Research Topics
Species | Michael J FrankSummaryAffiliation: University of Arizona Country: USA Publications
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Publications
Transitivity, flexibility, conjunctive representations, and the hippocampus. II. A computational analysisMichael J Frank
Department of Psychology, University of Colorado, Boulder, Colorado 80309, USA
Hippocampus 13:341-54. 2003..We use this model to account for a range of existing data and to make a number of distinctive predictions that clearly contrast these two views...
Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learningMichael J Frank
Department of Psychology and Program in Neuroscience, University of Arizona, Tucson, AZ 85721, USA
Proc Natl Acad Sci U S A 104:16311-6. 2007..Computational maximum likelihood analyses reveal independent gene effects on three reinforcement learning parameters that can explain the observed dissociations...- Cross-task individual differences in error processing: neural, electrophysiological, and genetic componentsMichael J Frank
Department of Psychology, University of Arizona, Tucson, Arizona 85721, USA
Cogn Affect Behav Neurosci 7:297-308. 2007..These results are consistent with a role for the Pe and frontal monoamines in error awareness... - Understanding decision-making deficits in neurological conditions: insights from models of natural action selectionMichael J Frank
Departments of Psychology and Neurology, Program in Neuroscience, University of Arizona Tucson, AZ 85721, USA
Philos Trans R Soc Lond B Biol Sci 362:1641-54. 2007..Incorporation of cortical noradrenaline function into the model improves action selection in noisy environments and accounts for response variability in ADHD. We close with more general clinical implications... - Midazolam, hippocampal function, and transitive inference: Reply to GreeneMichael J Frank
Dept of Psychology and Program in Neuroscience, University of Arizona, Tucson, USA
Behav Brain Funct 4:5. 2008..Here we stand by our original hypothesis, which remains the most parsimonious account of the data, and is grounded by multiple lines of evidence... 
Learning to avoid in older ageMichael J Frank
Department of Psychology, University of Arizona, Tucson, AZ 85721 0068, USA
Psychol Aging 23:392-8. 2008..These findings are consistent with models positing multiple neural mechanisms that support probabilistic integration and trial-to-trial behavior, which may be differentially impacted by older age...- Testing computational models of dopamine and noradrenaline dysfunction in attention deficit/hyperactivity disorderMichael J Frank
Department of Psychology and Program in Neuroscience, University of Arizona, Tucson, AZ 85721, USA
Neuropsychopharmacology 32:1583-99. 2007..Taken together, our results demonstrate the usefulness of computational approaches for understanding cognitive deficits in ADHD... - Hold your horses: a dynamic computational role for the subthalamic nucleus in decision makingMichael J Frank
Department of Psychology, Program in Neuroscience, University of Arizona, Tucson, AZ 85721, USA
Neural Netw 19:1120-36. 2006..Finally, the model accounts for the beneficial effects of STN lesions on these oscillations, but suggests that this benefit may come at the expense of impaired decision making... - When memory fails, intuition reigns: midazolam enhances implicit inference in humansMichael J Frank
Department of Psychology and Program in Neuroscience, University of Arizona, Tucson, AZ 85721, USA
Psychol Sci 17:700-7. 2006..We suggest that disengaging the hippocampal explicit memory system can be advantageous for this more implicit form of learning... - A mechanistic account of striatal dopamine function in human cognition: psychopharmacological studies with cabergoline and haloperidolMichael J Frank
Department of Psychology and Program in NeuroscienceUniversity of Arizona, Tucson, AZ 85721, USA
Behav Neurosci 120:497-517. 2006..Drug effects interacted with baseline working memory span in all tasks. Taken together, the results support a unified account of the role of dopamine in modulating cognitive processes that depend on the basal ganglia... - Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversalMichael J Frank
Department of Psychology, University of Colorado at Boulder, Boulder, CO, USA
Psychol Rev 113:300-26. 2006..The model successfully captures patterns of behavior resulting from OFC damage in decision making, reversal learning, and devaluation paradigms and makes additional predictions for the underlying source of these deficits... - Hold your horses: impulsivity, deep brain stimulation, and medication in parkinsonismMichael J Frank
Department of Psychology and Program in Neuroscience, University of Arizona, Tucson, AZ 85721, USA
Science 318:1309-12. 2007..These findings implicate independent mechanisms leading to impulsivity in treated Parkinson's patients and were predicted by a single neurocomputational model of the basal ganglia... - Single dose of a dopamine agonist impairs reinforcement learning in humans: evidence from event-related potentials and computational modeling of striatal-cortical functionDiane L Santesso
Department of Psychology, Harvard University, Cambridge, MA 02138, USA
Hum Brain Mapp 30:1963-76. 2009..These preliminary findings offer important insights on the role of phasic DA signals on reinforcement learning in humans and provide initial evidence regarding the spatiotemporal dynamics of brain mechanisms underlying these processes... - A role for dopamine in temporal decision making and reward maximization in parkinsonismAhmed A Moustafa
Department of Psychology and Program in Neuroscience, University of Arizona, Tucson, Arizona 85721, USA
J Neurosci 28:12294-304. 2008..There were also robust trial-to-trial changes in response time, but these single trial adaptations were not affected by disease or medication and are posited to rely on extrastriatal, possibly prefrontal, structures... - A dopaminergic basis for working memory, learning and attentional shifting in ParkinsonismAhmed A Moustafa
Department of Psychology and Program in Neuroscience, University of Arizona, Tucson, AZ 85721, United States
Neuropsychologia 46:3144-56. 2008..These results lend further insight into the role of basal ganglia dopamine in WM and broadly support predictions from neurocomputational models... - By carrot or by stick: cognitive reinforcement learning in parkinsonismMichael J Frank
Department of Psychology and Center for Neuroscience, University of Colorado Boulder, Boulder, CO 80309 0345, USA
Science 306:1940-3. 2004.... - Instructional control of reinforcement learning: a behavioral and neurocomputational investigationBradley B Doll
Department of Cognitive and Linguistic Sciences, Department of Psychology, Brown University, USA
Brain Res 1299:74-94. 2009.... - Social stress reactivity alters reward and punishment learningJames F Cavanagh
Department of Psychology, University of Arizona, Tucson, AZ, USA
Soc Cogn Affect Neurosci 6:311-20. 2011.... - Altered cingulate sub-region activation accounts for task-related dissociation in ERN amplitude as a function of obsessive-compulsive symptomsJames F Cavanagh
University of Arizona, Tucson, AZ, USA
Neuropsychologia 48:2098-109. 2010..These novel findings link both tonic and phasic activities in the ACC to action monitoring alterations, including dissociation in performance deficits, in OC symptomatic participants... - Towards an executive without a homunculus: computational models of the prefrontal cortex/basal ganglia systemThomas E Hazy
Department of Psychology, University of Colorado Boulder, 345 UCB, Boulder, CO 80309, USA
Philos Trans R Soc Lond B Biol Sci 362:1601-13. 2007..This learning is based on reinforcement learning mechanisms associated with the midbrain dopaminergic system and its activation via the BG and amygdala. Finally, we briefly describe various empirical tests of this framework... - Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated ParkinsonismMichael J Frank
Department of Psychology and Center for Neuroscience, University of Colorado at Boulder, CO 80309, USA
J Cogn Neurosci 17:51-72. 2005..The model also provides novel testable predictions for neuropsychological and pharmacological studies, and motivates further investigation of BG/DA interactions with the prefrontal cortex in working memory... - Error-related negativity predicts reinforcement learning and conflict biasesMichael J Frank
Department of Pschology and Center for Neuroscience, University of Colorado at Boulder, Boulder, CO 80309, USA
Neuron 47:495-501. 2005..These results demonstrate that the ERN predicts the degree to which participants are biased to learn more from their mistakes than their correct choices and clarify the extent to which it indexes decision conflict... - PVLV: the primary value and learned value Pavlovian learning algorithmRandall C O'Reilly
Department of Psychology, University of Colorado, Boulder, CO 80309, USA
Behav Neurosci 121:31-49. 2007..Overall, the model provides a biologically plausible framework for understanding the neural basis of reward learning... - Reinforcement-based decision making in corticostriatal circuits: mutual constraints by neurocomputational and diffusion modelsRoger Ratcliff
Department of Psychology, The Ohio State University, Columbus, OH 43210, USA
Neural Comput 24:1186-229. 2012..The result is a better fit and understanding of reinforcement-based choice data than that which would have occurred with either model alone... - Hippocampus, cortex, and basal ganglia: insights from computational models of complementary learning systemsHisham E Atallah
Department of Psychology, Center for Neuroscience, University of Colorado at Boulder, 345 UCB, Boulder, CO 80309, USA
Neurobiol Learn Mem 82:253-67. 2004..Here, we summarize recent results in the domains of recognition memory, contextual fear conditioning, effects of basal ganglia lesions on stimulus-response and place learning, and flexible responding... - Neurocomputational models of basal ganglia function in learning, memory and choiceMichael X Cohen
Department of Psychology, Program in Neuroscience, University of Arizona, 1503 E University Blvd, Tucson, AZ 85721, United States
Behav Brain Res 199:141-56. 2009..Finally, we discuss possible future directions and possible ways to integrate different types of models... - Making working memory work: a computational model of learning in the prefrontal cortex and basal gangliaRandall C O'Reilly
Department of Psychology, University of Colorado Boulder, Boulder, CO 80309, USA
Neural Comput 18:283-328. 2006..The model's performance compares favorably with standard backpropagation-based temporal learning mechanisms on the challenging 1-2-AX working memory task and other benchmark working memory tasks... - Triangulating a cognitive control network using diffusion-weighted magnetic resonance imaging (MRI) and functional MRIAdam R Aron
Department of Psychology, University of California San Diego, La Jolla, California 92093, USA
J Neurosci 27:3743-52. 2007..The results also demonstrate a three-way functional-anatomical network in the right hemisphere that could either brake or completely stop responses... - Frontal theta links prediction errors to behavioral adaptation in reinforcement learningJames F Cavanagh
Department of Psychology, University of Arizona, Tucson, AZ, USA
Neuroimage 49:3198-209. 2010.... - Single dose of a dopamine agonist impairs reinforcement learning in humans: behavioral evidence from a laboratory-based measure of reward responsivenessDiego A Pizzagalli
Department of Psychology, Harvard University, 1220 William James Hall, 33 Kirkland Street, Cambridge, MA 02138, USA
Psychopharmacology (Berl) 196:221-32. 2008..Animal studies have emphasized the role of phasic dopamine (DA) signaling in reward-related learning, but these processes remain largely unexplored in humans... - Seeing is believing: trustworthiness as a dynamic beliefLuke J Chang
Department of Psychology, University of Arizona, 1503 E University Blvd, Tucson, AZ 85721, United States
Cogn Psychol 61:87-105. 2010..This study provides a novel quantitative framework to conceptualize the notion of trustworthiness... - Sensitivity to reward and punishment in major depressive disorder: effects of rumination and of single versus multiple experiencesAnson J Whitmer
Department of Psychology, Stanford University, Stanford, CA 94305, USA
Cogn Emot 26:1475-85. 2012..The effects of rumination on sensitivity to punishment may be a mechanism by which rumination can lead to maladaptive consequences... - When logic fails: implicit transitive inference in humansMichael J Frank
Department of Psychology, University of Colorado, Boulder, CO 80309, USA
Mem Cognit 33:742-50. 2005..In this account, choice performance is based on differential associative strengths across the stimulus items that develop over training, despite equal overt reinforcement... - Pupillometric and behavioral markers of a developmental shift in the temporal dynamics of cognitive controlChristopher H Chatham
Department of Psychology and Neuroscience, University of Colorado, Boulder, CO 80309, USA
Proc Natl Acad Sci U S A 106:5529-33. 2009..These results demonstrate the need to reconsider the origins of cognitive control and the basis for children's behaviors across domains... - Acute stress selectively reduces reward sensitivityLisa H Berghorst
Department of Psychology, Harvard University Cambridge, MA, USA Center for Depression, Anxiety and Stress Research, Harvard Medical School, McLean Hospital Belmont, MA, USA
Front Hum Neurosci 7:133. 2013..While such results highlight the possibility that stress-induced anhedonia might be an important mechanism linking stress to affective disorders, future studies are necessary to confirm this conjecture... - Selective reinforcement learning deficits in schizophrenia support predictions from computational models of striatal-cortical dysfunctionJames A Waltz
Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland 21228, USA
Biol Psychiatry 62:756-64. 2007..We investigated whether fronto-striatal dysfunction in schizophrenia (SZ) is characterized by selective impairment in either reward- (Go) or punishment-driven (NoGo) learning...