| Frontal theta as a mechanism for cognitive control JF Cavanagh, MJ Frank Trends in cognitive sciences 18 (8), 414-421, 2014 | 2971 | 2014 |
| By carrot or by stick: cognitive reinforcement learning in parkinsonism MJ Frank, LC Seeberger, RC O'reilly Science 306 (5703), 1940-1943, 2004 | 2477 | 2004 |
| Making working memory work: a computational model of learning in the prefrontal cortex and basal ganglia RC O'Reilly, MJ Frank Neural computation 18 (2), 283-328, 2006 | 1456 | 2006 |
| Hold your horses: impulsivity, deep brain stimulation, and medication in parkinsonism MJ Frank, J Samanta, AA Moustafa, SJ Sherman science 318 (5854), 1309-1312, 2007 | 1307 | 2007 |
| HDDM: Hierarchical Bayesian estimation of the drift-diffusion model in Python TV Wiecki, I Sofer, MJ Frank Frontiers in neuroinformatics 7, 14, 2013 | 1266 | 2013 |
| Computational psychiatry as a bridge from neuroscience to clinical applications QJM Huys, TV Maia, MJ Frank Nature neuroscience 19 (3), 404-413, 2016 | 1265 | 2016 |
| Triangulating a cognitive control network using diffusion-weighted magnetic resonance imaging (MRI) and functional MRI AR Aron, TE Behrens, S Smith, MJ Frank, RA Poldrack Journal of Neuroscience 27 (14), 3743-3752, 2007 | 1263 | 2007 |
| Interactions between frontal cortex and basal ganglia in working memory: a computational model MJ Frank, B Loughry, RC O’Reilly Cognitive, Affective, & Behavioral Neuroscience 1 (2), 137-160, 2001 | 1188 | 2001 |
| Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism MJ Frank Journal of cognitive neuroscience 17 (1), 51-72, 2005 | 1160 | 2005 |
| From reinforcement learning models to psychiatric and neurological disorders TV Maia, MJ Frank Nature neuroscience 14 (2), 154-162, 2011 | 941 | 2011 |
| Hold your horses: a dynamic computational role for the subthalamic nucleus in decision making MJ Frank Neural networks 19 (8), 1120-1136, 2006 | 898 | 2006 |
| Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning MJ Frank, AA Moustafa, HM Haughey, T Curran, KE Hutchison Proceedings of the National Academy of Sciences 104 (41), 16311-16316, 2007 | 828 | 2007 |
| Subthalamic nucleus stimulation reverses mediofrontal influence over decision threshold JF Cavanagh, TV Wiecki, MX Cohen, CM Figueroa, J Samanta, ... Nature neuroscience 14 (11), 1462-1467, 2011 | 770 | 2011 |
| Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal. MJ Frank, ED Claus Psychological review 113 (2), 300, 2006 | 738 | 2006 |
| Motor symptoms in Parkinson’s disease: A unified framework AA Moustafa, S Chakravarthy, JR Phillips, A Gupta, S Keri, B Polner, ... Neuroscience & Biobehavioral Reviews 68, 727-740, 2016 | 608 | 2016 |
| Prefrontal and striatal dopaminergic genes predict individual differences in exploration and exploitation MJ Frank, BB Doll, J Oas-Terpstra, F Moreno Nature neuroscience 12 (8), 1062-1068, 2009 | 593 | 2009 |
| How much of reinforcement learning is working memory, not reinforcement learning? A behavioral, computational, and neurogenetic analysis AGE Collins, MJ Frank European Journal of Neuroscience 35 (7), 1024-1035, 2012 | 586 | 2012 |
| A mechanistic account of striatal dopamine function in human cognition: psychopharmacological studies with cabergoline and haloperidol. MJ Frank, RC O'Reilly Behavioral neuroscience 120 (3), 497, 2006 | 583 | 2006 |
| Towards an executive without a homunculus: computational models of the prefrontal cortex/basal ganglia system TE Hazy, MJ Frank, RC O'reilly Philosophical Transactions of the Royal Society B: Biological Sciences 362 …, 2007 | 582 | 2007 |
| Frontal theta links prediction errors to behavioral adaptation in reinforcement learning JF Cavanagh, MJ Frank, TJ Klein, JJB Allen Neuroimage 49 (4), 3198-3209, 2010 | 577 | 2010 |
james m. goldProfessor of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of MedicineVerified email at mprc.umaryland.edu
