Patrick Lee Purdon
Professor of Anesthesiology, Perioperative and Pain Medicine (Department Research) and, by courtesy, of Bioengineering
Bio
My research integrates neuroimaging, biomedical signal processing, and the systems neuroscience of general anesthesia and sedation.
My group conducts human studies of anesthesia-induced unconsciousness, using a variety of techniques including multimodal neuroimaging, high-density EEG, and invasive neurophysiological recordings used to diagnose medically refractory epilepsy. We also develop novel methods in neuroimaging and biomedical signal processing to support these studies, as well as methods for monitoring level of consciousness under general anesthesia using EEG.
Academic Appointments
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Professor, Anesthesiology, Perioperative and Pain Medicine
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Professor (By courtesy), Bioengineering
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Member, Wu Tsai Neurosciences Institute
Administrative Appointments
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Thesis Committee, M.D. Honors Thesis Committee for Katie Hartnack, Antioch University New England, Keene, NH (2018 - Present)
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Honors Thesis Committee (M.D. Honors Thesis Committee for Alexis Roy), Harvard Medical School (2017 - Present)
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Thesis Committee (Ph.D Thesis Committee for Britni Crocker, Medical Engineering and Medical Physics), Harvard-MIT Division of Health Sciences and Technology (2016 - 2018)
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Thesis Committee (Ph.D Thesis Committee for Koeun Lim, Speech and Hearing Bioscience and Technology), Harvard-MIT Division of Health Sciences and Technology (2014 - 2017)
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Thesis Committee (Ph.D. Thesis Committee for Mohammad Ghassemi, M.S.), Massachusetts Institute of Technology (2013 - 2014)
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Research Council, Massachusetts General Hospital (2019 - 2020)
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Research Council, Massachusetts General Hospital (2014 - 2015)
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Research Council, Massachusetts General Hospital, Boston, MA (2010 - 2011)
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Research Task Force, Massachusetts General Hospital, Boston, MA (2010 - 2010)
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Admissions Committee, Harvard-MIT Division of Health Sciences and Technology (2002 - 2003)
Honors & Awards
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Faculty Fellow, Stanford Biodesign (2023-2024)
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Invited Author and Participant, Ernst Strungmann Forum, Manifestations and Mechanisms of Dynamic Brain Coordination over Development (2017)
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Nathanial M. Sims Endowed Chair in Anesthesia Innovation and Bioengineering, Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital (2017)
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Winner, Art of Talking Science competition, Massachusetts General Hospital Research Institute (2016)
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Nathanial M. Sims Endowed Scholar in Anesthesia Innovation and Bioengineering, Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital (2016)
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Election to Association of University Anesthesiologists, Association of University Anesthesiologists (AUA) (2015)
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Best of Meeting Award Nominee, International Anesthesia Research Society (2015)
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Best in Neuroscience Award, Society for Neuroscience in Anesthesiology and Critical Care (2015)
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Election to College of Fellows, American Institute for Medical and Biological Engineering (AIMBE) (2015)
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Innovation Development Grant Award, Partners Innovation, Partners Healthcare (2014)
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Best Abstract, Clinical Sciences, Annual Meeting of the American Society of Anesthesiologists (2013)
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Honorable Mention, MGH Martin Prize, Massachusetts General Hospital (2013)
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DACCPM Clinical Research Day Award, Staff Category, Department of Anesthesia and Critical Care, Massachusetts General Hospital (2011)
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Citizenship Award, Department of Anesthesia and Critical Care, Department of Anesthesia and Critical Care, Massachusetts General Hospital (2009)
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National Institutes of Health Director’s New Innovator Award, National Institutes of Health (2009)
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Individual Award, Massachusetts General Hospital Clinical Research Day, Massachusetts General Hospital (2008)
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Best in Section poster prize (among Neuroanesthesia posters), Annual Meeting of the International Anesthesia Research Society (2008)
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Best Young Investigator, 7th International Symposium for Memory and Awareness in Anesthesia (2008)
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NIH/NIBIB Neuroimaging Training Program Fellowship, Harvard-MIT Division of Health Sciences and Technology (2005)
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Allan and Luanne Reed Scholarship, Harvard-MIT Division of Health Sciences and Technology (2000 - 2005)
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Whittaker Foundation Predoctoral Fellowship in Biomedical Engineering, Whitaker Foundation (1996 - 2001)
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Phi Beta Kappa Honor Society, Harvard College (1995)
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John Harvard Honorary Scholarship, Harvard College (1993 - 1995)
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Detur Prize Book, Harvard College (1993)
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Harvard National Scholar, Harvard College (1992 - 1996)
Boards, Advisory Committees, Professional Organizations
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Grant Reviewer - NPAS Study Section, Temporary Member (Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section), NIH/CSR (2022 - 2022)
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Ad hoc Reviewer, PLoS Computational Biology (2021 - Present)
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Ad hoc Reviewer, New England Journal of Medicine (2019 - Present)
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Research Council, Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA (2-year term, elected by peers) (2019 - 2020)
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Ad hoc Reviewer, Nature Communications (2018 - Present)
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Co-Founder, Director, PASCALL Systems, Inc. (2018 - Present)
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Grant Reviewer - ZRG1 SBIB-Z (02) M, BTSS and SAT member conflict review panel, NIH/CSR (2018 - 2018)
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Thesis Committee, M.D. Honors Thesis Committee for Katie Hartnack, Antioch University New England, Keene, NH (2018 - 2018)
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Honors Thesis Committee, M.D. Honors Thesis Committee for Alexis Roy, Harvard Medical School (2017 - 2017)
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Ad hoc Reviewer, Proceedings of the National Academy of Sciences (2016 - Present)
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Ad hoc Reviewer, Frontiers in Neural Circuits (2016 - Present)
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Thesis Committee, Ph.D. Thesis Committee for Britni Crocker, Medical Engineering and Medical Physics Program, Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology (2016 - 2018)
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Ad hoc Reviewer, British Journal of Anesthesia (2015 - Present)
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Ad hoc Reviewer, Journal of Neural Engineering (2015 - Present)
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Ad hoc Reviewer, Physiological Measurement (2015 - Present)
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College of Fellows, American Institute for Medical and Biological Engineering (2015 - Present)
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Member, Association of University Anesthesiologists (2015 - Present)
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Member, Society for Neuroscience in Anesthesiology and Critical Care (2015 - Present)
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Associate Editor, IEEE Neural Engineering Conference (2015 - 2015)
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Grant Reviewer - NIH Director’s Early Independence Award Review Panel, NIH/CSR (2015 - 2015)
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Ad hoc Reviewer, Anesthesiology (2014 - Present)
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Ad hoc Reviewer, Cerebral Cortex (2014 - Present)
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Thesis Committee, Ph.D. Thesis Committee for Koeun Lim, Speech and Hearing Bioscience and Technology Program, Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology (2014 - 2017)
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Research Council, Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA (2-year term, elected by peers) (2014 - 2016)
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Ad hoc Reviewer, Anesthesia and Analgesia (2013 - Present)
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Member, International Anesthesia Research Society (2013 - Present)
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Member, American Society of Anesthesiologists (2013 - Present)
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Thesis Committee, Ph.D. Thesis Committee for Mohammad Ghassemi, M.S., Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA (2013 - 2014)
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Associate Editor, IEEE Neural Engineering Conference (2013 - 2013)
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Grant Reviewer - Collaborative Research in Computational Neuroscience Study Section, NSF/NIH (2013 - 2013)
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Grant Reviewer - NIH Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Working Group Advisory Committee to the Director, NIH (2013 - 2013)
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Grant Reviewer - NINDS Board of Scientific Counselors Ad Hoc Member, NIH/NINDS (2013 - 2013)
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Grant Reviewer - Special Emphasis Review Panel ZGM1 PPBC-Y, NIH/NIGMS (2013 - 2013)
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Ad hoc Reviewer, Journal of Computational Neuroscience (2012 - Present)
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Ad hoc Reviewer, IEEE Trans. Neural Sys. & Rehab. Engineering (2012 - Present)
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Guest Editor, PLoS Computational Biology (2012 - 2012)
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Research Council, Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA (2-year term, elected by peers) (2010 - 2012)
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Research Task Force, Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA (2010 - 2010)
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Ad hoc Reviewer, Biological Cybernetics (2009 - Present)
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Member, Organization for Human Brain Mapping (2009 - 2010)
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Member, Institute of Electrical and Electronics Engineers (IEEE) (2008 - Present)
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Member, International Anesthesia Research Society (2007 - 2008)
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Ad hoc Reviewer, Statistics in Medicine (2006 - Present)
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Member, Society for Neuroscience (2005 - Present)
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Admissions Committee, Harvard-MIT Division of Health Sciences and Technology (2002 - 2003)
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Ad hoc Reviewer, Neuroimage (2001 - Present)
Professional Education
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Ph.D., Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology, Cambridge, MA, Biomedical Engineering (2005)
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S.M., Massachusetts Institute of Technology, Cambridge, MA, Electrical Engineering and Computer Science (1998)
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A.B., Harvard College, Cambridge, MA., Engineering Sciences, summa cum laude (1996)
Patents
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Patrick Purdon. "United StatesApparatuses and Methods For Electrophysiological Signal Delivery and Recording During MRI"
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Purdon PL, Soulat H, Beck AM, Stephen EP. "United StatesSystem and method for monitoring neural signals", Jul 16, 2019
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Brown EN, Van Dort CJ, Akeju O, Purdon PL. "United States Patent MGH 22571.02 Systems and Methods for Administering, Monitoring and Controlling Biomimetic Sleep", Aug 24, 2015
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Purdon PL, Akeju O, Brown EN. "United States Patent MGH 23036 A System and Method for Predicting Arousal to Consciousness During General Anesthesia and Sedation", Aug 24, 2015
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Purdon PL, Brown EN. "United States Patent MGH 23707.02 A System and Method for Discovery and Characterization of Neuroactive Drugs", Aug 24, 2015
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Purdon PL, Mukamel EA, Brown EN. "United States Patent MGH 22628.01 System and Method for Characterizing Brain States During General Anesthesia and Sedation Using Phase-Amplitude Modulation", Jan 14, 2015
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Purdon PL, Brown EN, Akeju O. "United States Patent MGH 22205.10 Systems and Methods for Improved Brain Monitoring During General Anesthesia and Sedation", Sep 13, 2014
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Purdon PL, Brown EN, Lewis LD, Westover MB. "United States Patent MGH 22295 System and Method to Infer Brain State During Burst Suppression", Jun 28, 2014
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Prerau MJ, Purdon PL. "United States Patent MGH 22302.03 A Method for Tracking Non-Stationary Spectral Peak Structure in EEG Data", Jun 25, 2014
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Prerau MJ, Purdon PL. "United States Patent MGH 22687 A Method for Quantifying the Sleep Onset Process using Combined Behavioral and Physiological Measures", Jun 25, 2014
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Purdon PL, Brown EN, Akeju O, Prerau MJ. "United States Patent MGH 22205.04 System and Method for Monitoring Level of Dexmedetomidine-Induced Sedation", Apr 24, 2014
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Brown EN, Ba D, Babadi B, Purdon PL. "United States Patent MGH 22205.13 System and Method for Estimating High Time-Frequency Resolution EEG Spectrograms to Monitor Patient State", Apr 24, 2014
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Purdon PL, Brown EN, Akeju O, Lewis LD. "United States Patent MGH 22205.01 System and Method for Monitoring Anesthesia and Sedation Using Measures of Brain Coherence and Synchrony", Apr 23, 2014
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Patrick L. Purdon, Emery N. Brown, ShiNung Ching, David A. Boas, Maria Angela Franceschini, Jason Sutin. "United States Patent MGH 22205.02 Monitoring Brain Metabolism and Activity Using Elecetroencephalogram and Optical Imaging", Apr 23, 2014
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Krishnaswamy P, Bonmassar G, Purdon PL, Brown EN. "United States Patent MGH 22191 A System and Method for Removing Artifacts from Electrophysiologic Information Acquired in the Magnetic Resonance Imaging Scanner", Apr 10, 2014
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Brown EN, Purdon PL, Ching S, Chemali J. "United States Patent MGH 21412 System and Method for Monitoring and Controlling a State of a Patient During and After Administration of Anesthetic Compound", Oct 14, 2013
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Brown EN, Purdon PL, Prerau MJ, Mukamel EA, Cimenser A. "United States Patent MGH 21181 System and Method for Tracking Brain States During Administration of Anesthesia", May 7, 2012
Projects
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Developing novel technologies to monitor nociception and opioid administration during surgery and general anesthesia in order to minimize post-operative opioid requirements, PASCALL Systems, Inc (9/2020 - 6/2025)
The major goal of this “Fast Track” STTR project is to develop novel technologies to monitor opioid administration during general anesthesia.
Location
300 Pasteur Drive, Stanford, CA
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Characterizing brain dynamic biomarkers of fentanyl using intracranial and high-density electroencephalogram in humans (8/2022 - 5/2027)
The major goal of this project is to characterize brain dynamic biomarkers of fentanyl using intracranial and high-density electroencephalogram in humans.
Location
300 Pasteur Drive, Stanford, CA
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Characterizing sleep brain dynamics associated with Alzheimer’s disease pathology and progression in humans using EEG source localization and PET (12/2022 - 11/2027)
The major goal of this project is to characterize sleep brain dynamics during Alzheimer’s disease progression.
Location
300 Pasteur Drive, Stanford, CA
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Developing active stimulation and monitoring technologies to optimize pain and nociception management during regional anesthesia, general anesthesia, and post-operative care (10/2023 - 9/2026)
Location
300 Pasteur Drive, Stanford, CA
Collaborators
- Tuan Le Mau, MPI, PASCALL Systems, Inc.
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Advanced signal processing methods for neural data analysis to support development of brain dynamic biomarkers for research and clinical applications in patients with Alzheimer's and related dementias (7/2023 - 6/2028)
Location
300 Pasteur Drive, Stanford, CA
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Developing a novel system combining cognitive assessment with PASCALL FDA-cleared intraoperative anesthesia EEG brain monitor to prevent postoperative neurocognitive disorders in aging patients (10/2023 - 8/2026)
Location
300 Pasteur Drive, Stanford, CA
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Joanna Sands -
Postdoctoral Faculty Sponsor
Proloy Das, Mingjian He, Ran Liu, Scott Oshiro
All Publications
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Anesthesia-induced Brain Oscillations and Vulnerability to Postoperative Neurocognitive Disorders.
Anesthesiology
2023; 139 (5): 557-559
View details for DOI 10.1097/ALN.0000000000004704
View details for PubMedID 37815470
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Switching state-space modeling of neural signal dynamics.
PLoS computational biology
2023; 19 (8): e1011395
Abstract
Linear parametric state-space models are a ubiquitous tool for analyzing neural time series data, providing a way to characterize the underlying brain dynamics with much greater statistical efficiency than non-parametric data analysis approaches. However, neural time series data are frequently time-varying, exhibiting rapid changes in dynamics, with transient activity that is often the key feature of interest in the data. Stationary methods can be adapted to time-varying scenarios by employing fixed-duration windows under an assumption of quasi-stationarity. But time-varying dynamics can be explicitly modeled by switching state-space models, i.e., by using a pool of state-space models with different dynamics selected by a probabilistic switching process. Unfortunately, exact solutions for state inference and parameter learning with switching state-space models are intractable. Here we revisit a switching state-space model inference approach first proposed by Ghahramani and Hinton. We provide explicit derivations for solving the inference problem iteratively after applying a variational approximation on the joint posterior of the hidden states and the switching process. We introduce a novel initialization procedure using an efficient leave-one-out strategy to compare among candidate models, which significantly improves performance compared to the existing method that relies on deterministic annealing. We then utilize this state inference solution within a generalized expectation-maximization algorithm to estimate model parameters of the switching process and the linear state-space models with dynamics potentially shared among candidate models. We perform extensive simulations under different settings to benchmark performance against existing switching inference methods and further validate the robustness of our switching inference solution outside the generative switching model class. Finally, we demonstrate the utility of our method for sleep spindle detection in real recordings, showing how switching state-space models can be used to detect and extract transient spindles from human sleep electroencephalograms in an unsupervised manner.
View details for DOI 10.1371/journal.pcbi.1011395
View details for PubMedID 37639391
View details for PubMedCentralID PMC10491408