Mehdi Keramati

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Amir DezfouliBIMLOGIQVerified email at bimlogiq.com
Boris GutkinEcole Normale SuperieureVerified email at ens.fr
Payam PirayAssistant Professor of Psychology and Neuroscience at USCVerified email at usc.edu
Rani MoranLecturer (Assistant Professor) Queen Mary University of London; Honorary Research Fellow, UCLVerified email at qmul.ac.uk
Bahador BahramiLudwig Maximilian UniversitätVerified email at psy.lmu.de
Nitzan ShaharSchool of Psychology, Sagol School of Neuroscience, Tel-Aviv UniversityVerified email at tauex.tau.ac.il
Tobias U. HauserUniversity of Tübingen; Wellcome Centre for Human Neuroimaging & Max Planck UCL Centre forVerified email at uni-tuebingen.de
Michael MoutoussisClinical lecturer, Department of Imaging Neuroscience, UCLVerified email at ucl.ac.uk
Joaquín NavajasUniversidad Torcuato Di TellaVerified email at utdt.edu
peter lathamProfessor, Gatsby Computational Neuroscience Unit, UCLVerified email at gatsby.ucl.ac.uk
Peter SmittenaarSurgo HealthVerified email at smittenaar.uk
Serge H. Ahmed / Twitter: @SergeAh...Directeur de recherche CNRSVerified email at u-bordeaux.fr
Hamed Ekhtiari, MD, PhD,Laureate Institute for Brain ResearchVerified email at laureateinstitute.org
Armin LakUniversity of OxfordVerified email at dpag.ox.ac.uk
Kensaku NomotoDokkyo Medical UniversityVerified email at dokkyomed.ac.jp
Adam KepecsBJC Investigator, Robert J Terry Professor of Neuroscience and Professor of Psychiatry, WashingtonVerified email at wustl.edu
Eren SezenerDeepMindVerified email at google.com
Uri HertzUniversity of HaifaVerified email at is.haifa.ac.il
Julie J. LeeNew York UniversityVerified email at nyu.edu
Majid Nili AhmadabadiProfessor of ECE, University of TehranVerified email at ut.ac.ir

Mehdi Keramati

MaxPlanck Centre for Computational Psychiatry, UCL

Verified email at gatsby.ucl.ac.uk

Computational neuroscience decision theory machine learning neuroeconomics


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Speed/accuracy trade-off between the habitual and the goal-directed processes M Keramati, A Dezfouli, P Piray PLoS computational biology 7 (5), e1002055, 2011	474	2011
Adaptive integration of habits into depth-limited planning defines a habitual-goal–directed spectrum M Keramati, P Smittenaar, RJ Dolan, P Dayan Proceedings of the National Academy of Sciences 113 (45), 12868-12873, 2016	310	2016
Homeostatic reinforcement learning for integrating reward collection and physiological stability M Keramati, B Gutkin Elife 3, e04811, 2014	196	2014
Midbrain Dopamine Neurons Signal Belief in Choice Accuracy during a Perceptual Decision A Lak, K Nomoto, M Keramati, M Sakagami, A Kepec Current Biology, 2017	178	2017
The idiosyncratic nature of confidence J Navajas, C Hindocha, H Foda, M Keramati, PE Latham, B Bahrami Nature Human Behavior 1 (11), 810-818, 2017	138	2017
Improving the reliability of model-based decision-making estimates in the two-stage decision task with reaction-times and drift-diffusion modeling N Shahar, TU Hauser, M Moutoussis, R Moran, M Keramati, ... PLoS computational biology 15 (2), e1006803, 2019	113	2019
Consortium, N., & Dolan, RJ (2019). Improving the reliability of model-based decision-making estimates in the two-stage decision task with reaction-times and drift-diffusion … N Shahar, TU Hauser, M Moutoussis, R Moran, M Keramati PLoS computational biology 15 (2), e1006803, 0	68
A reinforcement learning theory for homeostatic regulation M Keramati, B Gutkin Advances in neural information processing systems 24, 2011	63	2011
A neurocomputational model for cocaine addiction A Dezfouli, P Piray, MM Keramati, H Ekhtiari, C Lucas, A Mokri Neural computation 21 (10), 2869-2893, 2009	62	2009
Imbalanced decision hierarchy in addicts emerging from drug-hijacked dopamine spiraling circuit M Keramati, B Gutkin PloS one 8 (4), e61489, 2013	57	2013
Cocaine Addiction as a Homeostatic Reinforcement Learning Disorder M Keramati, A Durand, P Girardeau, B Gutkin, A Serge Psychological Review 125, 2017	52	2017
Individual differences in nucleus accumbens dopamine receptors predict development of addiction-like behavior: a computational approach P Piray, MM Keramati, A Dezfouli, C Lucas, A Mokri Neural computation 22 (9), 2334-2368, 2010	48	2010
Retrospective model-based inference guides model-free credit assignment R Moran, M Keramati, P Dayan, RJ Dolan Nature communications 10 (1), 750, 2019	41	2019
Optimizing the depth and the direction of prospective planning using information values CE Sezener, A Dezfouli, M Keramati PLoS computational biology 15 (3), e1006827, 2019	34	2019
Misdeed of the need: towards computational accounts of transition to addiction M Keramati, S Ahmed, B Gutkin Current Opinion in Neurobiology 46, 142–153, 2017	16	2017
Stochastic satisficing account of confidence in uncertain value-based decisions U Hertz, B Bahrami, M Keramati PLoS One 13 (4), 2018	15	2018
Flexibility to contingency changes distinguishes habitual and goal-directed strategies in humans J Lee, M Keramati PLoS computational biology 13 (9), 2017	11	2017
Behavioural signatures of backward planning in animals A Afsardeir, M Keramati European Journal of Neuroscience 47 (5), 479-487, 2018	9	2018
Understanding addiction as a pathological state of multiple decision making processes: a neurocomputational perspective M Keramati, A Dezfouli, P Piray Computational neuroscience of drug addiction, 205-233, 2012	6	2012
Model based planners reflect on their model-free propensities R Moran, M Keramati, RJ Dolan PLOS Computational Biology 17 (1), e1008552, 2021	5	2021

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