decision-making

Motivation, Cerveau & Comportement

Domaine de recherche principal: 

Cognitive neurosciences / neuropsychology /neuroeconomy

Mots clefs: 

decision-making
computational modeling
Neuropsychology
neuroimaging
elecrophysiology

Labelisation ENP: 

2007

Centre de recherche / Institut: 

Institut du Cerveau et de la Moelle épinière

Code unité de recherche: 

UMRS 1127 UMR 7225

Why do we do what we do? We are largely unaware of our own motives. Our team seeks to understand how motivation works, in both the normal and pathological brain. We define motivation as a set of processes that assign values to potential situations so as to drive behavior.

Our research is closely related to the emerging field of neuroeconomics, which is focused on understanding value-based decision-making and on explaining deviations to rationality. We wish to build a comprehensive account of motivational processes, investigating

Leader

Leader: 

Co leader: 

Personnel

Etudiants ENP: 

Établissements

Établissement de rattachement: 

Inserm

Établissements affiliés: 

CNRS
Université Pierre et Marie Curie

Université: 

Université Pierre et Marie Curie

École doctorale: 

ED158
Laboratory

Initiatives d'Excellence: 

Labex BioPsy
Publications

publications: 

Blain B, Hollard G, Pessiglione M. Incentive Sensitivity as a Behavioral Marker of Clinical Remission From Major Depressive Episode. J Clin Psychiatry. 2016 Jun;77(6):e697-703. doi: 10.4088/JCP.15m09995.

Automatic integration of confidence in the brain valuation signal. Lebreton M, Abitbol R, Daunizeau J, Pessiglione M. Nat Neurosci. 2015 Aug;18(8):1159-67. 

Skvortsova V, Palminteri S, Pessiglione M. Learning to minimize efforts versus maximizing rewards: computational principles and neural correlates. J Neurosci. 2014 Nov 19;34(47):15621-30. doi: 10.1523/JNEUROSCI.1350-14.2014.

Lebreton M, Bertoux M, Boutet C, Lehericy S, Dubois B, Fossati P, Pessiglione M. A critical role for the hippocampus in the valuation of imagined outcomes. PLoS Biol. 2013 Oct;11(10):e1001684. doi: 10.1371/journal.pbio.1001684. Epub 2013 Oct 22.

Similar improvement of reward and punishment learning by serotonin reuptake inhibitors in obsessive-compulsive disorder. Palminteri S, Clair AH, Mallet L, Pessiglione M.  Biological Psychiatry (2012).

Neural mechanisms underlying motivation of mental versus physical effort. 
Schmidt L, Lebreton M, Cléry-Melin ML, Daunizeau J, Pessiglione M
PLoS Biol. 2012 Feb;10(2):e1001266.

Complementary neural correlates of motivation in dopaminergic and noradrenergic neurons of monkeys, S. Bouret, S. Ravel, et B. J. Richmond, Frontiers in Behavioral Neuroscience, vol. 6, 201

Intersection of reward and memory in monkey rhinal cortex. Clark AM, Bouret S, Young AM, Richmond BJ.J Neurosci. 2012 May 16;32(20):6869-77

Groupe Lobe Frontal

Mots clefs: 

decision-making
neuroimaging techniques
computational modeling
behavioral studies

Labelisation ENP: 

2007

Centre de recherche / Institut: 

ENS Ecole Normale Supérieure

Code unité de recherche: 

U960

Le Laboratoire de Neurosciences Cognitives se consacre à l'étude des bases neurales de l'Action et des processus cognitifs qui lui sont associés sur les plans moteurs, linguistiques, sociaux et intentionnels. Il s'intéresse tout particulièrement à comprendre le fonctionnement du cerveau humain qui sous-tend ces processus cognitifs au moyen des outils d'investigation modernes de la neuroimagerie (Résonance magnétique fonctionnelle, Magnéto- et Electro-encéphalographie), des méthodes de la psychologie expérimentale, et de la modélisation mathématique.

Leader

Leader: 

Établissements

Établissement de rattachement: 

Ecole Normale Supérieure

Établissements affiliés: 

Inserm

Université: 

Université Pierre et Marie Curie

École doctorale: 

ED158
Laboratory

Nom: 

Laboratoire de Neurosciences Cognitives

Initiatives d'Excellence: 

Labex Institut d'Etude de la Cognition IEC - IDHEX Paris Sciences et Lettres
Publications

publications: 

Drugowitsch J, Wyart V, Devauchelle AD, Koechlin E. Computational Precision of Mental Inference as Critical Source of Human Choice Suboptimality. Neuron. 2016 Dec 21;92(6):1398-1411. doi: 10.1016/j.neuron.2016.11.005. 

Drugowitsch, J., Wyart, V. Koechlin, E. Inference rather than selection noise explains behavioral variability in perceptual decision-making. Proceedings of Computational and Systems Neuroscience 2013.

Collins, A., Koechlin, E. (2012). Reasoning, learning and creativity: Frontal lobe function and human decision-making. PLoS Biology, 10(3):e1001293.doi:10.1371/journal.pbio.1001293.

Drugowitsch, J.& Koechlin, E. (2012). Task set switching: dissecting ideal observer models and their approximation. Proceedings of Computational and Systems Neuroscience, 2012.

Summerfield, C., Behrens, T., Koechlin, E. (2011). Perceptual classification in a rapidly-changing environment, Neuron, 71, 725-736.

Koechlin, E. (2011). Frontal pole function: what is specifically human?, Trends in Cognitive Sciences, 15, 241.
Chambon V, Domenech P, Pacherie E , Koechlin E, Baraduc P, Farrer C (2011). What Are They Up To? The Role of Sensory Evidence and Prior Knowledge in Action Understanding, PloS One, 6, e17133.

Mathematics of Neural Circuits

Domaine de recherche principal: 

Computational neurosciences / neural theory

Mots clefs: 

Learning
Synaptic plasticity
computational neuroscience
cognitive decision processes
neuronal architectures
drug addiction
short-term memory
decision-making

Labelisation ENP: 

2007

Centre de recherche / Institut: 

ENS Ecole Normale Supérieure

Code unité de recherche: 

U960

Le but du GNT est de comprendre les bases du traitement de l'information dans le cerveau, en mettant en évidence les liens entre la dynamique collective d'une population neuronale et les fonctions associées à cette population.

Leader

Leader: 

Personnel

Etudiants ENP: 

Établissements

Établissement de rattachement: 

Ecole Normale Supérieure

Établissements affiliés: 

Inserm
Laboratory

Nom: 

Laboratoire de Neurosciences Cognitives

Initiatives d'Excellence: 

IEC, PSLP
Publications

publications: 

Buchin A, Chizhov A, Huberfeld G, Miles R, Gutkin BS. Reduced Efficacy of the KCC2 Cotransporter Promotes Epileptic Oscillations in a Subiculum Network Model. J Neurosci. 2016 Nov 16;36(46):11619-11633.

Keramati M, Gutkin B. Homeostatic reinforcement learning for integrating reward collection and physiological stability. Elife. 2014 Dec 2;3. doi: 10.7554/eLife.04811.

Caze, R.D., Humphries, M., and Gutkin, B.S., Passive Dendrites Enable Single Neurons to Compute Linearly Non-separableFunctions, PLOS Computational Biology, 9(2): e1002867, (2013).


Keramati, M. and Gutkin, B.S., Imbalanced decision hierarchy in addicts emerging from drug-hijacked dopamine spiraling circuit,PLOS One, 8:4, 1-8 (2013).

Lochmann, T., Ernst, U.A., and Denève, S., Perceptual inference predicts contextual modulations of sensory responses, Journal of Neuroscience, 32(12), 4179-95 (2012).

Tolu, S., Eddine, R., Marti, F., David, V., Graupner, M., Baudonnat, S.P.M., Besson, M., Reperant, C., Zemdegs, J., Pages, C., Caboche, J., Gutkin, B., Gardier, A.M., Changeux, J., Faure, P., and Maskos, U., Co-activation of VTA DA and GABA neurons mediates nicotine reinforcement., Molecular Psychiatry, in press, (2012).

DiPoppa, M., Krupa, M., Torcini, A., and Gutkin, B., Marginally Stable States and Quasi-periodic minor attractors in excitable pulse-coupled networks, SIAM Journal of Applied Dynamical Systems, 11, 864 894 (2012).

Deneve, S., Making decisions with unknown sensory reliability, Frontiers in Neuroscience, 6:75, doi: 10.3389/fnins.2012.00075 (2012).

Jardri, R. and Deneve, S., Computational models of hallucinations., The Neuroscience of Hallucinations, (2012).