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Michael J. Frank

Michael J. Frank

D-Index & Metrics

Neuroscience

D-Index
103
Citations
43804
World Ranking
680
National Ranking
379

Psychology

D-Index
102
Citations
43485
World Ranking
568
National Ranking
359

Overview

Michael J. Frank is affiliated with Brown University in the United States. Their research primarily focuses on neuroscience, with a significant emphasis on cognitive neuroscience, experimental and cognitive psychology, and artificial intelligence, as well as neurology and psychiatry and mental health.

The scientist's work covers several main topics including neural and behavioral psychology studies, neural dynamics and brain function, functional brain connectivity studies, mental health research topics, EEG and brain-computer interfaces, schizophrenia research and treatment, and neurological disorders and treatments.

Michael J. Frank has published extensively in various venues. Frequent publication venues include bioRxiv (Cold Spring Harbor Laboratory), PLoS Computational Biology, Biological Psychiatry Cognitive Neuroscience and Neuroimaging, arXiv (Cornell University), and eLife.

Their recent papers include the following:

  • "Dopamine promotes cognitive effort by biasing the benefits versus costs of cognitive work" (2020, Science)
  • "Wave-like dopamine dynamics as a mechanism for spatiotemporal credit assignment" (2021, Cell)
  • "Advances in the computational understanding of mental illness" (2020, Neuropsychopharmacology)
  • "Computational Psychiatry Needs Time and Context" (2021, Annual Review of Psychology)
  • "Anxiety Impedes Adaptive Social Learning Under Uncertainty" (2020, Psychological Science)

They frequently collaborate with several coauthors, including James M. Gold, Deanna M. Barch, Angus W. MacDonald, J. Daniel Ragland, and Megan A. Boudewyn.

Best Publications

  • Frontal theta as a mechanism for cognitive control

    James F. Cavanagh;Michael J. Frank

  • By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism

    Michael J. Frank;Lauren C. Seeberger;Randall C. O'Reilly

  • Making Working Memory Work: A Computational Model of Learning in the Prefrontal Cortex and Basal Ganglia

    Randall C. O'Reilly;Michael J. Frank

  • Hold your horses: impulsivity, deep brain stimulation, and medication in parkinsonism.

    Michael J. Frank;Johan Samanta;Johan Samanta;Ahmed A. Moustafa;Scott J. Sherman

  • Triangulating a Cognitive Control Network Using Diffusion-Weighted Magnetic Resonance Imaging (MRI) and Functional MRI

    Adam R. Aron;Tim E. Behrens;Steve Smith;Michael J. Frank

  • Interactions between frontal cortex and basal ganglia in working memory: a computational model.

    Michael J. Frank;Bryan Loughry;Randall C. O’Reilly

  • HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python.

    Thomas V. Wiecki;Imri Sofer;Michael Joshua Frank

  • Computational psychiatry as a bridge from neuroscience to clinical applications

    Quentin J M Huys;Tiago V Maia;Michael J Frank

  • Dynamic Dopamine Modulation in the Basal Ganglia: A Neurocomputational Account of Cognitive Deficits in Medicated and Nonmedicated Parkinsonism

    Michael J. Frank

  • From reinforcement learning models to psychiatric and neurological disorders

    Tiago V Maia;Michael J Frank

  • Hold your horses: a dynamic computational role for the subthalamic nucleus in decision making

    Michael J. Frank

  • Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning

    Michael J. Frank;Ahmed A. Moustafa;Heather M. Haughey;Tim Curran

  • Subthalamic nucleus stimulation reverses mediofrontal influence over decision threshold

    James F Cavanagh;Thomas V Wiecki;Michael X Cohen;Michael X Cohen;Christina M Figueroa

  • Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal.

    Michael J. Frank;Eric D. Claus

  • A mechanistic account of striatal dopamine function in human cognition: psychopharmacological studies with cabergoline and haloperidol.

    Michael J. Frank;Randall C. O'Reilly

  • Prefrontal and striatal dopaminergic genes predict individual differences in exploration and exploitation

    Michael J Frank;Bradley B Doll;Jen Oas-Terpstra;Francisco Moreno

  • How much of reinforcement learning is working memory, not reinforcement learning? A behavioral, computational, and neurogenetic analysis

    Anne G. E. Collins;Michael J. Frank

  • Towards an executive without a homunculus: computational models of the prefrontal cortex/basal ganglia system

    Thomas E Hazy;Michael J Frank;Randall C O'Reilly

  • Frontal theta links prediction errors to behavioral adaptation in reinforcement learning.

    James F. Cavanagh;Michael Joshua Frank;Theresa J. Klein;John J. B. Allen

  • Error-Related Negativity Predicts Reinforcement Learning and Conflict Biases

    Michael J. Frank;Brion S. Woroch;Tim Curran

Frequent Co-Authors

James M. Gold
James M. Gold University of Maryland, Baltimore
James F. Cavanagh
James F. Cavanagh University of New Mexico
Randall C. O'Reilly
Randall C. O'Reilly University of California, Davis
Diego A. Pizzagalli
Diego A. Pizzagalli Harvard University
Ahmed A. Moustafa
Ahmed A. Moustafa Bond University
Quentin J. M. Huys
Quentin J. M. Huys University College London
Roshan Cools
Roshan Cools Radboud University
John J.B. Allen
John J.B. Allen University of Arizona
David Badre
David Badre Brown University
Michael X Cohen
Michael X Cohen Radboud University

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