| Year |
Citation |
Score |
| 2023 |
Oikonomou P, Dometios A, Khamassi M, Tzafestas CS. Zero-shot model-free learning of periodic movements for a bio-inspired soft-robotic arm. Frontiers in Robotics and Ai. 10: 1256763. PMID 37929074 DOI: 10.3389/frobt.2023.1256763 |
0.825 |
|
| 2022 |
Renaudo E, Zech P, Chatila R, Khamassi M. Editorial: Computational models of affordance for robotics. Frontiers in Neurorobotics. 16: 1045355. PMID 36277333 DOI: 10.3389/fnbot.2022.1045355 |
0.801 |
|
| 2022 |
Moin Afshar N, Cinotti F, Martin DA, Khamassi M, Calu DJ, Taylor JR, Groman SM. Reward-mediated, model-free reinforcement-learning mechanisms in Pavlovian and instrumental tasks are related. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. PMID 36216504 DOI: 10.1523/JNEUROSCI.1113-22.2022 |
0.829 |
|
| 2022 |
Massi E, Barthélemy J, Mailly J, Dromnelle R, Canitrot J, Poniatowski E, Girard B, Khamassi M. Model-Based and Model-Free Replay Mechanisms for Reinforcement Learning in Neurorobotics. Frontiers in Neurorobotics. 16: 864380. PMID 35812782 DOI: 10.3389/fnbot.2022.864380 |
0.779 |
|
| 2021 |
Roumazeilles L, Schurz M, Lojkiewiez M, Verhagen L, Schüffelgen U, Marche K, Mahmoodi A, Emberton A, Simpson K, Joly O, Khamassi M, Rushworth MFS, Mars RB, Sallet J. Social prediction modulates activity of macaque superior temporal cortex. Science Advances. 7: eabh2392. PMID 34524842 DOI: 10.1126/sciadv.abh2392 |
0.676 |
|
| 2021 |
Panayi MC, Khamassi M, Killcross S. The rodent lateral orbitofrontal cortex as an arbitrator selecting between model-based and model-free learning systems. Behavioral Neuroscience. 135: 226-244. PMID 34060876 DOI: 10.1037/bne0000454 |
0.327 |
|
| 2020 |
Wittmann MK, Fouragnan E, Folloni D, Klein-Flügge MC, Chau BKH, Khamassi M, Rushworth MFS. Global reward state affects learning and activity in raphe nucleus and anterior insula in monkeys. Nature Communications. 11: 3771. PMID 32724052 DOI: 10.1038/S41467-020-17343-W |
0.804 |
|
| 2020 |
Schut EHS, Alonso A, Smits S, Khamassi M, Samanta A, Negwer M, Nadif Kasri N, Navarro Lobato I, Genzel L. The Object Space Task reveals increased expression of cumulative memory in a mouse model of Kleefstra Syndrome. Neurobiology of Learning and Memory. 107265. PMID 32531423 DOI: 10.1016/J.Nlm.2020.107265 |
0.689 |
|
| 2020 |
Khamassi M, Girard B. Modeling awake hippocampal reactivations with model-based bidirectional search. Biological Cybernetics. PMID 32065253 DOI: 10.1007/S00422-020-00817-X |
0.779 |
|
| 2020 |
Staffa M, Rossi S, Tapus A, Khamassi M. Special Issue on Behavior Adaptation, Interaction, and Artificial Perception for Assistive Robotics International Journal of Social Robotics. 12: 613-616. DOI: 10.1007/S12369-020-00655-8 |
0.778 |
|
| 2019 |
Cinotti F, Marchand AR, Roesch MR, Girard B, Khamassi M. Impacts of inter-trial interval duration on a computational model of sign-tracking vs. goal-tracking behaviour. Psychopharmacology. PMID 31367850 DOI: 10.1007/S00213-019-05323-Y |
0.78 |
|
| 2019 |
Genzel L, Schut E, Schröder T, Eichler R, Khamassi M, Gomez A, Navarro Lobato I, Battaglia F. The object space task shows cumulative memory expression in both mice and rats. Plos Biology. 17: e3000322. PMID 31206519 DOI: 10.1371/Journal.Pbio.3000322 |
0.773 |
|
| 2019 |
Cinotti F, Fresno V, Aklil N, Coutureau E, Girard B, Marchand AR, Khamassi M. Dopamine blockade impairs the exploration-exploitation trade-off in rats. Scientific Reports. 9: 6770. PMID 31043685 DOI: 10.1038/S41598-019-43245-Z |
0.792 |
|
| 2019 |
Zaraki A, Khamassi M, Wood LJ, Lakatos G, Tzafestas C, Amirabdollahian F, Robins B, Dautenhahn K. A Novel Reinforcement-Based Paradigm for Children to Teach the Humanoid Kaspar Robot International Journal of Social Robotics. 12: 709-720. DOI: 10.1007/S12369-019-00607-X |
0.378 |
|
| 2018 |
Chatila R, Renaudo E, Andries M, Chavez-Garcia RO, Luce-Vayrac P, Gottstein R, Alami R, Clodic A, Devin S, Girard B, Khamassi M. Toward Self-Aware Robots. Frontiers in Robotics and Ai. 5: 88. PMID 33500967 DOI: 10.3389/frobt.2018.00088 |
0.819 |
|
| 2018 |
Bavard S, Lebreton M, Khamassi M, Coricelli G, Palminteri S. Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences. Nature Communications. 9: 4503. PMID 30374019 DOI: 10.1038/S41467-018-06781-2 |
0.427 |
|
| 2018 |
Cazé R, Khamassi M, Aubin L, Girard B. Hippocampal replays under the scrutiny of reinforcement learning models. Journal of Neurophysiology. PMID 30303758 DOI: 10.1152/Jn.00145.2018 |
0.812 |
|
| 2018 |
Lee B, Gentry RN, Bissonette GB, Herman RJ, Mallon JJ, Bryden DW, Calu DJ, Schoenbaum G, Coutureau E, Marchand AR, Khamassi M, Roesch MR. Manipulating the revision of reward value during the intertrial interval increases sign tracking and dopamine release. Plos Biology. 16: e2004015. PMID 30256785 DOI: 10.1371/Journal.Pbio.2004015 |
0.38 |
|
| 2018 |
Dollé L, Chavarriaga R, Guillot A, Khamassi M. Interactions of spatial strategies producing generalization gradient and blocking: A computational approach. Plos Computational Biology. 14: e1006092. PMID 29630600 DOI: 10.1371/Journal.Pcbi.1006092 |
0.81 |
|
| 2018 |
Chatila R, Renaudo E, Andries M, Chavez-Garcia R, Luce-Vayrac P, Gottstein R, Alami R, Clodic A, Devin S, Girard B, Khamassi M. Toward Self-Aware Robots Frontiers in Robotics and Ai. 5. DOI: 10.3389/frobt.2018.00088 |
0.78 |
|
| 2018 |
Velentzas G, Tsitsimis T, Rañó I, Tzafestas C, Khamassi M. Adaptive reinforcement learning with active state-specific exploration for engagement maximization during simulated child-robot interaction Paladyn, Journal of Behavioral Robotics. 9: 235-253. DOI: 10.1515/Pjbr-2018-0016 |
0.82 |
|
| 2018 |
Aklil N, Girard B, Denoyer L, Khamassi M. Sequential Action Selection and Active Sensing for Budgeted Localization in Robot Navigation International Journal of Semantic Computing. 12: 109-127. DOI: 10.1142/S1793351X18400068 |
0.811 |
|
| 2018 |
Khamassi M, Velentzas G, Tsitsimis T, Tzafestas C. Robot Fast Adaptation to Changes in Human Engagement During Simulated Dynamic Social Interaction With Active Exploration in Parameterized Reinforcement Learning Ieee Transactions On Cognitive and Developmental Systems. 10: 881-893. DOI: 10.1109/Tcds.2018.2843122 |
0.814 |
|
| 2017 |
Rougier NP, Hinsen K, Alexandre F, Arildsen T, Barba LA, Benureau FCY, Brown CT, de Buyl P, Caglayan O, Davison AP, Delsuc MA, Detorakis G, Diem AK, Drix D, Enel P, ... ... Khamassi M, et al. Sustainable computational science: the ReScience initiative. Peerj. Computer Science. 3: e142. PMID 34722870 DOI: 10.7717/peerj-cs.142 |
0.763 |
|
| 2017 |
Viejo G, Girard B, Procyk E, Khamassi M. Adaptive coordination of working-memory and reinforcement learning in non-human primates performing a trial-and-error problem solving task. Behavioural Brain Research. PMID 29061387 DOI: 10.1016/J.Bbr.2017.09.030 |
0.812 |
|
| 2017 |
Rougier NP, Hinsen K, Alexandre F, Arildsen T, Barba LA, Benureau FC, Brown CT, de Buyl P, Caglayan O, Davison AP, Delsuc M, Detorakis G, Diem AK, Drix D, Enel P, ... ... Khamassi M, et al. Sustainable computational science: the ReScience initiative Peerj Computer Science. 3: e142. DOI: 10.7717/Peerj-Cs.142 |
0.762 |
|
| 2015 |
Viejo G, Khamassi M, Brovelli A, Girard B. Modeling choice and reaction time during arbitrary visuomotor learning through the coordination of adaptive working memory and reinforcement learning. Frontiers in Behavioral Neuroscience. 9: 225. PMID 26379518 DOI: 10.3389/Fnbeh.2015.00225 |
0.835 |
|
| 2015 |
Palminteri S, Khamassi M, Joffily M, Coricelli G. Contextual modulation of value signals in reward and punishment learning. Nature Communications. 6: 8096. PMID 26302782 DOI: 10.1038/Ncomms9096 |
0.43 |
|
| 2015 |
Lesaint F, Sigaud O, Clark JJ, Flagel SB, Khamassi M. Experimental predictions drawn from a computational model of sign-trackers and goal-trackers. Journal of Physiology, Paris. 109: 78-86. PMID 24954026 DOI: 10.1016/J.Jphysparis.2014.06.001 |
0.797 |
|
| 2015 |
Viejo G, Khamassi M, Brovelli A, Girard B. Modeling choice and reaction time during arbitrary visuomotor learning through the coordination of adaptive working memory and reinforcement learning Frontiers in Behavioral Neuroscience. 9. DOI: 10.3389/fnbeh.2015.00225 |
0.819 |
|
| 2015 |
Renaudo E, Girard B, Chatila R, Khamassi M. Respective Advantages and Disadvantages of Model-based and Model-free Reinforcement Learning in a Robotics Neuro-inspired Cognitive Architecture Procedia Computer Science. 71: 178-184. DOI: 10.1016/J.Procs.2015.12.194 |
0.827 |
|
| 2014 |
Lesaint F, Sigaud O, Khamassi M. Accounting for negative automaintenance in pigeons: a dual learning systems approach and factored representations. Plos One. 9: e111050. PMID 25347531 DOI: 10.1371/Journal.Pone.0111050 |
0.808 |
|
| 2014 |
Khamassi M, Quilodran R, Enel P, Dominey PF, Procyk E. Behavioral Regulation and the Modulation of Information Coding in the Lateral Prefrontal and Cingulate Cortex. Cerebral Cortex (New York, N.Y. : 1991). PMID 24904073 DOI: 10.1093/Cercor/Bhu114 |
0.794 |
|
| 2014 |
Lesaint F, Sigaud O, Flagel SB, Robinson TE, Khamassi M. Modelling individual differences in the form of Pavlovian conditioned approach responses: a dual learning systems approach with factored representations. Plos Computational Biology. 10: e1003466. PMID 24550719 DOI: 10.1371/Journal.Pcbi.1003466 |
0.816 |
|
| 2014 |
Viejo GD, Khamassi M, Brovelli A, Girard B. Coordination of adaptive working memory and reinforcement learning systems explaining choice and reaction time in a human experiment Bmc Neuroscience. 15. DOI: 10.1186/1471-2202-15-S1-P156 |
0.834 |
|
| 2014 |
Renaudo E, Girard B, Chatila R, Khamassi M. Design of a control architecture for habit learning in robots Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8608: 249-260. DOI: 10.1007/978-3-319-09435-9_22 |
0.811 |
|
| 2013 |
Arleo A, Déjean C, Allegraud P, Khamassi M, Zugaro MB, Wiener SI. Optic flow stimuli update anterodorsal thalamus head direction neuronal activity in rats. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 33: 16790-5. PMID 24133279 DOI: 10.1523/Jneurosci.2698-13.2013 |
0.76 |
|
| 2013 |
Cos I, Khamassi M, Girard B. Modelling the learning of biomechanics and visual planning for decision-making of motor actions. Journal of Physiology, Paris. 107: 399-408. PMID 23973913 DOI: 10.1016/J.Jphysparis.2013.07.004 |
0.808 |
|
| 2013 |
Khamassi M, Enel P, Dominey PF, Procyk E. Medial prefrontal cortex and the adaptive regulation of reinforcement learning parameters. Progress in Brain Research. 202: 441-64. PMID 23317844 DOI: 10.1016/B978-0-444-62604-2.00022-8 |
0.83 |
|
| 2013 |
Bellot J, Khamassi M, Sigaud O, Girard B. Which Temporal Difference learning algorithm best reproduces dopamine activity in a multi-choice task? Bmc Neuroscience. 14: 144. DOI: 10.1186/1471-2202-14-S1-P144 |
0.811 |
|
| 2012 |
Khamassi M, Humphries MD. Integrating cortico-limbic-basal ganglia architectures for learning model-based and model-free navigation strategies. Frontiers in Behavioral Neuroscience. 6: 79. PMID 23205006 DOI: 10.3389/Fnbeh.2012.00079 |
0.467 |
|
| 2012 |
Caluwaerts K, Staffa M, N'Guyen S, Grand C, Dollé L, Favre-Félix A, Girard B, Khamassi M. A biologically inspired meta-control navigation system for the Psikharpax rat robot. Bioinspiration & Biomimetics. 7: 025009. PMID 22617382 DOI: 10.1088/1748-3182/7/2/025009 |
0.816 |
|
| 2012 |
Humphries MD, Khamassi M, Gurney K. Dopaminergic Control of the Exploration-Exploitation Trade-Off via the Basal Ganglia. Frontiers in Neuroscience. 6: 9. PMID 22347155 DOI: 10.3389/Fnins.2012.00009 |
0.376 |
|
| 2012 |
Bellot J, Sigaud O, Khamassi M. Which temporal difference learning algorithm best reproduces dopamine activity in a multi-choice task? Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7426: 289-298. DOI: 10.1007/978-3-642-33093-3_29 |
0.588 |
|
| 2012 |
Caluwaerts K, Favre-Félix A, Staffa M, N'Guyen S, Grand C, Girard B, Khamassi M. Neuro-inspired navigation strategies shifting for robots: Integration of a multiple landmark taxon strategy Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7375: 62-73. DOI: 10.1007/978-3-642-31525-1_6 |
0.79 |
|
| 2011 |
Khamassi M, Lallée S, Enel P, Procyk E, Dominey PF. Robot cognitive control with a neurophysiologically inspired reinforcement learning model. Frontiers in Neurorobotics. 5: 1. PMID 21808619 DOI: 10.3389/Fnbot.2011.00001 |
0.826 |
|
| 2010 |
Benchenane K, Peyrache A, Khamassi M, Tierney PL, Gioanni Y, Battaglia FP, Wiener SI. Coherent theta oscillations and reorganization of spike timing in the hippocampal- prefrontal network upon learning. Neuron. 66: 921-36. PMID 20620877 DOI: 10.1016/J.Neuron.2010.05.013 |
0.794 |
|
| 2010 |
Peyrache A, Benchenane K, Khamassi M, Wiener SI, Battaglia FP. Sequential Reinstatement of Neocortical Activity during Slow Oscillations Depends on Cells' Global Activity. Frontiers in Systems Neuroscience. 3: 18. PMID 20130754 DOI: 10.3389/Neuro.06.018.2009 |
0.76 |
|
| 2010 |
Peyrache A, Benchenane K, Khamassi M, Wiener SI, Battaglia FP. Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolution. Journal of Computational Neuroscience. 29: 309-25. PMID 19529888 DOI: 10.1007/S10827-009-0154-6 |
0.759 |
|
| 2010 |
Khamassi M, Quilodran R, Enel P, Procyk E, Dominey PF. A computational model of integration between reinforcement learning and task monitoring in the prefrontal cortex Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6226: 424-434. DOI: 10.1007/978-3-642-15193-4_40 |
0.76 |
|
| 2010 |
Benchenane K, Peyrache A, Khamassi M, Tierney PL, Douchamps V, Battaglia FP, Wiener SI. Coherent oscillations and learning-related reorganization of spike timing 4th International Conference On Cognitive Systems, Cogsys 2010. |
0.782 |
|
| 2009 |
Peyrache A, Khamassi M, Benchenane K, Wiener SI, Battaglia FP. Replay of rule-learning related neural patterns in the prefrontal cortex during sleep. Nature Neuroscience. 12: 919-26. PMID 19483687 DOI: 10.1038/Nn.2337 |
0.795 |
|
| 2008 |
Khamassi M, Mulder AB, Tabuchi E, Douchamps V, Wiener SI. Anticipatory reward signals in ventral striatal neurons of behaving rats. The European Journal of Neuroscience. 28: 1849-66. PMID 18973599 DOI: 10.1111/J.1460-9568.2008.06480.X |
0.82 |
|
| 2008 |
Battaglia FP, Peyrache A, Khamassi M, Wiener SI. Spatial Decisions and Neuronal Activity in Hippocampal Projection Zones in Prefrontal Cortex and Striatum Hippocampal Place Fields: Relevance to Learning and Memory. DOI: 10.1093/acprof:oso/9780195323245.003.0021 |
0.764 |
|
| 2008 |
Dollé L, Khamassi M, Girard B, Guillot A, Chavarriaga R. Analyzing interactions between navigation strategies using a computational model of action selection Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5248: 71-86. DOI: 10.1007/978-3-540-87601-4_8 |
0.776 |
|
| 2006 |
Khamassi M, Martinet LE, Guillot A. Combining self-organizing maps with mixtures of experts: Application to an actor-critic model of reinforcement learning in the basal ganglia Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4095: 394-405. |
0.654 |
|
| 2005 |
Khamassi M, Lachèze L, Girard B, Berthoz A, Guillot A. Actor-critic models of reinforcement learning in the basal ganglia: From natural to artificial rats Adaptive Behavior. 13: 131-148. DOI: 10.1177/105971230501300205 |
0.828 |
|
| 2005 |
Meyer JA, Guillot A, Girard B, Khamassi M, Pirim P, Berthoz A. The Psikharpax project: Towards building an artificial rat Robotics and Autonomous Systems. 50: 211-223. DOI: 10.1016/J.Robot.2004.09.018 |
0.815 |
|
| 2004 |
Zugaro MB, Arleo A, Déjean C, Burguière E, Khamassi M, Wiener SI. Rat anterodorsal thalamic head direction neurons depend upon dynamic visual signals to select anchoring landmark cues. The European Journal of Neuroscience. 20: 530-6. PMID 15233762 DOI: 10.1111/J.1460-9568.2004.03512.X |
0.768 |
|
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