Kaustubh R. Kulkarni, MD, PhD
he/him/his
Psychiatry ResidentCards
About
Research
Publications
Featured Publications
A computational mechanism linking momentary craving and decision-making in alcohol drinkers and cannabis users
Kulkarni KR, Berner LA, Rhoads SA, Fiore VG, Schiller D, Gu X. A computational mechanism linking momentary craving and decision-making in alcohol drinkers and cannabis users. Nature Mental Health 2026 DOI: 10.1038/s44220-026-00593-w.Peer-Reviewed Original ResearchLonging to act: Bayesian inference as a framework for craving in behavioral addiction
Kulkarni K, O'Brien M, Gu X. Longing to act: Bayesian inference as a framework for craving in behavioral addiction. Addictive Behaviors 2023, 144: 107752. PMID: 37201396, PMCID: PMC10330403, DOI: 10.1016/j.addbeh.2023.107752.Peer-Reviewed Original ResearchConceptsBehavioral addictionsDrug addictionAddictive disordersSubstance use disordersBayesian brain hypothesisDrug-induced effectsInteroceptive inferenceUse disorderDrug dependenceCravingSensory evidenceBrain hypothesisAddictionAction completionDisordersComputational theoryEffective treatmentEmpirical findingsBeliefsDrugHypothesisTherapeutic implicationsFindingsEvidenceEmpirical studiesAn Interpretable and Predictive Connectivity-Based Neural Signature for Chronic Cannabis Use
Kulkarni K, Schafer M, Berner L, Fiore V, Heflin M, Hutchison K, Calhoun V, Filbey F, Pandey G, Schiller D, Gu X. An Interpretable and Predictive Connectivity-Based Neural Signature for Chronic Cannabis Use. Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2022, 8: 320-330. PMID: 35659965, PMCID: PMC9708942, DOI: 10.1016/j.bpsc.2022.04.009.Peer-Reviewed Original ResearchConceptsPredictive networkDifferent classification modelsMachine learningClassification modelUser groupsDecoding modelUsersNetwork analysisChronic cannabis usersSuccessful classificationCannabis useInterpretable biomarkersNetworkHigh accuracyNovel approachHealthy control subjectsWhole-brain functional connectivityCannabis usersChronic cannabis useConnectivityFunctional magnetic resonance imagingMagnetic resonance imagingPredictive regionsFunctional magnetic resonanceLinear machine
2026
Sustained Activity of Human Substantia Nigra Neurons Reflect Prior Rewards
Imtiaz Z, Kato A, Kopell B, Qasim S, Davis A, Martinez L, Heflin M, Kulkarni K, Morsi A, Charney A, Gu X, Saez I. Sustained Activity of Human Substantia Nigra Neurons Reflect Prior Rewards. IScience 2026, 115458. DOI: 10.1016/j.isci.2026.115458.Peer-Reviewed Original ResearchReward expectationReward historyFiring rateSubstantia nigraDA neuronal activityReaction timeMotivational vigorHuman substantia nigra neuronsReward processingSingle-unit recordingsResponse vigorDopaminergic activityDopaminergic systemDA neuronsSubstantia nigra neuronsRewardNeuronal activityParkinson's patientsHigher firing ratesDopamineMotor controlPositive outcomesSustained activationTrial outcomesNeural signals
2025
Spatial Craving Patterns in Marijuana Users: Insights From fMRI Brain Connectivity Analysis With High-Order Graph Attention Neural Networks
Ding J, Yang S, Zilverstand A, Kulkarni K, Gu X, Liu F. Spatial Craving Patterns in Marijuana Users: Insights From fMRI Brain Connectivity Analysis With High-Order Graph Attention Neural Networks. IEEE Journal Of Biomedical And Health Informatics 2025, 29: 358-370. PMID: 39321007, PMCID: PMC11875913, DOI: 10.1109/jbhi.2024.3462371.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingGraph attention neural networkAttention-based long short-term memoryFunctional brain networksLong short-term memoryAttention neural networkBrain networksShort-term memoryNeighboring nodesInformation fusionBenchmark algorithmsIntrinsic functional brain networksClassification accuracyNeural networkMarijuana usersNetwork communitiesChronic marijuana usersSuperior performanceNetwork dynamicsNetworkCraving patternsNetwork community analysisFrontoparietal networkConsumption of marijuanaDorsal attention
2023
Neural patterns differentiate traumatic from sad autobiographical memories in PTSD
Perl O, Duek O, Kulkarni K, Gordon C, Krystal J, Levy I, Harpaz-Rotem I, Schiller D. Neural patterns differentiate traumatic from sad autobiographical memories in PTSD. Nature Neuroscience 2023, 26: 2226-2236. PMID: 38036701, DOI: 10.1038/s41593-023-01483-5.Peer-Reviewed Original ResearchConceptsPost-traumatic stress disorderTraumatic memoriesAutobiographical memoryNeural patternsIntersubject representational similarity analysisSimilar neural representationsRepresentational similarity analysisPosterior cingulate cortexTrauma memoriesMnemonic featuresNegative memoriesMultivoxel patternsNeural representationCognitive stateHippocampal representationsCognitive entitiesStress disorderCingulate cortexNeural activityTraumatic narrativesIndividual symptom severitySemantic representationMemory typesOwn memoryMemory
2022
P9. Computational Mechanisms Underlying Drug-Based Decision Making and Momentary Craving in Chronic Cannabis Users
Kulkarni K, Fiore V, Schiller D, Gu X. P9. Computational Mechanisms Underlying Drug-Based Decision Making and Momentary Craving in Chronic Cannabis Users. Biological Psychiatry 2022, 91: s91. DOI: 10.1016/j.biopsych.2022.02.244.Peer-Reviewed Original Research
2021
Emotional adaptation during a crisis: decline in anxiety and depression after the initial weeks of COVID-19 in the United States
Shuster A, O’Brien M, Luo Y, Berner L, Perl O, Heflin M, Kulkarni K, Chung D, Na S, Fiore V, Gu X. Emotional adaptation during a crisis: decline in anxiety and depression after the initial weeks of COVID-19 in the United States. Translational Psychiatry 2021, 11: 435. PMID: 34417441, PMCID: PMC8377451, DOI: 10.1038/s41398-021-01552-y.Peer-Reviewed Original ResearchConceptsLevels of depressionEmotional adaptationDecreased levels of depressionState-Trait Anxiety InventoryScale and State-Trait Anxiety InventoryAssociated with anxietyHigher overall levelsPsychiatric diagnosisState subscaleExacerbate depressionAnxiety InventoryMeasure depressionAnxietyDepressionAnxiety levelsOnline studyLinear mixed-effects modelsLongitudinal changesMixed-effects modelsSocial media useUnder-investigatedOverall levelContainment of COVID-19: Simulating the impact of different policies and testing capacities for contact tracing, testing, and isolation
Fiore V, DeFelice N, Glicksberg B, Perl O, Shuster A, Kulkarni K, O’Brien M, Pisauro M, Chung D, Gu X. Containment of COVID-19: Simulating the impact of different policies and testing capacities for contact tracing, testing, and isolation. PLOS ONE 2021, 16: e0247614. PMID: 33788852, PMCID: PMC8011755, DOI: 10.1371/journal.pone.0247614.Peer-Reviewed Original Research
2020
A Whole-Brain and Cross-Diagnostic Perspective on Functional Brain Network Dysfunction
Spronk M, Keane BP, Ito T, Kulkarni K, Ji JL, Anticevic A, Cole MW. A Whole-Brain and Cross-Diagnostic Perspective on Functional Brain Network Dysfunction. Cerebral Cortex 2020, 31: 547-561. PMID: 32909037, PMCID: PMC7947178, DOI: 10.1093/cercor/bhaa242.Peer-Reviewed Original ResearchConceptsAttention deficit hyperactivity disorderFunctional brain network changesAutism spectrum disorderNetwork organizationFunctional network organizationBrain network organizationBrain network dysfunctionWhole-brain perspectiveBrain network changesMental illnessMental disordersNetwork alterationsNeurocognitive theoriesBrain systemsCognitive changesHyperactivity disorderSpectrum disorderFunctional connectomeFunctional network alterationsGroup of individualsNetwork dysfunctionMental diseasesDisordersNetwork changesWhole brain