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Michael J. Frank

Active 1985–2026

163
Papers
32,581
Citations
93
h-index
143
i10-index

Citations

Citations per year for Michael J. Frank1920: 3 citations1944: 1 citations1979: 1 citations1980: 1 citations1982: 2 citations1989: 2 citations1996: 1 citations1998: 2 citations1999: 2 citations2001: 5 citations2002: 9 citations2003: 21 citations2004: 14 citations2005: 52 citations2006: 80 citations2007: 157 citations2008: 258 citations2009: 298 citations2010: 365 citations2011: 437 citations2012: 440 citations2013: 482 citations2014: 510 citations2015: 501 citations2016: 539 citations2017: 554 citations2018: 477 citations2019: 1,071 citations2020: 1,267 citations2021: 1,169 citations2022: 845 citations2023: 711 citations2024: 1,007 citations2025: 530 citations2026: 58 citations1921–1943: no citations, so these years are not shown1945–1978: no citations, so these years are not shown1981: no citations, so this year is not shown1983–1988: no citations, so these years are not shown1990–1995: no citations, so these years are not shown1997: no citations, so this year is not shown2000: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 3,607 citing papers, 30.8% of this breakdownUnited Kingdom: 1,317 citing papers, 11.2% of this breakdownGermany: 1,103 citing papers, 9.4% of this breakdownNetherlands: 602 citing papers, 5.1% of this breakdownChina: 539 citing papers, 4.6% of this breakdownCanada: 506 citing papers, 4.3% of this breakdownFrance: 438 citing papers, 3.7% of this breakdownItaly: 398 citing papers, 3.4% of this breakdownAustralia: 367 citing papers, 3.1% of this breakdownSwitzerland: 327 citing papers, 2.8% of this breakdownJapan: 227 citing papers, 2% of this breakdownSpain: 211 citing papers, 1.8% of this breakdown
0%30.8%Other 17.8%

Institutions

Fields

  • Neuroscience57.2%
  • Medicine18.6%
  • Psychology12.6%
  • Computer Science3.6%
  • Biochemistry, Genetics and Molecular Biology2.1%
  • Decision Sciences1.7%
  • Other4.2%

Topics

  • Neural and Behavioral Psychology Studies12.9%
  • Neural dynamics and brain function9.3%
  • Functional Brain Connectivity Studies7.1%
  • EEG and Brain-Computer Interfaces4.7%
  • Memory and Neural Mechanisms3.8%
  • Neurotransmitter Receptor Influence on Behavior3.6%
  • Other58.6%

Coauthors

All papers

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  1. Frontal theta as a mechanism for cognitive control

    Authors: James F. Cavanagh, Michael J. Frank - Trends in Cognitive Sciences 2014 cited by 2,752

  2. Computational psychiatry as a bridge from neuroscience to clinical applications

    Authors: Quentin J. M. Huys, Tiago V. Maia, Michael J. Frank - Nature Neuroscience 2016 cited by 1,077

  3. Motor symptoms in Parkinson’s disease: A unified framework

    Authors: Ahmed A. Moustafa, V. Srinivasa Chakravarthy, Joseph R. Phillips, Ankur Gupta, Szabolcs Kéri, Bertalan Polner, Michael J. Frank, Marjan Jahanshahi - Neuroscience & Biobehavioral Reviews 2016 cited by 474

  4. By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism

    Authors: Michael J. Frank, Lauren Seeberger, Randall C. O’Reilly - Science 2004 cited by 2,055

  5. Wave-like dopamine dynamics as a mechanism for spatiotemporal credit assignment

    Authors: Arif Hamid, Michael J. Frank, Christopher I. Moore - Cell 2021 cited by 246

  6. Subthalamic nucleus stimulation reverses mediofrontal influence over decision threshold

    Authors: James F. Cavanagh, Thomas V. Wiecki, Michael X Cohen, Christina M. Figueroa, Johan Samanta, Scott J. Sherman, Michael J. Frank - Nature Neuroscience 2011 cited by 687

  7. From reinforcement learning models to psychiatric and neurological disorders

    Authors: Tiago V. Maia, Michael J. Frank - Nature Neuroscience 2011 cited by 748

  8. Cognitive control over learning: Creating, clustering, and generalizing task-set structure.

    Authors: Anne Collins, Michael J. Frank - Psychological Review 2013 cited by 456

  9. Impulse control disorders and levodopa-induced dyskinesias in Parkinson's disease: an update

    Authors: Valerie Voon, T. Celeste Napier, Michael J. Frank, Véronique Sgambato, Anthony A. Grace, María Rodríguez‐Oroz, José Á. Obeso, Erwan Bézard, Pierre‐Olivier Fernagut - The Lancet Neurology 2017 cited by 357

  10. Advances in the computational understanding of mental illness

    Authors: Quentin J. M. Huys, Michael Browning, Martin P. Paulus, Michael J. Frank - Neuropsychopharmacology 2020 cited by 183

  11. Multiple Dissociations Between Comorbid Depression and Anxiety on Reward and Punishment Processing: Evidence From Computationally Informed EEG

    Authors: James F. Cavanagh, Andrew W. Bismark, Michael J. Frank, John J. B. Allen - Computational Psychiatry 2018 cited by 139

  12. The drift diffusion model as the choice rule in reinforcement learning

    Authors: Mads L. Pedersen, Michael J. Frank, Guido Biele - Psychonomic Bulletin & Review 2016 cited by 327

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

    Authors: Anne Collins, Michael J. Frank - European Journal of Neuroscience 2012 cited by 479

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

    Authors: Adam R. Aron, Timothy E.J. Behrens, Steve Smith, Michael J. Frank, Russell A. Poldrack - Journal of Neuroscience 2007 cited by 997

  15. Hold Your Horses: Impulsivity, Deep Brain Stimulation, and Medication in Parkinsonism

    Authors: Michael J. Frank, Johan Samanta, Ahmed A. Moustafa, Scott J. Sherman - Science 2007 cited by 1,139

  16. Frontal Theta Reflects Uncertainty and Unexpectedness during Exploration and Exploitation

    Authors: James F. Cavanagh, Carlos María López Fé y Figueroa, Michael X Cohen, Michael J. Frank - Cerebral Cortex 2011 cited by 303

  17. Computational Psychiatry Needs Time and Context

    Authors: Peter Hitchcock, Eiko I. Fried, Michael J. Frank - Annual Review of Psychology 2021 cited by 128

  18. Opponent actor learning (OpAL): Modeling interactive effects of striatal dopamine on reinforcement learning and choice incentive.

    Authors: Anne Collins, Michael J. Frank - Psychological Review 2014 cited by 466

  19. Mechanisms of Hierarchical Reinforcement Learning in Corticostriatal Circuits 1: Computational Analysis

    Authors: Michael J. Frank, David Badre - Cerebral Cortex 2011 cited by 366

  20. A mosaic of cost–benefit control over cortico-striatal circuitry

    Authors: Andrew Westbrook, Michael J. Frank, Roshan Cools - Trends in Cognitive Sciences 2021 cited by 94

  21. Interactions between frontal cortex and basal ganglia in working memory: A computational model

    Authors: Michael J. Frank, B. LOUGHRY, R. C. O'REILLY - Cognitive Affective & Behavioral Neuroscience 2001 cited by 918

  22. fMRI and EEG Predictors of Dynamic Decision Parameters during Human Reinforcement Learning

    Authors: Michael J. Frank, Chris Gagne, Erika Nyhus, Sean E. Masters, Thomas V. Wiecki, James F. Cavanagh, David Badre - Journal of Neuroscience 2015 cited by 280

  23. On the normative advantages of dopamine and striatal opponency for learning and choice

    Authors: Alana Jaskir, Michael J. Frank - eLife 2023 cited by 56

  24. Beyond Drift Diffusion Models: Fitting a Broad Class of Decision and Reinforcement Learning Models with HDDM

    Authors: Alexander Fengler, Krishn Bera, Mads L. Pedersen, Michael J. Frank - Journal of Cognitive Neuroscience, J. Cogn. Neurosci. 2022 cited by 43