric disease. His lab focuses on understanding the neural mechanisms of how brain stimulation technologies alter brain circuits in an effort to develop novel, personalized, and more effective brain stimulation treatments. Specifically, his lab seeks to identify and apply individualized stimulation protocols to elicit precise and predictable long-term plasticity in order to alleviate psychiatric suffering. His lab combines invasive and noninvasive human electrophysiology to answer these critical questions.
TMS is a non-invasive brain stimulation technique focused on normalizing dysfunctional brain networks and is FDA-approved for depression, OCD, migraines, and smoking cessation, with clinical trials underway for PTSD, addiction, and Alzheimers. Unfortunately, TMS is typically applied in a one-size-fits-all manner without reference to one’s biology, and as such we are in critical need for a personalized and more effective approach. Dr. Keller's seeks to improve Transcranial Magnetic Stimulation (TMS) and other brain stimulation techniques by better understanding the fundamental principles of human brain plasticity and building trans-diagnostic real-time monitoring platforms for personalized brain stimulation.
Dr. Keller's lab performs translational research at the intersection of neuroscience, electrophysiology, brain stimulation, neuroengineering, psychiatry, and precision therapeutics. Their work suggests that brain-based biomarkers may be used to predict non-responders to TMS treatment, monitor brain networks during intervention, and be used to propose novel targets and treatment paradigms.
This work has the expected outcome of producing novel stimulation treatments with enhanced specificity, plasticity, and efficacy. By increasing our understanding of the underlying mechanism and monitoring of brain changes during TMS, we will markedly increase the utility of these powerful techniques. Together, this work will help transform interventional psychiatry from an isolated (from a clinic perspective), one-size-fits-all treatment approach to one that focuses on targeting objective biomarkers and that is collaborative, large-scale, and automated, pushing the field into the age of personalized neuromodulation.
Dr. Keller emphasizes an environment conducive to team-based learning in order to train the next generation of clinically-informed circuit neuroscientists, question the status quo with rigorous scientific experiments, and make important contributions in understanding how brain stimulation alters neural circuits and behavior and translate these findings to develop targeted, personalized, and more effective treatments.
Clinical Trials
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Closed-loop Optimized rTMS for Depression
Recruiting
Targeted and individualized treatments for mental health disorders are critically needed. Repetitive transcranial magnetic stimulation (rTMS) represents the front-line of new and innovative approaches to normalizing dysfunctional brain networks in those with mental illness. rTMS is FDA-approved for depression and obsessive-compulsive disorder with clinical trials underway for PTSD and addiction, among others. However, remission rates are suboptimal and ideal stimulation parameters are unknown. We recently completed a randomized, double blind clinical trial and a depression severity biomarker that predicts clinical outcome. The overarching goal of this study is to develop the first broadly generalizable platform for real-time biomarker monitoring and personalized rTMS treatment. We plan to recruit patients with medication-resistant depression and in perform a four-phase, cross-over, double-blind, placebo-controlled trial to 1) identify how standard and optimized rTMS patterns engage the depression severity biomarker, and 2) determine the dose-response of these rTMS patterns. Findings from this study will provide the basis for a double-blind, randomized clinical trial comparing rTMS optimized to the individual against standard rTMS.
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Probing the Dorsolateral Prefrontal Cortex and Central Executive Network for Improving Neuromodulation in Depression
Recruiting
Depression is a highly prevalent condition characterized by persistent low mood, energy, and activity that can affect one's thoughts, mood, behavior, and sense of well-being. Repetitive transcranial magnetic stimulation (rTMS), a non-invasive neuromodulatory technique, is an effective treatment for depression when targeting the dorsolateral prefrontal cortex (dlPFC) of the central executive network (CEN). However, remission rates are suboptimal and individual methods to target the dlPFC are lacking. In this study, we will enroll 50 patients with major depression and in a single rTMS 'dose,' prospective, randomized, double-blind, cross-over design will assess whether rTMS targeted to an individual's central executive network (CEN) assessed by single pulse TMS can enhance network modulation. If successful, this work will lead to a clinical rTMS trial comparing this personalized targeting approach against standard rTMS.
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Brain-Based Biomarkers in Response to TMS in MDD
Not Recruiting
The overarching goal of this research program is to elucidate causal and directional neural network- level abnormalities in depression, and how they are modulated by an individually-tailored, circuit-directed intervention. By using concurrent TMS and EEG, the investigators can overcome a major limitation of EEG - the inability to demonstrate causality. Here, we plan to recruit patients with medication-resistant depression undergoing rTMS treatment. At multiple time points, we will perform TMS-EEG to investigate the excitability and connectivity profiles of brain networks and how they are modulated during treatment. This study aims to provide objective brain network measures that can predict and track clinical response to TMS treatment. Findings from this study will be utilized to develop a novel, personalized treatment protocol based on individual brain networks.
Stanford is currently not accepting patients for this trial.
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Investigating the Neural Mechanisms of Repetitive Brain Stimulation With Invasive and Noninvasive Electrophysiology in Humans
Not Recruiting
Transcranial magnetic stimulation (TMS) is an effective treatment for depression, but clinical outcome is suboptimal, partially because investigators are missing biologically-grounded brain markers which show that TMS is modifying activity at the intended target in the brain. The goal of this proposal is to characterize the key markers of the brain's response to repeated doses of TMS with high resolution using invasive brain recordings in humans, and relate these brain markers to noninvasive recordings. These markers will improve the understanding of TMS and can be used to optimize and enhance clinical efficacy for depression and other psychiatric disorders.
Stanford is currently not accepting patients for this trial. For more information, please contact Jade Truong, (408) 840-3313.
2024-25 Courses
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Independent Studies (8)
- Directed Reading in Neurosciences
NEPR 299 (Aut, Win, Spr, Sum) - Graduate Research
NEPR 399 (Aut, Win, Spr, Sum) - Graduate Research
PSYC 399 (Aut, Win, Spr, Sum) - Medical Scholars Research
PSYC 370 (Aut, Win, Spr, Sum) - Out-of-Department Advanced Research Laboratory in Bioengineering
BIOE 191X (Aut, Win, Spr, Sum) - Ph.D. Research
MATSCI 300 (Aut, Win, Spr, Sum) - Undergraduate Research, Independent Study, or Directed Reading
PSYC 199 (Aut, Win, Spr, Sum) - Writing of Original Research for Engineers
ENGR 199W (Aut, Win, Spr, Sum)
- Directed Reading in Neurosciences
Stanford Advisees
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Med Scholar Project Advisor
Maximilian Bailey -
Postdoctoral Faculty Sponsor
Umair Hassan, Ethan Solomon -
Doctoral Dissertation Advisor (NonAC)
Ajay Subramanian -
Doctoral Dissertation Co-Advisor (NonAC)
Christopher Minasi -
Doctoral Dissertation Reader (NonAC)
Benyamin Meschede-Krasa -
Postdoctoral Research Mentor
Jennifer Lissemore
All Publications
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Theta-burst direct electrical stimulation remodels human brain networks.
Nature communications
2024; 15 (1): 6982
Abstract
Theta-burst stimulation (TBS), a patterned brain stimulation technique that mimics rhythmic bursts of 3-8 Hz endogenous brain rhythms, has emerged as a promising therapeutic approach for treating a wide range of brain disorders, though the neural mechanism of TBS action remains poorly understood. We investigated the neural effects of TBS using intracranial EEG (iEEG) in 10 pre-surgical epilepsy participants undergoing intracranial monitoring. Here we show that individual bursts of direct electrical TBS at 29 frontal and temporal sites evoked strong neural responses spanning broad cortical regions. These responses exhibited dynamic local field potential voltage changes over the course of stimulation presentations, including either increasing or decreasing responses, suggestive of short-term plasticity. Stronger stimulation augmented the mean TBS response amplitude and spread with more recording sites demonstrating short-term plasticity. TBS responses were stimulation site-specific with stronger TBS responses observed in regions with strong baseline stimulation effective (cortico-cortical evoked potentials) and functional (low frequency phase locking) connectivity. Further, we could use these measures to predict stable and varying (e.g. short-term plasticity) TBS response locations. Future work may integrate pre-treatment connectivity alongside other biophysical factors to personalize stimulation parameters, thereby optimizing induction of neuroplasticity within disease-relevant brain networks.
View details for DOI 10.1038/s41467-024-51443-1
View details for PubMedID 39143083
View details for PubMedCentralID PMC11324911
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Real-time optimization to enhance noninvasive cortical excitability assessment in the human dorsolateral prefrontal cortex.
bioRxiv : the preprint server for biology
2024
Abstract
We currently lack a robust noninvasive method to measure prefrontal excitability in humans. Concurrent TMS and EEG in the prefrontal cortex is usually confounded by artifacts. Here we asked if real-time optimization could reduce artifacts and enhance a TMS-EEG measure of left prefrontal excitability.This closed-loop optimization procedure adjusts left dlPFC TMS coil location, angle, and intensity in real-time based on the EEG response to TMS. Our outcome measure was the left prefrontal early (20-60 ms) and local TMS-evoked potential (EL-TEP).In 18 healthy participants, this optimization of coil angle and brain target significantly reduced artifacts by 63% and, when combined with an increase in intensity, increased EL-TEP magnitude by 75% compared to a non-optimized approach.Real-time optimization of TMS parameters during dlPFC stimulation can enhance the EL-TEP.Enhancing our ability to measure prefrontal excitability is important for monitoring pathological states and treatment response.
View details for DOI 10.1101/2024.05.29.596317
View details for PubMedID 38853941
View details for PubMedCentralID PMC11160722
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TMS provokes target-dependent intracranial rhythms across human cortical and subcortical sites.
Brain stimulation
2024
Abstract
Transcranial magnetic stimulation (TMS) is believed to alter ongoing neural activity and cause circuit-level changes in brain function. While the electrophysiological effects of TMS have been extensively studied with scalp electroencephalography (EEG), this approach generally evaluates low-frequency neural activity at the cortical surface. However, TMS can be safely used in patients with intracranial electrodes (iEEG), allowing for direct assessment of deeper and more localized oscillatory responses across the frequency spectrum.Our study used iEEG to understand the effects of TMS on human neural activity in the spectral domain. We asked (1) which brain regions respond to cortically-targeted TMS, and in what frequency bands, (2) whether deeper brain structures exhibit oscillatory responses, and (3) whether the neural responses to TMS reflect evoked versus induced oscillations.We recruited 17 neurosurgical patients with indwelling electrodes and recorded neural activity while patients underwent repeated trials of single-pulse TMS at either the dorsolateral prefrontal cortex (DLPFC) or parietal cortex. iEEG signals were analyzed using spectral methods to understand the oscillatory responses to TMS.Stimulation to DLPFC drove widespread low-frequency increases (3-8Hz) in frontolimbic cortices and high-frequency decreases (30-110Hz) in frontotemporal areas, including the hippocampus. Stimulation to parietal cortex specifically provoked low-frequency responses in the medial temporal lobe. While most low-frequency activity was consistent with phase-locked evoked responses, anterior frontal regions exhibited induced theta oscillations following DLPFC stimulation.By combining TMS with intracranial EEG recordings, our results suggest that TMS is an effective means to perturb oscillatory neural activity in brain-wide networks, including deeper structures not directly accessed by stimulation itself.
View details for DOI 10.1016/j.brs.2024.05.014
View details for PubMedID 38821396
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Mapping cortical excitability in the human dorsolateral prefrontal cortex.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
2024; 164: 138-148
Abstract
Transcranial magnetic stimulation (TMS) to the dorsolateral prefrontal cortex (dlPFC) is an effective treatment for depression, but the neural effects after TMS remains unclear. TMS paired with electroencephalography (TMS-EEG) can causally probe these neural effects. Nonetheless, variability in single pulse TMS-evoked potentials (TEPs) across dlPFC subregions, and potential artifact induced by muscle activation, necessitate detailed mapping for accurate treatment monitoring.To characterize early TEPs anatomically and temporally (20-50 ms) close to the TMS pulse (EL-TEPs), as well as associated muscle artifacts (<20 ms), across the dlPFC. We hypothesized that TMS location and angle influence EL-TEPs, and specifically that conditions with larger muscle artifact may exhibit lower observed EL-TEPs due to over-rejection during preprocessing. Additionally, we sought to determine an optimal group-level TMS target and angle, while investigating the potential benefits of a personalized approach.In 16 healthy participants, we applied single-pulse TMS to six targets within the dlPFC at two coil angles and measured EEG responses.Stimulation location significantly influenced observed EL-TEPs, with posterior and medial targets yielding larger EL-TEPs. Regions with high EL-TEP amplitude had less muscle artifact, and vice versa. The best group-level target yielded 102% larger EL-TEP responses compared to other dlPFC targets. Optimal dlPFC target differed across subjects, suggesting that a personalized targeting approach might boost the EL-TEP by an additional 36%.EL-TEPs can be probed without significant muscle-related confounds in posterior-medial regions of the dlPFC. The identification of an optimal group-level target and the potential for further refinement through personalized targeting hold significant implications for optimizing depression treatment protocols.
View details for DOI 10.1016/j.clinph.2024.05.008
View details for PubMedID 38865780
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TMS Provokes Target-Dependent Intracranial Rhythms Across Human Cortical and Subcortical Sites
ELSEVIER SCIENCE INC. 2024: S75
View details for Web of Science ID 001282811900173
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Reliability of the TMS-evoked potential in dorsolateral prefrontal cortex.
Cerebral cortex (New York, N.Y. : 1991)
2024; 34 (4)
Abstract
We currently lack a reliable method to probe cortical excitability noninvasively from the human dorsolateral prefrontal cortex (dlPFC). We recently found that the strength of early and local dlPFC transcranial magnetic stimulation (TMS)-evoked potentials (EL-TEPs) varied widely across dlPFC subregions. Despite these differences in response amplitude, reliability at each target is unknown. Here we quantified within-session reliability of dlPFC EL-TEPs after TMS to six left dlPFC subregions in 15 healthy subjects. We evaluated reliability (concordance correlation coefficient [CCC]) across targets, time windows, quantification methods, regions of interest, sensor- vs. source-space, and number of trials. On average, the medial target was most reliable (CCC=0.78) and the most anterior target was least reliable (CCC=0.24). However, all targets except the most anterior were reliable (CCC>0.7) using at least one combination of the analytical parameters tested. Longer (20 to 60ms) and later (30 to 60ms) windows increased reliability compared to earlier and shorter windows. Reliable EL-TEPs (CCC up to 0.86) were observed using only 25 TMS trials at a medial dlPFC target. Overall, medial dlPFC targeting, wider windows, and peak-to-peak quantification improved reliability. With careful selection of target and analytic parameters, highly reliable EL-TEPs can be extracted from the dlPFC after only a small number of trials.
View details for DOI 10.1093/cercor/bhae130
View details for PubMedID 38596882
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Effects of transcranial magnetic stimulation on the human brain recorded with intracranial electrocorticography.
Molecular psychiatry
2024
Abstract
Transcranial magnetic stimulation (TMS) is increasingly used as a noninvasive technique for neuromodulation in research and clinical applications, yet its mechanisms are not well understood. Here, we present the neurophysiological effects of TMS using intracranial electrocorticography (iEEG) in neurosurgical patients. We first evaluated safety in a gel-based phantom. We then performed TMS-iEEG in 22 neurosurgical participants with no adverse events. We next evaluated intracranial responses to single pulses of TMS to the dorsolateral prefrontal cortex (dlPFC) (N = 10, 1414 electrodes). We demonstrate that TMS is capable of inducing evoked potentials both locally within the dlPFC and in downstream regions functionally connected to the dlPFC, including the anterior cingulate and insular cortex. These downstream effects were not observed when stimulating other distant brain regions. Intracranial dlPFC electrical stimulation had similar timing and downstream effects as TMS. These findings support the safety and promise of TMS-iEEG in humans to examine local and network-level effects of TMS with higher spatiotemporal resolution than currently available methods.
View details for DOI 10.1038/s41380-024-02405-y
View details for PubMedID 38317012
View details for PubMedCentralID 4876726
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Experimental suppression of transcranial magnetic stimulation-electroencephalography sensory potentials.
Human brain mapping
2022
Abstract
The sensory experience of transcranial magnetic stimulation (TMS) evokes cortical responses measured in electroencephalography (EEG) that confound interpretation of TMS-evoked potentials (TEPs). Methods for sensory masking have been proposed to minimize sensory contributions to the TEP, but the most effective combination for suprathreshold TMS to dorsolateral prefrontal cortex (dlPFC) is unknown. We applied sensory suppression techniques and quantified electrophysiology and perception from suprathreshold dlPFC TMS to identify the best combination to minimize the sensory TEP. In 21 healthy adults, we applied single pulse TMS at 120% resting motor threshold (rMT) to the left dlPFC and compared EEG vertex N100-P200 and perception. Conditions included three protocols: No masking (no auditory masking, no foam, and jittered interstimulus interval [ISI]), Standard masking (auditory noise, foam, and jittered ISI), and our ATTENUATE protocol (auditory noise, foam, over-the-ear protection, and unjittered ISI). ATTENUATE reduced vertex N100-P200 by 56%, "click" loudness perception by 50%, and scalp sensation by 36%. We show that sensory prediction, induced with predictable ISI, has a suppressive effect on vertex N100-P200, and that combining standard suppression protocols with sensory prediction provides the best N100-P200 suppression. ATTENUATE was more effective than Standard masking, which only reduced vertex N100-P200 by 22%, loudness by 27%, and scalp sensation by 24%. We introduce a sensory suppression protocol superior to Standard masking and demonstrate that using an unjittered ISI can contribute to minimizing sensory confounds. ATTENUATE provides superior sensory suppression to increase TEP signal-to-noise and contributes to a growing understanding of TMS-EEG sensory neuroscience.
View details for DOI 10.1002/hbm.25990
View details for PubMedID 35770956
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Intracortical dynamics underlying repetitive stimulation predicts changes in network connectivity.
The Journal of neuroscience : the official journal of the Society for Neuroscience
2019
Abstract
Targeted stimulation can be used to modulate the activity of brain networks. Previously we demonstrated that direct electrical stimulation produces predictable post-stimulation changes in brain excitability. However, understanding the neural dynamics during stimulation and its relationship to post-stimulation effects is limited but critical for treatment optimization. Here, we applied 10Hz direct electrical stimulation across several cortical regions in 14 human subjects (6 males) implanted with intracranial electrodes for seizure monitoring. The stimulation train was characterized by a consistent increase in high gamma (70-170Hz) power. Immediately post-train, low-frequency (1-8Hz) power increased, resulting in an evoked response that was highly correlated with the neural response during stimulation. Using two measures of network connectivity, cortico-cortical evoked potentials (indexing effective connectivity) and theta coherence (indexing functional connectivity), we found a stronger response to stimulation in regions that were highly connected to the stimulation site. In these regions, repeated cycles of stimulation trains and rest progressively altered the stimulation response. Finally, after just two minutes (10%) of repetitive stimulation, we were able to predict post-stimulation connectivity changes with high discriminability. Taken together, this work reveals a relationship between stimulation dynamics and post-stimulation connectivity changes in humans. Thus, measuring neural activity during stimulation can inform future plasticity-inducing protocols.SIGNIFICANCE STATEMENTBrain stimulation tools have the potential to revolutionize the treatment of neuropsychiatric disorders. Despite the widespread use of brain stimulation techniques such as transcranial magnetic stimulation, the therapeutic efficacy of these technologies remains suboptimal. This is in part due to a lack of understanding of the dynamic neural changes that occur during stimulation. In this study, we provide the first detailed characterization of neural activity during plasticity induction through intracranial electrode stimulation and recording in 14 medication-resistant seizure patients. These results fill a missing gap in our understanding of stimulation-induced plasticity in humans. In the longer term, these data will also guide our translational efforts toward non-invasive, personalized, closed-loop neuromodulation therapy for neurological and psychiatric disorders in humans.
View details for DOI 10.1523/JNEUROSCI.0535-19.2019
View details for PubMedID 31182638
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Brain Stimulation Therapies
AMERICAN PSYCHIATRIC ASSOCIATION PUBLISHING TEXTBOOK OF PSYCHIATRY, 7TH EDITION
2019: 861–98
View details for Web of Science ID 000550979400032
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Induction and Quantification of Excitability Changes in Human Cortical Networks
JOURNAL OF NEUROSCIENCE
2018; 38 (23): S384–S398
Abstract
How does human brain stimulation result in lasting changes in cortical excitability? Uncertainty on this question hinders the development of personalized brain stimulation therapies. To characterize how cortical excitability is altered by stimulation, we applied repetitive direct electrical stimulation in eight human subjects (male and female) undergoing intracranial monitoring. We evaluated single-pulse corticocortical-evoked potentials (CCEPs) before and after repetitive stimulation across prefrontal (n = 4), temporal (n = 1), and motor (n = 3) cortices. We asked whether a single session of repetitive stimulation was sufficient to induce excitability changes across distributed cortical sites. We found a subset of regions at which 10 Hz prefrontal repetitive stimulation resulted in both potentiation and suppression of excitability that persisted for at least 10 min. We then asked whether these dynamics could be modeled by the prestimulation connectivity profile of each subject. We found that cortical regions (1) anatomically close to the stimulated site and (2) exhibiting high-amplitude CCEPs underwent changes in excitability following repetitive stimulation. We demonstrate high accuracy (72-95%) and discriminability (81-99%) in predicting regions exhibiting changes using individual subjects' prestimulation connectivity profile, and show that adding prestimulation connectivity features significantly improved model performance. The same features predicted regions of modulation following motor and temporal cortices stimulation in an independent dataset. Together, baseline connectivity profile can be used to predict regions susceptible to brain changes and provides a basis for personalizing brain stimulation.SIGNIFICANCE STATEMENT Brain stimulation is increasingly used to treat neuropsychiatric disorders by inducing excitability changes at specific brain regions. However, our understanding of how, when, and where these changes are induced is critically lacking. We inferred plasticity in the human brain after applying electrical stimulation to the brain's surface and measuring changes in excitability. We observed excitability changes in regions anatomically and functionally closer to the stimulation site. Those in responsive regions were accurately predicted using a classifier trained on baseline brain network characteristics. Finally, we showed that the excitability changes can potentially be monitored in real-time. These results begin to fill basic gaps in our understanding of stimulation-induced brain dynamics in humans and offer pathways to optimize stimulation protocols.
View details for PubMedID 29875229
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Mapping human brain networks with cortico-cortical evoked potentials
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
2014; 369 (1653)
Abstract
The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex.
View details for DOI 10.1098/rstb.2013.0528
View details for Web of Science ID 000341695200007
View details for PubMedID 25180306
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Neurophysiological Investigation of Spontaneous Correlated and Anticorrelated Fluctuations of the BOLD Signal
JOURNAL OF NEUROSCIENCE
2013; 33 (15): 6333-6342
Abstract
Analyses of intrinsic fMRI BOLD signal fluctuations reliably reveal correlated and anticorrelated functional networks in the brain. Because the BOLD signal is an indirect measure of neuronal activity and anticorrelations can be introduced by preprocessing steps, such as global signal regression, the neurophysiological significance of correlated and anticorrelated BOLD fluctuations is a source of debate. Here, we address this question by examining the correspondence between the spatial organization of correlated BOLD fluctuations and correlated fluctuations in electrophysiological high γ power signals recorded directly from the cortical surface of 5 patients. We demonstrate that both positive and negative BOLD correlations have neurophysiological correlates reflected in fluctuations of spontaneous neuronal activity. Although applying global signal regression to BOLD signals results in some BOLD anticorrelations that are not apparent in the ECoG data, it enhances the neuronal-hemodynamic correspondence overall. Together, these findings provide support for the neurophysiological fidelity of BOLD correlations and anticorrelations.
View details for DOI 10.1523/JNEUROSCI.4837-12.2013
View details for Web of Science ID 000317476300009
View details for PubMedID 23575832
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Intrinsic functional architecture predicts electrically evoked responses in the human brain
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2011; 108 (25): 10308-10313
Abstract
Adaptive brain function is characterized by dynamic interactions within and between neuronal circuits, often occurring at the time scale of milliseconds. These complex interactions between adjacent and noncontiguous brain areas depend on a functional architecture that is maintained even in the absence of input. Functional MRI studies carried out during rest (R-fMRI) suggest that this architecture is represented in low-frequency (<0.1 Hz) spontaneous fluctuations in the blood oxygen level-dependent signal that are correlated within spatially distributed networks of brain areas. These networks, collectively referred to as the brain's intrinsic functional architecture, exhibit a remarkable correspondence with patterns of task-evoked coactivation as well as maps of anatomical connectivity. Despite this striking correspondence, there is no direct evidence that this intrinsic architecture forms the scaffold that gives rise to faster processes relevant to information processing and seizure spread. Here, we demonstrate that the spatial distribution and magnitude of temporally correlated low-frequency fluctuations observed with R-fMRI during rest predict the pattern and magnitude of corticocortical evoked potentials elicited within 500 ms after single-pulse electrical stimulation of the cerebral cortex with intracranial electrodes. Across individuals, this relationship was found to be independent of the specific regions and functional systems probed. Our findings bridge the immense divide between the temporal resolutions of these distinct measures of brain function and provide strong support for the idea that the low-frequency signal fluctuations observed with R-fMRI maintain and update the intrinsic architecture underlying the brain's repertoire of functional responses.
View details for DOI 10.1073/pnas.1019750108
View details for Web of Science ID 000291857500057
View details for PubMedID 21636787
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Heterogeneous neuronal firing patterns during interictal epileptiform discharges in the human cortex
BRAIN
2010; 133: 1668-1681
Abstract
Epileptic cortex is characterized by paroxysmal electrical discharges. Analysis of these interictal discharges typically manifests as spike-wave complexes on electroencephalography, and plays a critical role in diagnosing and treating epilepsy. Despite their fundamental importance, little is known about the neurophysiological mechanisms generating these events in human focal epilepsy. Using three different systems of microelectrodes, we recorded local field potentials and single-unit action potentials during interictal discharges in patients with medically intractable focal epilepsy undergoing diagnostic workup for localization of seizure foci. We studied 336 single units in 20 patients. Ten different cortical areas and the hippocampus, including regions both inside and outside the seizure focus, were sampled. In three of these patients, high density microelectrode arrays simultaneously recorded between 43 and 166 single units from a small (4 mm x 4 mm) patch of cortex. We examined how the firing rates of individual neurons changed during interictal discharges by determining whether the firing rate during the event was the same, above or below a median baseline firing rate estimated from interictal discharge-free periods (Kruskal-Wallis one-way analysis, P<0.05). Only 48% of the recorded units showed such a modulation in firing rate within 500 ms of the discharge. Units modulated during the discharge exhibited significantly higher baseline firing and bursting rates than unmodulated units. As expected, many units (27% of the modulated population) showed an increase in firing rate during the fast segment of the discharge (+ or - 35 ms from the peak of the discharge), while 50% showed a decrease during the slow wave. Notably, in direct contrast to predictions based on models of a pure paroxysmal depolarizing shift, 7.7% of modulated units recorded in or near the seizure focus showed a decrease in activity well ahead (0-300 ms) of the discharge onset, while 12.2% of units increased in activity in this period. No such pre-discharge changes were seen in regions well outside the seizure focus. In many recordings there was also a decrease in broadband field potential activity during this same pre-discharge period. The different patterns of interictal discharge-modulated firing were classified into more than 15 different categories. This heterogeneity in single unit activity was present within small cortical regions as well as inside and outside the seizure onset zone, suggesting that interictal epileptiform activity in patients with epilepsy is not a simple paroxysm of hypersynchronous excitatory activity, but rather represents an interplay of multiple distinct neuronal types within complex neuronal networks.
View details for DOI 10.1093/brain/awq112
View details for Web of Science ID 000278226700010
View details for PubMedID 20511283
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Contrastive Functional Connectivity Defines Neurophysiology-informed Symptom Dimensions in Major Depression.
bioRxiv : the preprint server for biology
2024
Abstract
Major depressive disorder (MDD) is a prevalent psychiatric disorder characterized by substantial clinical and neurobiological heterogeneity. Conventional studies that solely focus on clinical symptoms or neuroimaging metrics often fail to capture the intricate relationship between these modalities, limiting their ability to disentangle the complexity in MDD. Moreover, patient neuroimaging data typically contains normal sources of variance shared with healthy controls, which can obscure disorder-specific variance and complicate the delineation of disease heterogeneity.We employed contrastive principal component analysis to extract disorder-specific variations in fMRI-based resting-state functional connectivity (RSFC) by contrasting MDD patients (N=233) with age-matched healthy controls (N=285). We then applied sparse canonical correlation analysis to identify latent dimensions in the disorder variations by linking the extracted contrastive connectivity features to clinical symptoms in MDD patients.Two significant and generalizable dimensions linking distinct brain circuits and clinical profiles were discovered. The first dimension, associated with an apparent "internalizing-externalizing" symptom dimension, was characterized by self-connections within the visual network and also associated with choice reaction times of cognitive tasks. The second dimension, associated with personality facets such as extraversion and conscientiousness typically inversely associated with depression symptoms, is primarily driven by self-connections within the dorsal attention network. This "depression-protective personality" dimension is also associated with multiple cognitive task performances related to psychomotor slowing and cognitive control.Our contrastive RSFC-based dimensional approach offers a new avenue to dissect clinical heterogeneity underlying MDD. By identifying two stable, neurophysiology-informed symptom dimensions in MDD patients, our findings may enhance disease mechanism insights and facilitate precision phenotyping, thus advancing the development of targeted therapeutics for precision mental health.
View details for DOI 10.1101/2024.10.04.616707
View details for PubMedID 39416217
View details for PubMedCentralID PMC11482755
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Intracortical mechanisms of single pulse electrical stimulation (SPES) evoked excitations and inhibitions in humans.
Scientific reports
2024; 14 (1): 13784
Abstract
Cortico-cortical evoked potentials (CCEPs) elicited by single-pulse electric stimulation (SPES) are widely used to assess effective connectivity between cortical areas and are also implemented in the presurgical evaluation of epileptic patients. Nevertheless, the cortical generators underlying the various components of CCEPs in humans have not yet been elucidated. Our aim was to describe the laminar pattern arising under SPES evoked CCEP components (P1, N1, P2, N2, P3) and to evaluate the similarities between N2 and the downstate of sleep slow waves. We used intra-cortical laminar microelectrodes (LMEs) to record CCEPs evoked by 10 mA bipolar 0.5 Hz electric pulses in seven patients with medically intractable epilepsy implanted with subdural grids. Based on the laminar profile of CCEPs, the latency of components is not layer-dependent, however their rate of appearance varies across cortical depth and stimulation distance, while the seizure onset zone does not seem to affect the emergence of components. Early neural excitation primarily engages middle and deep layers, propagating to the superficial layers, followed by mainly superficial inhibition, concluding in a sleep slow wave-like inhibition and excitation sequence.
View details for DOI 10.1038/s41598-024-62433-0
View details for PubMedID 38877093
View details for PubMedCentralID PMC11178858
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Identifying Brain-Clinical Dimensions in Major Depression Using Contrastive Connectivity Analysis
ELSEVIER SCIENCE INC. 2024: S166
View details for Web of Science ID 001282811900389
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Naturalistic acute pain states decoded from neural and facial dynamics.
bioRxiv : the preprint server for biology
2024
Abstract
Pain is a complex experience that remains largely unexplored in naturalistic contexts, hindering our understanding of its neurobehavioral representation in ecologically valid settings. To address this, we employed a multimodal, data-driven approach integrating intracranial electroencephalography, pain self-reports, and facial expression quantification to characterize the neural and behavioral correlates of naturalistic acute pain in twelve epilepsy patients undergoing continuous monitoring with neural and audiovisual recordings. High self-reported pain states were associated with elevated blood pressure, increased pain medication use, and distinct facial muscle activations. Using machine learning, we successfully decoded individual participants' high versus low self-reported pain states from distributed neural activity patterns (mean AUC = 0.70), involving mesolimbic regions, striatum, and temporoparietal cortex. High self-reported pain states exhibited increased low-frequency activity in temporoparietal areas and decreased high-frequency activity in mesolimbic regions (hippocampus, cingulate, and orbitofrontal cortex) compared to low pain states. This neural pain representation remained stable for hours and was modulated by pain onset and relief. Objective facial expression changes also classified self-reported pain states, with results concordant with electrophysiological predictions. Importantly, we identified transient periods of momentary pain as a distinct naturalistic acute pain measure, which could be reliably differentiated from affect-neutral periods using intracranial and facial features, albeit with neural and facial patterns distinct from self-reported pain. These findings reveal reliable neurobehavioral markers of naturalistic acute pain across contexts and timescales, underscoring the potential for developing personalized pain interventions in real-world settings.
View details for DOI 10.1101/2024.05.10.593652
View details for PubMedID 38766098
View details for PubMedCentralID PMC11100805
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Simultaneous invasive and non-invasive recordings in humans: a novel Rosetta stone for deciphering brain activity.
Journal of neuroscience methods
2024: 110160
Abstract
Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.
View details for DOI 10.1016/j.jneumeth.2024.110160
View details for PubMedID 38734149
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TMS-associated auditory evoked potentials can be effectively masked: Evidence from intracranial EEG.
Brain stimulation
2024
View details for DOI 10.1016/j.brs.2024.05.002
View details for PubMedID 38729299
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Optimizing Antidepressant Efficacy: Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response.
medRxiv : the preprint server for health sciences
2024
Abstract
Major depressive disorder (MDD) is a common and often severe condition that profoundly diminishes quality of life for individuals across ages and demographic groups. Unfortunately, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates in a substantial number of patients. The development of effective therapies for MDD is hindered by the insufficiently understood heterogeneity within the disorder and its elusive underlying mechanisms. To address these challenges, we present a target-oriented multimodal fusion framework that robustly predicts antidepressant response by integrating structural and functional connectivity data (sertraline: R2 = 0.31; placebo: R2 = 0.22). Through the model, we identify multimodal neuroimaging biomarkers of antidepressant response and observe that sertraline and placebo show distinct predictive patterns. We further decompose the overall predictive patterns into constitutive network constellations with generalizable structural-functional co-variation, which exhibit treatment-specific association with personality traits and behavioral/cognitive task performance. Our innovative and interpretable multimodal framework provides novel insights into the intricate neuropsychopharmacology of antidepressant treatment and paves the way for advances in precision medicine and development of more targeted antidepressant therapeutics.
View details for DOI 10.1101/2024.04.11.24305583
View details for PubMedID 38645124
View details for PubMedCentralID PMC11030479
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Individual deviations from normative electroencephalographic connectivity predict antidepressant response.
Journal of affective disorders
2024
Abstract
Antidepressant medications yield unsatisfactory treatment outcomes in patients with major depressive disorder (MDD) with modest advantages over the placebo, partly due to the elusive mechanisms of antidepressant responses and unexplained heterogeneity in patient's response to treatment. Here we develop a novel normative modeling framework to quantify individual deviations in psychopathological dimensions that offers a promising avenue for the personalized treatment for psychiatric disorders.We built a normative model with resting-state electroencephalography (EEG) connectivity data from healthy controls of three independent cohorts. We characterized the individual deviation of MDD patients from the healthy norms, based on which we trained sparse predictive models for treatment responses of MDD patients (102 sertraline-medicated and 119 placebo-medicated). Hamilton depression rating scale (HAMD-17) was assessed at both baseline and after the eight-week antidepressant treatment.We successfully predicted treatment outcomes for patients receiving sertraline (r = 0.43, p < 0.001) and placebo (r = 0.33, p < 0.001). We also showed that the normative modeling framework successfully distinguished subclinical and diagnostic variabilities among subjects. From the predictive models, we identified key connectivity signatures in resting-state EEG for antidepressant treatment, suggesting differences in neural circuit involvement between sertraline and placebo responses.Our findings and highly generalizable framework advance the neurobiological understanding in the potential pathways of antidepressant responses, enabling more targeted and effective personalized MDD treatment.Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC), NCT#01407094.
View details for DOI 10.1016/j.jad.2024.01.177
View details for PubMedID 38281595
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Neural effects of TMS trains on the human prefrontal cortex.
Scientific reports
2023; 13 (1): 22700
Abstract
How does a train of TMS pulses modify neural activity in humans? Despite adoption of repetitive TMS (rTMS) for the treatment of neuropsychiatric disorders, we still do not understand how rTMS changes the human brain. This limited understanding stems in part from a lack of methods for noninvasively measuring the neural effects of a single TMS train-a fundamental building block of treatment-as well as the cumulative effects of consecutive TMS trains. Gaining this understanding would provide foundational knowledge to guide the next generation of treatments. Here, to overcome this limitation, we developed methods to noninvasively measure causal and acute changes in cortical excitability and evaluated this neural response to single and sequential TMS trains. In 16 healthy adults, standard 10 Hz trains were applied to the dorsolateral prefrontal cortex in a randomized, sham-controlled, event-related design and changes were assessed based on the TMS-evoked potential (TEP), a measure of cortical excitability. We hypothesized that single TMS trains would induce changes in the local TEP amplitude and that those changes would accumulate across sequential trains, but primary analyses did not indicate evidence in support of either of these hypotheses. Exploratory analyses demonstrated non-local neural changes in sensor and source space and local neural changes in phase and source space. Together these results suggest that single and sequential TMS trains may not be sufficient to modulate local cortical excitability indexed by typical TEP amplitude metrics but may cause neural changes that can be detected outside the stimulation area or using phase or source space metrics. This work should be contextualized as methods development for the monitoring of transient noninvasive neural changes during rTMS and contributes to a growing understanding of the neural effects of rTMS.
View details for DOI 10.1038/s41598-023-49250-7
View details for PubMedID 38123591
View details for PubMedCentralID 6592198
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Direct cortical stimulation induces short-term plasticity of neural oscillations in humans.
bioRxiv : the preprint server for biology
2023
Abstract
Patterned brain stimulation is commonly employed as a tool for eliciting plasticity in brain circuits and treating neuropsychiatric disorders. Although widely used in clinical settings, there remains a limited understanding of how stimulation-induced plasticity influences neural oscillations and their interplay with the underlying baseline functional architecture. To address this question, we applied 15 minutes of 10Hz focal electrical simulation, a pattern identical to 'excitatory' repetitive transcranial magnetic stimulation (rTMS), to 14 medically-intractable epilepsy patients undergoing intracranial electroencephalographic (iEEG). We quantified the spectral features of the cortico-cortical evoked potential (CCEPs) in these patients before and after stimulation. We hypothesized that for a given region the temporal and spectral components of the CCEP predicted the location and degree of stimulation-induced plasticity. Across patients, low frequency power (alpha and beta) showed the broadest change, while the magnitude of change was stronger in high frequencies (beta and gamma). Next we demonstrated that regions with stronger baseline evoked spectral responses were more likely to undergo plasticity after stimulation. These findings were specific to a given frequency in a specific temporal window. Post-stimulation power changes were driven by the interaction between direction of change in baseline power and temporal window of change. Finally, regions exhibiting early increases and late decreases in evoked baseline power exhibited power changes after stimulation and were independent of stimulation location. Together, these findings that time-frequency baseline features predict post-stimulation plasticity effects demonstrate properties akin to Hebbian learning in humans and extend this theory to the temporal and spectral window of interest. These findings can help improve our understanding of human brain plasticity and lead to more effective brain stimulation techniques.
View details for DOI 10.1101/2023.11.15.567302
View details for PubMedID 38014071
View details for PubMedCentralID PMC10680685
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Reliability of the TMS-evoked potential in dorsolateral prefrontal cortex.
bioRxiv : the preprint server for biology
2023
Abstract
Background: We currently lack a robust and reliable method to probe cortical excitability noninvasively from the human dorsolateral prefrontal cortex (dlPFC), a region heavily implicated in psychiatric disorders. We recently found that the strength of early and local dlPFC single pulse transcranial magnetic stimulation (TMS)-evoked potentials (EL-TEPs) varied widely depending on the anatomical subregion probed, with more medial regions eliciting stronger responses than anterolateral sites. Despite these differences in amplitude of response, the reliability at each target is not known.Objective: To evaluate the reliability of EL-TEPs across the dlPFC.Methods: In 15 healthy subjects, we quantified within-session reliability of dlPFC EL-TEPs after single pulse TMS to six dlPFC subregions. We evaluated the concordance correlation coefficient (CCC) across targets and analytical parameters including time window, quantification method, region of interest, sensor-vs. source-space, and number of trials.Results: At least one target in the anterior and posterior dlPFC produced reliable EL-TEPs (CCC>0.7). The medial target was most reliable (CCC = 0.78) and the most anterior target was least reliable (CCC = 0.24). ROI size and type (sensor vs. source space) did not affect reliability. Longer (20-60 ms, CCC = 0.62) and later (30-60 ms, CCC = 0.61) time windows resulted in higher reliability compared to earlier and shorter (20-40 ms, CCC 0.43; 20-50 ms, CCC = 0.55) time windows. Peak-to-peak quantification resulted in higher reliability than the mean of the absolute amplitude. Reliable EL-TEPs (CCC up to 0.86) were observed using only 25 TMS trials for a medial dlPFC target.Conclusions: Medial TMS location, wider time window (20-60ms), and peak-to-peak quantification improved reliability. Highly reliable EL-TEPs can be extracted from dlPFC after only a small number of trials.Highlights: Medial dlPFC target improved EL-TEP reliability compared to anterior targets.After optimizing analytical parameters, at least one anterior and one posterior target was reliable (CCC>0.7).Longer (20-60 ms) and later (30-60 ms) time windows were more reliable than earlier and shorter (20-40 ms or 20-50 ms) latencies.Peak-to-peak quantification resulted in higher reliability compared to the mean of the absolute amplitude.As low as 25 trials can yield reliable EL-TEPs from the dlPFC.
View details for DOI 10.1101/2023.09.04.556283
View details for PubMedID 37732239
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TMS provokes target-dependent intracranial rhythms across human cortical and subcortical sites.
bioRxiv : the preprint server for biology
2023
Abstract
Transcranial magnetic stimulation (TMS) is increasingly deployed in the treatment of neuropsychiatric illness, under the presumption that stimulation of specific cortical targets can alter ongoing neural activity and cause circuit-level changes in brain function. While the electrophysiological effects of TMS have been extensively studied with scalp electroencephalography (EEG), this approach is most useful for evaluating low-frequency neural activity at the cortical surface. As such, little is known about how TMS perturbs rhythmic activity among deeper structures - such as the hippocampus and amygdala - and whether stimulation can alter higher-frequency oscillations. Understanding these effects is necessary to refine clinical stimulation protocols and better use TMS as a neuroscientific tool to investigate causal relationships in the brain. Recent work has established that TMS can be safely used in patients with intracranial electrodes (iEEG), making it possible to collect direct neural recordings at sufficient spatiotemporal resolution to examine oscillatory responses to stimulation. To that end, we recruited 17 neurosurgical patients with indwelling electrodes and recorded neural activity while patients underwent repeated trials of single-pulse TMS at various cortical sites. We found that TMS elicited widespread - but brief - changes in spectral power that markedly differed according to the stimulation target. Stimulation to the dorsolateral prefrontal cortex (DLPFC) drove widespread low-frequency increases (3-8Hz) in frontolimbic cortices, as well as high-frequency decreases (30-110Hz) in frontotemporal areas. Stimulation in parietal cortex specifically provoked low-frequency responses in the medial temporal lobe and hippocampus but not other regions. We also found high inter-trial phase consistency at low frequencies in the early post-stimulation period, suggestive of evoked responses. Taken together, we established that exogenous, non-invasive stimulation can be used to (1) provoke phase-locked theta increases and (2) briefly suppress high-frequency activity in a cortico-subcortical pattern that varies by stimulation target.
View details for DOI 10.1101/2023.08.09.552524
View details for PubMedID 37645954
View details for PubMedCentralID PMC10461914
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The role of superficial and deep layers in the generation of high frequency oscillations and interictal epileptiform discharges in the human cortex.
Scientific reports
2023; 13 (1): 9620
Abstract
Describing intracortical laminar organization of interictal epileptiform discharges (IED) and high frequency oscillations (HFOs), also known as ripples. Defining the frequency limits of slow and fast ripples. We recorded potential gradients with laminar multielectrode arrays (LME) for current source density (CSD) and multi-unit activity (MUA) analysis of interictal epileptiform discharges IEDs and HFOs in the neocortex and mesial temporal lobe of focal epilepsy patients. IEDs were observed in 20/29, while ripples only in 9/29 patients. Ripples were all detected within the seizure onset zone (SOZ). Compared to hippocampal HFOs, neocortical ripples proved to be longer, lower in frequency and amplitude, and presented non-uniform cycles. A subset of ripples (≈ 50%) co-occurred with IEDs, while IEDs were shown to contain variable high-frequency activity, even below HFO detection threshold. The limit between slow and fast ripples was defined at 150 Hz, while IEDs' high frequency components form clusters separated at 185 Hz. CSD analysis of IEDs and ripples revealed an alternating sink-source pair in the supragranular cortical layers, although fast ripple CSD appeared lower and engaged a wider cortical domain than slow ripples MUA analysis suggested a possible role of infragranularly located neural populations in ripple and IED generation. Laminar distribution of peak frequencies derived from HFOs and IEDs, respectively, showed that supragranular layers were dominated by slower (< 150 Hz) components. Our findings suggest that cortical slow ripples are generated primarily in upper layers while fast ripples and associated MUA in deeper layers. The dissociation of macro- and microdomains suggests that microelectrode recordings may be more selective for SOZ-linked ripples. We found a complex interplay between neural activity in the neocortical laminae during ripple and IED formation. We observed a potential leading role of cortical neurons in deeper layers, suggesting a refined utilization of LMEs in SOZ localization.
View details for DOI 10.1038/s41598-022-22497-2
View details for PubMedID 37316509
View details for PubMedCentralID PMC10267175
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Individual Deviations from Normative Electroencephalographic Connectivity Predict Antidepressant Response.
medRxiv : the preprint server for health sciences
2023
Abstract
Antidepressant medications yield unsatisfactory treatment outcomes in patients with major depressive disorder (MDD) with modest advantages over the placebo. This modest efficacy is partly due to the elusive mechanisms of antidepressant responses and unexplained heterogeneity in patient's response to treatment - the approved antidepressants only benefit a portion of patients, calling for personalized psychiatry based on individual-level prediction of treatment responses. Normative modeling, a framework that quantifies individual deviations in psychopathological dimensions, offers a promising avenue for the personalized treatment for psychiatric disorders. In this study, we built a normative model with resting-state electroencephalography (EEG) connectivity data from healthy controls of three independent cohorts. We characterized the individual deviation of MDD patients from the healthy norms, based on which we trained sparse predictive models for treatment responses of MDD patients. We successfully predicted treatment outcomes for patients receiving sertraline (r = 0.43, p < 0.001) and placebo (r = 0.33, p < 0.001). We also showed that the normative modeling framework successfully distinguished subclinical and diagnostic variabilities among subjects. From the predictive models, we identified key connectivity signatures in resting-state EEG for antidepressant treatment, suggesting differences in neural circuit involvement between treatment responses. Our findings and highly generalizable framework advance the neurobiological understanding in the potential pathways of antidepressant responses, enabling more targeted and effective MDD treatment.
View details for DOI 10.1101/2023.05.24.23290434
View details for PubMedID 37292874
View details for PubMedCentralID PMC10246152
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A generalizable functional connectivity signature characterizes brain dysfunction and links to rTMS treatment response in cocaine use disorder.
medRxiv : the preprint server for health sciences
2023
Abstract
Cocaine use disorder (CUD) is a prevalent substance abuse disorder, and repetitive transcranial magnetic stimulation (rTMS) has shown potential in reducing cocaine cravings. However, a robust and replicable biomarker for CUD phenotyping is lacking, and the association between CUD brain phenotypes and treatment response remains unclear. Our study successfully established a cross-validated functional connectivity signature for accurate CUD phenotyping, using resting-state functional magnetic resonance imaging from a discovery cohort, and demonstrated its generalizability in an independent replication cohort. We identified phenotyping FCs involving increased connectivity between the visual network and dorsal attention network, and between the frontoparietal control network and ventral attention network, as well as decreased connectivity between the default mode network and limbic network in CUD patients compared to healthy controls. These abnormal connections correlated significantly with other drug use history and cognitive dysfunctions, e.g., non-planning impulsivity. We further confirmed the prognostic potential of the identified discriminative FCs for rTMS treatment response in CUD patients and found that the treatment-predictive FCs mainly involved the frontoparietal control and default mode networks. Our findings provide new insights into the neurobiological mechanisms of CUD and the association between CUD phenotypes and rTMS treatment response, offering promising targets for future therapeutic development.
View details for DOI 10.1101/2023.04.21.23288948
View details for PubMedID 37162878
View details for PubMedCentralID PMC10168499
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Mapping cortical excitability in the human dorsolateral prefrontal cortex.
bioRxiv : the preprint server for biology
2023
Abstract
Background: Repetitive transcranial magnetic stimulation (rTMS) to the dorsolateral prefrontal cortex (dlPFC) is an effective treatment for depression, but the neural response to rTMS remains unclear. TMS with electroencephalography (TMS-EEG) can probe these neural effects, but variation in TMS-evoked potentials (TEPs) across the dlPFC are not well characterized and often obscured by muscle artifact. Mapping TEPs and artifacts across dlPFC targets is needed to identify high fidelity subregions that can be used for rTMS treatment monitoring.Objective: To characterize 'early TEPs' anatomically and temporally close (20-50 ms) to the TMS pulse and associated muscle artifacts (<20 ms) across the dlPFC. We hypothesized that TMS location and angle would affect these early TEPs and that TEP size would be inversely related to muscle artifact. We sought to identify an optimal TMS target / angle for the group and asked if individualization would be beneficial.Methods: In 16 healthy participants, we applied single-pulse TMS to six targets within the dlPFC at two coil angles and measured EEG responses.Results: Early TEPs were sensitive to stimulation location, with posterior and medial targets yielding larger early TEPs. Regions with high early TEP amplitude had less muscle artifact, and vice versa. The best group-level target yielded 102% larger TEP responses compared to other standard targets. Optimal TMS target differed across subjects, suggesting that a personalized targeting approach could boost the early TEP by additional 36%.Conclusions: The early TEPs can be probed without significant muscle-related confounds in posterior-medial regions of the dlPFC. A personalized targeting approach may further enhance the signal quality of the early TEP.Highlights: Early TEPs varied significantly across the dlPFC as a function of TMS target.TMS targets with less muscle artifact had significantly larger early TEPs.Selection of a postero-medial target increased early TEPs by 102% compared to anterior targets.Retrospective target and angle optimization increased early TEPs by an additional 36%.
View details for DOI 10.1101/2023.01.20.524867
View details for PubMedID 36711689
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Neural effects of TMS trains on the human prefrontal cortex
bioRxiv
2023
View details for DOI 10.1101/2023.01.30.526374
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Reliability and Validity of Transcranial Magnetic Stimulation-Electroencephalography Biomarkers.
Biological psychiatry. Cognitive neuroscience and neuroimaging
2022
Abstract
Noninvasive brain stimulation and neuroimaging have revolutionized human neuroscience with a multitude of applications, including diagnostic subtyping, treatment optimization, and relapse prediction. It is therefore particularly relevant to identify robust and clinically valuable brain biomarkers linking symptoms to their underlying neural mechanisms. Brain biomarkers must be reproducible (i.e., have internal reliability) across similar experiments within a laboratory and be generalizable (i.e., have external reliability) across experimental setups, laboratories, brain regions, and disease states. However, reliability (internal and external) is not alone sufficient; biomarkers also must have validity. Validity describes closeness to a true measure of the underlying neural signal or disease state. We propose that these metrics, reliability and validity, should be evaluated and optimized before any biomarker is used to inform treatment decisions. Here, we discuss these metrics with respect to causal brain connectivity biomarkers from coupling transcranial magnetic stimulation (TMS) with electroencephalography (EEG). We discuss controversies around TMS-EEG stemming from the multiple large off-target components (noise) and relatively weak genuine brain responses (signal), as is unfortunately often the case in noninvasive human neuroscience. We review the current state of TMS-EEG recordings, which consist of a mix of reliable noise and unreliable signal. We describe methods for evaluating TMS-EEG biomarkers, including how to assess internal and external reliability across facilities, cognitive states, brain networks, and disorders and how to validate these biomarkers using invasive neural recordings or treatment response. We provide recommendations to increase reliability and validity, discuss lessons learned, and suggest future directions for the field.
View details for DOI 10.1016/j.bpsc.2022.12.005
View details for PubMedID 36894435
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Personalized Repetitive Transcranial Magnetic Stimulation for Depression.
Biological psychiatry. Cognitive neuroscience and neuroimaging
2022
Abstract
Personalized treatments are gaining momentum across all fields of medicine. Precision medicine can be applied to neuromodulatory techniques, in which focused brain stimulation treatments such as repetitive transcranial magnetic stimulation (rTMS) modulate brain circuits and alleviate clinical symptoms. rTMS is well tolerated and clinically effective for treatment-resistant depression and other neuropsychiatric disorders. Despite its wide stimulation parameter space (location, angle, pattern, frequency, and intensity can be adjusted), rTMS is currently applied in a one-size-fits-all manner, potentially contributing to its suboptimal clinical response (∼50%). In this review, we examine components of rTMS that can be optimized to account for interindividual variability in neural function and anatomy. We discuss current treatment options for treatment-resistant depression, the neural mechanisms thought to underlie treatment, targeting strategies, stimulation parameter selection, and adaptive closed-loop treatment. We conclude that a better understanding of the wide and modifiable parameter space of rTMS will greatly improve the clinical outcome.
View details for DOI 10.1016/j.bpsc.2022.10.006
View details for PubMedID 36792455
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Pilot study of responsive nucleus accumbens deep brain stimulation for loss-of-control eating.
Nature medicine
2022
Abstract
Cravings that precede loss of control (LOC) over food consumption present an opportunity for intervention in patients with the binge eating disorder (BED). In this pilot study, we used responsive deep brain stimulation (DBS) to record nucleus accumbens (NAc) electrophysiology during food cravings preceding LOC eating in two patients with BED and severe obesity (trial registration no. NCT03868670). Increased NAc low-frequency oscillations, prominent during food cravings, were used to guide DBS delivery. Over 6 months, we observed improved self-control of food intake and weight loss. These findings provide early support for restoring inhibitory control with electrophysiologically-guided NAc DBS. Further work with increased sample sizes is required to determine the scalability of this approach.
View details for DOI 10.1038/s41591-022-01941-w
View details for PubMedID 36038628
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Spectral-Temporal Electrophysiological Features Predict Short-Term Plasticity in Humans Following Repetitive Stimulation
ELSEVIER SCIENCE INC. 2022: S202
View details for Web of Science ID 000789022200494
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Anticipatory human subthalamic area beta-band power responses to dissociable tastes correlate with weight gain.
Neurobiology of disease
2021: 105348
Abstract
The availability of enticing sweet, fatty tastes is prevalent in the modern diet and contribute to overeating and obesity. In animal models, the subthalamic area plays a role in mediating appetitive and consummatory feeding behaviors, however, its role in human feeding is unknown. We used intraoperative, subthalamic field potential recordings while participants (n = 5) engaged in a task designed to provoke responses of taste anticipation and receipt. Decreased subthalamic beta-band (15-30 Hz) power responses were observed for both sweet-fat and neutral tastes. Anticipatory responses to taste-neutral cues started with an immediate decrease in beta-band power from baseline followed by an early beta-band rebound above baseline. On the contrary, anticipatory responses to sweet-fat were characterized by a greater and sustained decrease in beta-band power. These activity patterns were topographically specific to the subthalamic nucleus and substantia nigra. Further, a neural network trained on this beta-band power signal accurately predicted (AUC ≥ 74%) single trials corresponding to either taste. Finally, the magnitude of the beta-band rebound for a neutral taste was associated with increased body mass index after starting deep brain stimulation therapy. We provide preliminary evidence of discriminatory taste encoding within the subthalamic area associated with control mechanisms that mediate appetitive and consummatory behaviors.
View details for DOI 10.1016/j.nbd.2021.105348
View details for PubMedID 33781923
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Deep Transcranial Magnetic Stimulation Combined With Brief Exposure for Posttraumatic Stress Disorder: A Prospective Multisite Randomized Trial.
Biological psychiatry
2021
Abstract
Posttraumatic stress disorder (PTSD) is both prevalent and debilitating. While deep transcranial magnetic stimulation (dTMS) has shown preliminary efficacy, exposure therapy remains the most efficacious, though limited, treatment in PTSD. The medial prefrontal cortex (mPFC) is implicated in extinction learning, suggesting that concurrent mPFC stimulation may enhance exposure therapy. In this randomized controlled multicenter trial, the efficacy and safety of mPFC dTMS combined with a brief exposure procedure were studied in patients with PTSD.Immediately following exposure to their trauma narrative, 125 outpatients were randomly assigned to receive dTMS or sham. Twelve sessions were administered over 4 weeks, with a primary end point of change in 5-week Clinician-Administered PTSD Scale for DSM-5 score. This clinical study did not include biological markers.Clinician-Administered PTSD Scale for DSM-5 score improved significantly in both groups at 5 weeks, though the improvement was smaller in the dTMS group (16.32) compared with the sham group (20.52; p = .027). At 9 weeks, improvement continued in Clinician-Administered PTSD Scale for DSM-5 score in both groups but remained smaller in dTMS (19.0) versus sham (24.4; p = .024).Both groups showed significant PTSD symptom improvement, possibly from the brief script-driven imagery exposure. While our design was unable to rule out placebo effects, the magnitude and durability of improvement suggest that repeated ultrabrief exposure therapy alone may be an effective treatment for PTSD, warranting additional study. The surprising and unexpected effect in the dTMS group also suggests that repeated mPFC stimulation with the H7 coil may interfere with trauma memory-mediated extinction. Our results provide new insight for dTMS approaches for possible future avenues to treat PTSD.
View details for DOI 10.1016/j.biopsych.2021.04.019
View details for PubMedID 34274108
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Editorial: Inter- and Intra-subject Variability in Brain Imaging and Decoding.
Frontiers in computational neuroscience
1800; 15: 791129
View details for DOI 10.3389/fncom.2021.791129
View details for PubMedID 34912203
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The insulo-opercular cortex encodes food-specific content under controlled and naturalistic conditions.
Nature communications
2021; 12 (1): 3609
Abstract
The insulo-opercular network functions critically not onlyin encoding taste, but also inguiding behavior based on anticipated food availability. However, there remains no direct measurement of insulo-opercular activity when humans anticipate taste. Here, we collect direct, intracranial recordings during a food task that elicits anticipatory and consummatory taste responses, and during ad libitum consumption of meals. While cue-specific high-frequency broadband (70-170Hz) activity predominant in the left posterior insula is selective for taste-neutral cues, sparse cue-specific regions in the anterior insulaare selective for palatable cues. Latency analysis reveals this insular activity is preceded by non-discriminatory activity in the frontal operculum. During ad libitum meal consumption, time-locked high-frequency broadband activity at the time of food intake discriminates food types and is associated with cue-specific activity during the task. These findings reveal spatiotemporally-specificactivity in the human insulo-opercular cortex that underlies anticipatory evaluation of food across both controlled and naturalistic settings.
View details for DOI 10.1038/s41467-021-23885-4
View details for PubMedID 34127675
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Global connectivity and local excitability changes underlie antidepressant effects of repetitive transcranial magnetic stimulation.
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
2020
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a commonly used treatment for major depressive disorder (MDD). However, our understanding of the mechanism by which TMS exerts its antidepressant effect is minimal. Furthermore, we lack brain signals that can be used to predict and track clinical outcome. Such signals would allow for treatment stratification and optimization. Here, we performed a randomized, sham-controlled clinical trial and measured electrophysiological, neuroimaging, and clinical changes before and after rTMS. Patients (N = 36) were randomized to receive either active or sham rTMS to the left dorsolateral prefrontal cortex (dlPFC) for 20 consecutive weekdays. To capture the rTMS-driven changes in connectivity and causal excitability, resting fMRI and TMS/EEG were performed before and after the treatment. Baseline causal connectivity differences between depressed patients and healthy controls were also evaluated with concurrent TMS/fMRI. We found that active, but not sham rTMS elicited (1) an increase in dlPFC global connectivity, (2) induction of negative dlPFC-amygdala connectivity, and (3) local and distributed changes in TMS/EEG potentials. Global connectivity changes predicted clinical outcome, while both global connectivity and TMS/EEG changes tracked clinical outcome. In patients but not healthy participants, we observed a perturbed inhibitory effect of the dlPFC on the amygdala. Taken together, rTMS induced lasting connectivity and excitability changes from the site of stimulation, such that after active treatment, the dlPFC appeared better able to engage in top-down control of the amygdala. These measures of network functioning both predicted and tracked clinical outcome, potentially opening the door to treatment optimization.
View details for DOI 10.1038/s41386-020-0633-z
View details for PubMedID 32053828
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Reproducibility in TMS-EEG studies: A call for data sharing, standard procedures and effective experimental control
BRAIN STIMULATION
2019; 12 (3): 787–90
View details for DOI 10.1016/j.brs.2019.01.010
View details for Web of Science ID 000465395800027
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Using fMRI connectivity to define a treatment-resistant form of post-traumatic stress disorder
SCIENCE TRANSLATIONAL MEDICINE
2019; 11 (486)
View details for DOI 10.1126/scitranslmed.aal3236
View details for Web of Science ID 000463186500002
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Using fMRI connectivity to define a treatment-resistant form of post-traumatic stress disorder.
Science translational medicine
2019; 11 (486)
Abstract
A mechanistic understanding of the pathology of psychiatric disorders has been hampered by extensive heterogeneity in biology, symptoms, and behavior within diagnostic categories that are defined subjectively. We investigated whether leveraging individual differences in information-processing impairments in patients with post-traumatic stress disorder (PTSD) could reveal phenotypes within the disorder. We found that a subgroup of patients with PTSD from two independent cohorts displayed both aberrant functional connectivity within the ventral attention network (VAN) as revealed by functional magnetic resonance imaging (fMRI) neuroimaging and impaired verbal memory on a word list learning task. This combined phenotype was not associated with differences in symptoms or comorbidities, but nonetheless could be used to predict a poor response to psychotherapy, the best-validated treatment for PTSD. Using concurrent focal noninvasive transcranial magnetic stimulation and electroencephalography, we then identified alterations in neural signal flow in the VAN that were evoked by direct stimulation of that network. These alterations were associated with individual differences in functional fMRI connectivity within the VAN. Our findings define specific neurobiological mechanisms in a subgroup of patients with PTSD that could contribute to the poor response to psychotherapy.
View details for PubMedID 30944165
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Reproducibility in TMS-EEG studies: A call for data sharing, standard procedures and effective experimental control.
Brain stimulation
2019
View details for PubMedID 30738777
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ARTIST: A fully automated artifact rejection algorithm for single-pulse TMS-EEG data.
Human brain mapping
2018
Abstract
Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings.
View details for PubMedID 29331054
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Tuning face perception with electrical stimulation of the fusiform gyrus.
Human brain mapping
2017; 38 (6): 2830-2842
Abstract
The fusiform gyrus (FG) is an important node in the face processing network, but knowledge of its causal role in face perception is currently limited. Recent work demonstrated that high frequency stimulation applied to the FG distorts the perception of faces in human subjects (Parvizi et al. []: J Neurosci 32:14915-14920). However, the timing of this process in the FG relative to stimulus onset and the spatial extent of FG's role in face perception are unknown. Here, we investigate the causal role of the FG in face perception by applying precise, event-related electrical stimulation (ES) to higher order visual areas including the FG in six human subjects undergoing intracranial monitoring for epilepsy. We compared the effects of single brief (100 μs) electrical pulses to the FG and non-face-selective visual areas on the speed and accuracy of detecting distorted faces. Brief ES applied to face-selective sites did not affect accuracy but significantly increased the reaction time (RT) of detecting face distortions. Importantly, RT was altered only when ES was applied 100ms after visual onset and in face-selective but not place-selective sites. Furthermore, ES applied to face-selective areas decreased the amplitude of visual evoked potentials and high gamma power over this time window. Together, these results suggest that ES of face-selective regions within a critical time window induces a delay in face perception. These findings support a temporally and spatially specific causal role of face-selective areas and signify an important link between electrophysiology and behavior in face perception. Hum Brain Mapp 38:2830-2842, 2017. © 2017 Wiley Periodicals, Inc.
View details for DOI 10.1002/hbm.23543
View details for PubMedID 28345189
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Reliability of Transcranial Magnetic Stimulation EEG Evoked Potentials
ELSEVIER SCIENCE INC. 2017: S131
View details for DOI 10.1016/j.biopsych.2017.02.333
View details for Web of Science ID 000400348700319
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Test-retest reliability of transcranial magnetic stimulation EEG evoked potentials.
Brain stimulation
2017
Abstract
Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs), recorded using electroencephalography (TMS-EEG), offer a powerful tool for measuring causal interactions in the human brain. However, the test-retest reliability of TEPs, critical to their use in clinical biomarker and interventional studies, remains poorly understood.We quantified TEP reliability to: (i) determine the minimal TEP amplitude change which significantly exceeds that associated with simply re-testing, (ii) locate the most reliable scalp regions of interest (ROIs) and TEP peaks, and (iii) determine the minimal number of TEP pulses for achieving reliability.TEPs resulting from stimulation of the left dorsolateral prefrontal cortex were collected on two separate days in sixteen healthy participants. TEP peak amplitudes were compared between alternating trials, split-halves of the same run, two runs five minutes apart and two runs on separate days. Reliability was quantified using concordance correlation coefficient (CCC) and smallest detectable change (SDC).Substantial concordance was achieved in prefrontal electrodes at 40 and 60 ms, centroparietal and left parietal ROIs at 100 ms, and central electrodes at 200 ms. Minimum SDC was found in the same regions and peaks, particularly for the peaks at 100 and 200 ms. CCC, but not SDC, reached optimal values by 60-100 pulses per run with saturation beyond this number, while SDC continued to improve with increased pulse numbers.TEPs were robust and reliable, requiring a relatively small number of trials to achieve stability, and are thus well suited as outcomes in clinical biomarker or interventional studies.
View details for PubMedID 29342443
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Test-retest reliability of transcranial magnetic stimulation EEG evoked potentials
Brain Stimulation
2017
Abstract
Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs), recorded using electroencephalography (TMS-EEG), offer a powerful tool for measuring causal interactions in the human brain. However, the test-retest reliability of TEPs, critical to their use in clinical biomarker and interventional studies, remains poorly understood.We quantified TEP reliability to: (i) determine the minimal TEP amplitude change which significantly exceeds that associated with simply re-testing, (ii) locate the most reliable scalp regions of interest (ROIs) and TEP peaks, and (iii) determine the minimal number of TEP pulses for achieving reliability.TEPs resulting from stimulation of the left dorsolateral prefrontal cortex were collected on two separate days in sixteen healthy participants. TEP peak amplitudes were compared between alternating trials, split-halves of the same run, two runs five minutes apart and two runs on separate days. Reliability was quantified using concordance correlation coefficient (CCC) and smallest detectable change (SDC).Substantial concordance was achieved in prefrontal electrodes at 40 and 60 ms, centroparietal and left parietal ROIs at 100 ms, and central electrodes at 200 ms. Minimum SDC was found in the same regions and peaks, particularly for the peaks at 100 and 200 ms. CCC, but not SDC, reached optimal values by 60-100 pulses per run with saturation beyond this number, while SDC continued to improve with increased pulse numbers.TEPs were robust and reliable, requiring a relatively small number of trials to achieve stability, and are thus well suited as outcomes in clinical biomarker or interventional studies.
View details for DOI 10.1016/j.brs.2017.12.010
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Cotard Delusion in the Context of Schizophrenia: A Case Report and Review of the Literature
FRONTIERS IN PSYCHOLOGY
2016; 7
Abstract
The Cotard delusion (CD) is one of a variety of narrowly defined monothematic delusions characterized by nihilistic beliefs about the body's existence or life itself. The presence of CD within the context of schizophrenia is rare (<1%), and remains understudied.'Mr. C' is a 58-year-old veteran with a prior diagnosis of schizophrenia, who presented with CD in the context of significant depression, suicidal ideation, violence, and self-harm behavior. He perseverated in his belief that he was physically dead and possessed by demons for several weeks. This delusion was reinforced by his religious belief that life was an attribute of God, and by inference, he as a human, was dead. His condition gradually improved over the course of treatment with Divalproex and quetiapine with discussions about the rationale for his belief. Upon discharge, Mr. C. demonstrated awareness of his fixation on death and an ability to redirect himself.This case highlights the need to better understand the co-occurrence of CD in schizophrenia, their differentiation, the increased risk of violence and self-harm behavior in this presentation, and how specific events and religious factors can influence delusional themes of CD. Pharmacotherapy and aspects of cognitive-behavioral therapy may be effective in ameliorating these symptoms in CD.
View details for DOI 10.3389/fpsyg.2016.01351
View details for PubMedID 27656159
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The Clinical Applicability of Functional Connectivity in Depression: Pathways Toward More Targeted Intervention.
Biological psychiatry. Cognitive neuroscience and neuroimaging
2016; 1 (3): 262–70
Abstract
Resting-state functional magnetic resonance imaging provides a noninvasive method to rapidly map large-scale brain networks affected in depression and other psychiatric disorders. Dysfunctional connectivity in large-scale brain networks has been consistently implicated in major depressive disorder (MDD). Although advances have been made in identifying neural circuitry implicated in MDD, this information has yet to be translated into improved diagnostic or treatment interventions. In the first section of this review, we discuss dysfunctional connectivity in affective salience, cognitive control, and default mode networks observed in MDD in association with characteristic symptoms of the disorder. In the second section, we address neurostimulation focusing on transcranial magnetic stimulation and evidence that this approach may directly modulate circuit abnormalities. Finally, we discuss possible avenues of future research to develop more precise diagnoses and targeted interventions within the heterogeneous diagnostic category of MDD as well as the methodological limitations to clinical implementation. We conclude by proposing, with cautious optimism, the future incorporation of neuroimaging into clinical practice as a tool to aid in more targeted diagnosis and treatment guided by circuit-level connectivity dysfunction in patients with depression.
View details for PubMedID 29560882
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The Limited Utility of Multiunit Data in Differentiating Neuronal Population Activity
PLOS ONE
2016; 11 (4)
Abstract
To date, single neuron recordings remain the gold standard for monitoring the activity of neuronal populations. Since obtaining single neuron recordings is not always possible, high frequency or 'multiunit activity' (MUA) is often used as a surrogate. Although MUA recordings allow one to monitor the activity of a large number of neurons, they do not allow identification of specific neuronal subtypes, the knowledge of which is often critical for understanding electrophysiological processes. Here, we explored whether prior knowledge of the single unit waveform of specific neuron types is sufficient to permit the use of MUA to monitor and distinguish differential activity of individual neuron types. We used an experimental and modeling approach to determine if components of the MUA can monitor medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) in the mouse dorsal striatum. We demonstrate that when well-isolated spikes are recorded, the MUA at frequencies greater than 100Hz is correlated with single unit spiking, highly dependent on the waveform of each neuron type, and accurately reflects the timing and spectral signature of each neuron. However, in the absence of well-isolated spikes (the norm in most MUA recordings), the MUA did not typically contain sufficient information to permit accurate prediction of the respective population activity of MSNs and FSIs. Thus, even under ideal conditions for the MUA to reliably predict the moment-to-moment activity of specific local neuronal ensembles, knowledge of the spike waveform of the underlying neuronal populations is necessary, but not sufficient.
View details for DOI 10.1371/journal.pone.0153154
View details for Web of Science ID 000374970600012
View details for PubMedID 27111446
View details for PubMedCentralID PMC4844128
- The clinical applicability of functional connectivity in depression: Pathways toward more targeted intervention Journal of Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2016
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A case of butane hash oil (marijuana wax)-induced psychosis
SUBSTANCE ABUSE
2016; 37 (3): 384-386
Abstract
Marijuana is one of the most widely used controlled substances in the United States. Despite extensive research on smoked marijuana, little is known regarding the potential psychotropic effects of marijuana "wax," a high-potency form of marijuana that is gaining in popularity.The authors present a case of "Mr. B," a 34-year-old veteran who presented with profound psychosis in the setting of recent initiation of heavy, daily marijuana wax use. He exhibited incoherent speech and odd behaviors and appeared to be in a dream-like state with perseverating thoughts about his combat experience. His condition persisted despite treatment with risperidone 4 mg twice a day (BID), but improved dramatically on day 8 of hospitalization with the return of baseline mental function. Following discharge, Mr. B discontinued all marijuana use and did not exhibit the return of any psychotic symptoms.This study highlights the need for future research regarding the potential medical and psychiatric effects of new, high-potency forms of marijuana. Could cannabis have a dose-dependent impact on psychosis? What other potential psychiatric effects could emerge heretofore unseen in lower potency formulations? Given the recent legalization of marijuana, these questions merit timely exploration.
View details for DOI 10.1080/08897077.2016.1141153
View details for Web of Science ID 000382769800003
View details for PubMedID 26820171
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Evoked Effective Connectivity of the Human Neocortex
HUMAN BRAIN MAPPING
2014; 35 (12): 5736-5753
Abstract
The role of cortical connectivity in brain function and pathology is increasingly being recognized. While in vivo magnetic resonance imaging studies have provided important insights into anatomical and functional connectivity, these methodologies are limited in their ability to detect electrophysiological activity and the causal relationships that underlie effective connectivity. Here, we describe results of cortico-cortical evoked potential (CCEP) mapping using single pulse electrical stimulation in 25 patients undergoing seizure monitoring with subdural electrode arrays. Mapping was performed by stimulating adjacent electrode pairs and recording CCEPs from the remainder of the electrode array. CCEPs reliably revealed functional networks and showed an inverse relationship to distance between sites. Coregistration to Brodmann areas (BA) permitted group analysis. Connections were frequently directional with 43% of early responses and 50% of late responses of connections reflecting relative dominance of incoming or outgoing connections. The most consistent connections were seen as outgoing from motor cortex, BA6-BA9, somatosensory (SS) cortex, anterior cingulate cortex, and Broca's area. Network topology revealed motor, SS, and premotor cortices along with BA9 and BA10 and language areas to serve as hubs for cortical connections. BA20 and BA39 demonstrated the most consistent dominance of outdegree connections, while BA5, BA7, auditory cortex, and anterior cingulum demonstrated relatively greater indegree. This multicenter, large-scale, directional study of local and long-range cortical connectivity using direct recordings from awake, humans will aid the interpretation of noninvasive functional connectome studies.
View details for DOI 10.1002/hbm.22581
View details for Web of Science ID 000344398900002
View details for PubMedID 25044884
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Corticocortical Evoked Potentials Reveal Projectors and Integrators in Human Brain Networks
JOURNAL OF NEUROSCIENCE
2014; 34 (27): 9152-9163
Abstract
The cerebral cortex is composed of subregions whose functional specialization is largely determined by their incoming and outgoing connections with each other. In the present study, we asked which cortical regions can exert the greatest influence over other regions and the cortical network as a whole. Previous research on this question has relied on coarse anatomy (mapping large fiber pathways) or functional connectivity (mapping inter-regional statistical dependencies in ongoing activity). Here we combined direct electrical stimulation with recordings from the cortical surface to provide a novel insight into directed, inter-regional influence within the cerebral cortex of awake humans. These networks of directed interaction were reproducible across strength thresholds and across subjects. Directed network properties included (1) a decrease in the reciprocity of connections with distance; (2) major projector nodes (sources of influence) were found in peri-Rolandic cortex and posterior, basal and polar regions of the temporal lobe; and (3) major receiver nodes (receivers of influence) were found in anterolateral frontal, superior parietal, and superior temporal regions. Connectivity maps derived from electrical stimulation and from resting electrocorticography (ECoG) correlations showed similar spatial distributions for the same source node. However, higher-level network topology analysis revealed differences between electrical stimulation and ECoG that were partially related to the reciprocity of connections. Together, these findings inform our understanding of large-scale corticocortical influence as well as the interpretation of functional connectivity networks.
View details for DOI 10.1523/JNEUROSCI.4289-13.2014
View details for Web of Science ID 000339153400023
View details for PubMedID 24990935
View details for PubMedCentralID PMC4078089
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Exemplar Selectivity Reflects Perceptual Similarities in the Human Fusiform Cortex
CEREBRAL CORTEX
2014; 24 (7): 1879-1893
Abstract
While brain imaging studies emphasized the category selectivity of face-related areas, the underlying mechanisms of our remarkable ability to discriminate between different faces are less understood. Here, we recorded intracranial local field potentials from face-related areas in patients presented with images of faces and objects. A highly significant exemplar tuning within the category of faces was observed in high-Gamma (80-150 Hz) responses. The robustness of this effect was supported by single-trial decoding of face exemplars using a minimal (n = 5) training set. Importantly, exemplar tuning reflected the psychophysical distance between faces but not their low-level features. Our results reveal a neuronal substrate for the establishment of perceptual distance among faces in the human brain. They further imply that face neurons are anatomically grouped according to well-defined functional principles, such as perceptual similarity.
View details for DOI 10.1093/cercor/bht038
View details for Web of Science ID 000338110900016
View details for PubMedID 23438448
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Dominant frequencies of resting human brain activity as measured by the electrocorticogram
NEUROIMAGE
2013; 79: 223-233
Abstract
The brain's spontaneous, intrinsic activity is increasingly being shown to reveal brain function, delineate large scale brain networks, and diagnose brain disorders. One of the most studied and clinically utilized types of intrinsic brain activity are oscillations in the electrocorticogram (ECoG), a relatively localized measure of cortical synaptic activity. Here we objectively characterize the types of ECoG oscillations commonly observed over particular cortical areas when an individual is awake and immobile with eyes closed, using a surface-based cortical atlas and cluster analysis. Both methods show that [1] there is generally substantial variability in the dominant frequencies of cortical regions and substantial overlap in dominant frequencies across the areas sampled (primarily lateral central, temporal, and frontal areas), [2] theta (4-8 Hz) is the most dominant type of oscillation in the areas sampled with a mode around 7 Hz, [3] alpha (8-13 Hz) is largely limited to parietal and occipital regions, and [4] beta (13-30 Hz) is prominent peri-Rolandically, over the middle frontal gyrus, and the pars opercularis. In addition, the cluster analysis revealed seven types of ECoG spectral power densities (SPDs). Six of these have peaks at 3, 5, 7 (narrow), 7 (broad), 10, and 17 Hz, while the remaining cluster is broadly distributed with less pronounced peaks at 8, 19, and 42 Hz. These categories largely corroborate conventional sub-gamma frequency band distinctions (delta, theta, alpha, and beta) and suggest multiple sub-types of theta. Finally, we note that gamma/high gamma activity (30+ Hz) was at times prominently observed, but was too infrequent and variable across individuals to be reliably characterized. These results should help identify abnormal patterns of ECoG oscillations, inform the interpretation of EEG/MEG intrinsic activity, and provide insight into the functions of these different oscillations and the networks that produce them. Specifically, our results support theories of the importance of theta oscillations in general cortical function, suggest that alpha activity is primarily related to sensory processing/attention, and demonstrate that beta networks extend far beyond primary sensorimotor regions.
View details for DOI 10.1016/j.neuroimage.2013.04.044
View details for Web of Science ID 000320412200023
View details for PubMedID 23639261
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Individualized localization and cortical surface-based registration of intracranial electrodes
NEUROIMAGE
2012; 59 (4): 3563-3570
Abstract
In addition to its widespread clinical use, the intracranial electroencephalogram (iEEG) is increasingly being employed as a tool to map the neural correlates of normal cognitive function as well as for developing neuroprosthetics. Despite recent advances, and unlike other established brain-mapping modalities (e.g. functional MRI, magneto- and electroencephalography), registering the iEEG with respect to neuroanatomy in individuals-and coregistering functional results across subjects-remains a significant challenge. Here we describe a method which coregisters high-resolution preoperative MRI with postoperative computerized tomography (CT) for the purpose of individualized functional mapping of both normal and pathological (e.g., interictal discharges and seizures) brain activity. Our method accurately (within 3mm, on average) localizes electrodes with respect to an individual's neuroanatomy. Furthermore, we outline a principled procedure for either volumetric or surface-based group analyses. We demonstrate our method in five patients with medically-intractable epilepsy undergoing invasive monitoring of the seizure focus prior to its surgical removal. The straight-forward application of this procedure to all types of intracranial electrodes, robustness to deformations in both skull and brain, and the ability to compare electrode locations across groups of patients makes this procedure an important tool for basic scientists as well as clinicians.
View details for DOI 10.1016/j.neuroimage.2011.11.046
View details for Web of Science ID 000301090100052
View details for PubMedID 22155045
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Parallel versus serial processing dependencies in the perisylvian speech network: A Granger analysis of intracranial EEG data
BRAIN AND LANGUAGE
2009; 110 (1): 43-48
Abstract
In this work, we apply Granger causality analysis to high spatiotemporal resolution intracranial EEG (iEEG) data to examine how different components of the left perisylvian language network interact during spoken language perception. The specific focus is on the characterization of serial versus parallel processing dependencies in the dominant hemisphere dorsal and ventral speech processing streams. Analysis of iEEG data from a large, 64-electrode grid implanted over the left perisylvian region in a single right-handed patient showed a consistent pattern of direct posterior superior temporal gyrus influence over sites distributed over the entire ventral pathway for words, non-words, and phonetically ambiguous items that could be interpreted either as words or non-words. For the phonetically ambiguous items, this pattern was overlayed by additional dependencies involving the inferior frontal gyrus, which influenced activation measured at electrodes located in both ventral and dorsal stream speech structures. Implications of these results for understanding the functional architecture of spoken language processing and interpreting the role of the posterior superior temporal gyrus in speech perception are discussed.
View details for DOI 10.1016/j.bandl.2009.02.004
View details for Web of Science ID 000267098500006
View details for PubMedID 19356793
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Intracranial microprobe for evaluating neuro-hemodynamic coupling in unanesthetized human neocortex
JOURNAL OF NEUROSCIENCE METHODS
2009; 179 (2): 208-218
Abstract
Measurement of the blood-oxygen-level dependent (BOLD) response with fMRI has revolutionized cognitive neuroscience and is increasingly important in clinical care. The BOLD response reflects changes in deoxy-hemoglobin concentration, blood volume, and blood flow. These hemodynamic changes ultimately result from neuronal firing and synaptic activity, but the linkage between these domains is complex, poorly understood, and may differ across species, cortical areas, diseases, and cognitive states. We describe here a technique that can measure neural and hemodynamic changes simultaneously from cortical microdomains in waking humans. We utilize a "laminar optode," a linear array of microelectrodes for electrophysiological measures paired with a micro-optical device for hemodynamic measurements. Optical measurements include laser Doppler to estimate cerebral blood flow as well as point spectroscopy to estimate oxy- and deoxy-hemoglobin concentrations. The microelectrode array records local field potential gradients (PG) and multi-unit activity (MUA) at 24 locations spanning the cortical depth, permitting estimation of population trans-membrane current flows (Current Source Density, CSD) and population cell firing in each cortical lamina. Comparison of the laminar CSD/MUA profile with the origins and terminations of cortical circuits allows activity in specific neuronal circuits to be inferred and then directly compared to hemodynamics. Access is obtained in epileptic patients during diagnostic evaluation for surgical therapy. Validation tests with relatively well-understood manipulations (EKG, breath-holding, cortical electrical stimulation) demonstrate the expected responses. This device can provide a new and robust means for obtaining detailed, quantitative data for defining neurovascular coupling in awake humans.
View details for DOI 10.1016/j.jneumeth.2009.01.036
View details for Web of Science ID 000265585400008
View details for PubMedID 19428529