John D Murray, PhD
Associate Professor Adjunct of PsychiatryDownloadHi-Res Photo
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Psychiatry
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Associate Professor Adjunct of Psychiatry
Biography
John D. Murray is the Gregg L. Engles Associate Professor of Psychological and Brain Sciences at Dartmouth College. Dr. Murray completed a PhD in Physics from Yale University, followed by postdoctoral research at New York University in the Center for Neural Science. He was primary faculty in the Department of Psychiatry at Yale School of Medicine from 2015 to 2023, with secondary appointments in Physics and Neuroscience. His research is in the areas of computational neuroscience and computational psychiatry.
Appointments
Psychiatry
Associate Professor AdjunctPrimary
Other Departments & Organizations
Education & Training
- PhD
- Yale University, Physics (2013)
- BS
- Yale University, Physics and Mathematics (2006)
Research
Overview
Medical Research Interests
Cognition; Computational Biology; Computer Simulation; Decision Making; Functional Neuroimaging; Interneurons; Memory, Short-Term; Prefrontal Cortex; Schizophrenia
ORCID
0000-0003-4115-8181- View Lab Website
Murray Lab
Research at a Glance
Yale Co-Authors
Frequent collaborators of John D Murray's published research.
Publications Timeline
A big-picture view of John D Murray's research output by year.
Research Interests
Research topics John D Murray is interested in exploring.
John Krystal, MD
Brendan Adkinson
Clara Fonteneau, PhD
David Glahn, PhD
Amber Howell
Dustin Scheinost, PhD, BS
24Publications
1,234Citations
Decision Making
Cognition
Memory, Short-Term
Prefrontal Cortex
Computer Simulation
Schizophrenia
Publications
Featured Publications
Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography
Burt JB, Demirtaş M, Eckner WJ, Navejar NM, Ji JL, Martin WJ, Bernacchia A, Anticevic A, Murray JD. Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography. Nature Neuroscience 2018, 21: 1251-1259. PMID: 30082915, PMCID: PMC6119093, DOI: 10.1038/s41593-018-0195-0.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsHierarchical Heterogeneity across Human Cortex Shapes Large-Scale Neural Dynamics
Demirtaş M, Burt JB, Helmer M, Ji JL, Adkinson BD, Glasser MF, Van Essen DC, Sotiropoulos SN, Anticevic A, Murray JD. Hierarchical Heterogeneity across Human Cortex Shapes Large-Scale Neural Dynamics. Neuron 2019, 101: 1181-1194.e13. PMID: 30744986, PMCID: PMC6447428, DOI: 10.1016/j.neuron.2019.01.017.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsResting-state functional connectivityHigh-frequency spectral powerMagnetic resonance imagingLocal synaptic strengthsResting-state magnetoencephalographyCircuit-level mechanismsMicrocircuit propertiesHuman cortical dynamicsCortical areasLocal circuitsResonance imagingSynaptic strengthHuman cortexFunctional MRIFunctional connectivityCortical organizationHierarchical specializationLarge-scale neural dynamicsNeural activityFMRI featuresCortexCortical dynamicsLocal propertiesSpectral powerIntrinsic local propertiesGenerative modeling of brain maps with spatial autocorrelation
Burt JB, Helmer M, Shinn M, Anticevic A, Murray JD. Generative modeling of brain maps with spatial autocorrelation. NeuroImage 2020, 220: 117038. PMID: 32585343, DOI: 10.1016/j.neuroimage.2020.117038.Peer-Reviewed Original ResearchCitationsAltmetricA flexible framework for simulating and fitting generalized drift-diffusion models
Shinn M, Lam NH, Murray JD. A flexible framework for simulating and fitting generalized drift-diffusion models. ELife 2020, 9: e56938. PMID: 32749218, PMCID: PMC7462609, DOI: 10.7554/elife.56938.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsDrift-diffusion modelArbitrary user-defined functionsImportant decision-making modelFokker-Planck equationEfficient numerical methodDecision-making mechanismUser-defined functionsDrift diffusion model frameworkFlexible frameworkSoftware packageGDDMHuman datasetsNumerical methodDecision-making modelResponse time distributionsDecision-making taskLatest methodologiesModel formGood accuracyFrameworkMaximum likelihoodModel innovationTime distributionDDM parametersModel frameworkConfluence of Timing and Reward Biases in Perceptual Decision-Making Dynamics
Shinn M, Ehrlich D, Lee D, Murray JD, Seo H. Confluence of Timing and Reward Biases in Perceptual Decision-Making Dynamics. Journal Of Neuroscience 2020, 40: 7326-7342. PMID: 32839233, PMCID: PMC7534922, DOI: 10.1523/jneurosci.0544-20.2020.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsDecision-making taskReward biasesDecision-making strategiesPerceptual decision-making taskNovel decision-making taskGeneralized drift-diffusion modelsResponse time patternsTiming mechanismTemporal structureCognitive mechanismsSensory evidenceDecision-making dynamicsUrgency signalAsymmetric rewardsNeural mechanismsStimulus timingDrift-diffusion modelTemporal contextLeaky integrationRewardReward structureTemporal uncertaintyEvidence reliabilityEveryday lifeSuch regularitiesA circuit mechanism for decision-making biases and NMDA receptor hypofunction
Cavanagh SE, Lam NH, Murray JD, Hunt LT, Kennerley SW. A circuit mechanism for decision-making biases and NMDA receptor hypofunction. ELife 2020, 9: e53664. PMID: 32988455, PMCID: PMC7524553, DOI: 10.7554/elife.53664.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsNMDA-R hypofunctionCortical excitation/inhibition balanceExcitation/inhibition balanceNMDA receptor hypofunctionNMDA receptor antagonismNMDA-R antagonist ketamineCircuit-level mechanismsPotential neural mechanismsNeuropsychiatric symptomsReceptor hypofunctionReceptor antagonismInhibition balanceExcitatory neuronsInhibitory neuronsPharmacological modelPharmacological manipulationNeuropsychiatric disordersCircuit mechanismsHypofunctionVariable evidenceNeural mechanismsKetamineNeuronsBehavioral psychophysicsPossible effectsPsychRNN: An Accessible and Flexible Python Package for Training Recurrent Neural Network Models on Cognitive Tasks
Ehrlich DB, Stone JT, Brandfonbrener D, Atanasov A, Murray JD. PsychRNN: An Accessible and Flexible Python Package for Training Recurrent Neural Network Models on Cognitive Tasks. ENeuro 2020, 8: eneuro.0427-20.2020. PMID: 33328247, PMCID: PMC7814477, DOI: 10.1523/eneuro.0427-20.2020.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsRecurrent neural networkCognitive tasksCognitive neurosciencePython packageTraining of animalsTraining recurrent neural networksNetwork modelArtificial recurrent neural networkDeep learning softwareDeep-learning methodsRecurrent neural network modelNeural network modelNeural representationCognitive computationsNeuroscience researchNeural networkRNN modelCurriculum learningNeuroscienceCircuit mechanismsAdditional customizationConnectivity patternsTaskSoftware packageComputational modeling frameworkTranscriptomics-informed large-scale cortical model captures topography of pharmacological neuroimaging effects of LSD
Burt JB, Preller KH, Demirtas M, Ji JL, Krystal JH, Vollenweider FX, Anticevic A, Murray JD. Transcriptomics-informed large-scale cortical model captures topography of pharmacological neuroimaging effects of LSD. ELife 2021, 10: e69320. PMID: 34313217, PMCID: PMC8315798, DOI: 10.7554/elife.69320.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsLysergic acid diethylamideEffects of LSDSerotonin 2A receptorPharmacological neuroimagingNeuromodulatory effectsPharmacological responseFunctional alterationsBrain physiologyCircuit mechanismsFunctional connectivityNeural functionBrain structuresPsychoactive drugsAcid diethylamideFunctional topographyPrecision medicineNeural differencesNeuroimagingAltered statesReceptorsTrial-to-Trial Variability of Spiking Delay Activity in Prefrontal Cortex Constrains Burst-Coding Models of Working Memory
Li D, Constantinidis C, Murray JD. Trial-to-Trial Variability of Spiking Delay Activity in Prefrontal Cortex Constrains Burst-Coding Models of Working Memory. Journal Of Neuroscience 2021, 41: 8928-8945. PMID: 34551937, PMCID: PMC8549532, DOI: 10.1523/jneurosci.0167-21.2021.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsEffects of Altered Excitation-Inhibition Balance on Decision Making in a Cortical Circuit Model
Lam NH, Borduqui T, Hallak J, Roque A, Anticevic A, Krystal JH, Wang XJ, Murray JD. Effects of Altered Excitation-Inhibition Balance on Decision Making in a Cortical Circuit Model. Journal Of Neuroscience 2021, 42: 1035-1053. PMID: 34887320, PMCID: PMC8824494, DOI: 10.1523/jneurosci.1371-20.2021.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsCortical circuitsCognitive deficitsCortical circuit modelAltered excitation-inhibition balanceExcitatory pyramidal neuronsNMDA receptor hypofunctionCerebral cortical circuitsExcitation-inhibition balancePyramidal neuronsReceptor hypofunctionDistinct time coursesSynaptic excitationInhibitory interneuronsMultiple neuropsychiatric disordersBehavioral deficitsSynaptic balanceSynaptic levelLatest evidenceNeuropsychiatric disordersCognitive functionCircuit mechanismsBehavioral effectsPsychometric performanceBehavioral levelTask paradigm
News & Links
News
- January 10, 2022Source: Nature Communications
Transient Neuronal Suppression for Exploitation of New Sensory Evidence
- August 06, 2021Source: YaleNews
New Model Helps Map the Individual Variations of Mental Illness
- February 11, 2019
Local variations in circuitry are key to brain’s power
- August 08, 2018
Marriage of imaging and genetics opens new view of brain function
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