Lab Overview

Welcome to the Murray Lab

Research in the lab, led by John D. Murray, focuses on investigating the dynamics and function of neural circuits, and their dysfunction in psychiatric and neurological disorders. To investigate these issues, we develop modeling, theoretical, and data-analytic approaches to systems neuroscience, in close collaboration with experimentalists. We build biophysically-based neural circuit models that span levels of scale and complexity, ranging from detailed microcircuitry supporting cognitive function, to large-scale brain dynamics. Furthermore, we leverage computational insights from models to advance the study of disorders such as schizophrenia, in a framework for Computational Psychiatry.

Lab News

  • John Murray and Alan Anticevic have edited a new book (with much gratitude to the exceptional contributors!), Computational Psychiatry: Mathematical Modeling of Mental Illness.    [Link]
  • Markus Helmer (postdoc) has been awarded a DFG Research Fellowship from the German Research Foundation. Congratulations, Markus!
  • Norman Lam (Physics PhD student) has been awarded a Graduate Scholarship from the the National Sciences and Engineering Research Council (NSERC) of Canada. Congratulations, Norman!
  • The lab has been awarded its first R01 grant from the National Institute of Mental Health.
  • Special Issue in Biological Psychiatry on "Cortical Excitation-Inhibition Balance and Dysfunction in Psychiatric Disorders" (Edited by Alan Anticevic and John Murray)    [Link] 

Upcoming Events

  • Aug 23: John will give a talk at Marine Biological Laboratory in Woods Hole, at the 30th Anniversary Symposium for the Methods in Computational Neuroscience (MCN) course. 
  • Sept 5: John will give a seminar at Columbia University in the C3N (Computational, Cognitive, and Clinical Neuroscience) seminar series. 
  • Sept 8: John will present at the Cognitive Computational Neuroscience meeting, as part of the Cross-collaboration Breakout session on "How can we bring neuroscientific insights into neural network models?".
  • Sept 12: John will give a seminar at SUNY Downstate in the Neural & Behavioral Science seminar series. 
  • Oct 11-14: John will give a talk at the 6th Workshop on Computational Properties of Prefrontal Cortex (CPPC), held at Vanderbilt University.    [LINK]
  • Nov 29: John will give a seminar at Stony Brook University in the Multi-Modal Translational Imaging Lab Seminar Series.

Principal Investigator

John D Murray, PhD

Assistant Professor of Psychiatry, of Neuroscience and of Physics

Selected recent publications
  • Murray JD, Demirtas M, Anticevic A (2018) 
    Biophysical modeling of large-scale brain dynamics and applications for computational psychiatry.
    Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 
    [DOI: 10.1016/j.bpsc.2018.07.004] 
  • Demirtas M, Burt JB, Helmer M, Ji JL, Adkinson BD, Glasser MF, Van Essen DC, Sotiropoulos S, Anticevic A, Murray JD (2018)   
    Hierarchical heterogeneity across human cortex shapes large-scale neural dynamics.    
    bioRxiv 10.1101/341966 
    [DOI: 10.1101/341966] 
  • Burt JB, Demirtas M, Eckner WJ, Navejar N, Ji JL, Martin WJ, Bernacchia A, Anticevic A, Murray JD (2018) 
    Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography.
    Nature Neuroscience 
    [DOI: 10.1038/s41593-018-0195-0] 
  • Murray JD*, Jaramillo JH*, Wang X-J (2017) (* denotes equal contribution)   
    Working memory and decision making in a fronto-parietal circuit model.
    Journal of Neuroscience 37:12167 
    [DOI: 10.1523/JNEUROSCI.0343-17.2017] 
  • Lam NH, Borduqui T, Hallak J, Roque AC, Anticevic A, Krystal JH, Wang X-J, Murray JD (2017)  
    Effects of altered excitation-inhibition balance on decision making in a cortical circuit model.
    bioRxiv 10.1101/100347 
    [DOI: 10.1101/100347] 
  • Murray JD, Bernacchia A, Roy NA, Constantinidis C, Romo R, Wang X-J (2017)  
    Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex. 
    Proceedings of the National Academy of Sciences 114:394 
    [DOI: 10.1073/pnas.1619449114]