Becket Ebitz
- Professeur adjoint
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Faculté de médecine - Département de neurosciences
Pavillon Paul-G.-Desmarais
Profile
Research expertise
Becket Ebitz is the PI of the noiseLab in the Departement de neurosciences. The lab is interested in how our internal states (our goals, beliefs, expectations, and even arousal) shape how we perceive and interact with the world. Our work combines (1) behavioral experiments, (2) direct, intracranial recordings from large populations of neurons, and (3) powerful causal perturbations. We use a variety of sophisticated computational methods to make sense out of neural activity and behavior. Although we are a neuroscience lab, we enthusiastically incorporate tools and insight from disciplines like artificial intelligence, economics, robotics, and ethology.
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Affiliations and responsabilities
Research affiliations
Teaching and supervision
Teaching
Courses taught (current session only)
Programs
Projects
Research projects
Neuroscience of exploration
Union Neurosciences et Intelligence Artificielle Québec (UNIQUE)
Canada Research Chair in the Dynamics of Cognition
Interactions between cortical stimulation and prefrontal population dynamics
Physiological and neurophysiological mechanisms for exploration and mistakes
Physiological and neurophysiological mechanisms for exploration and mistakes
FlyRanch: A Platform for Uncovering the Molecular Bases of Hidden Behavioral State Dynamics
Jacobs Foundation Research Fellowship Becket Ebitz
Bioenergetics of the Braine, Body and Mind
Computational dissociation of the causes of cognitive rigidity in depression
Neurophysiologie cognitive et computationnelle de la prise de décision
Neurophysiologie cognitive et computationnelle de la prise de décision
Neuroscience of exploration
Data-driven discovery of continual learning algorithms from neural populations
Neuromodulatory Interventions to Regulate Flexibility in Brain and Behavior - Transfert de la subvention de l'Université du Minnesota
Outreach
Publications and presentations
Publications
Exploration and Learning
Wilson, R. C., Bonawitz, L., Costa, V. D., & Ebitz, R. B. (2021). “Balancing exploration and exploitation with information and randomization.” Current Opinion in Behavioral Sciences 38.
Chen, C. S.*, Ebitz, R. B.*, Bindas, S. R., Redish, A. D., Hayden, B. Y., & Grissom, N. M. (2020). “Divergent strategies for learning in males and females.” Current Biology 31(1).
Ebitz, R. B., Sleezer, B.J., Jedema, H.P., Bradberry, C.W., Hayden, B. Y. (2019). “Tonic exploration governs both flexibility and lapses.” PLoS Comp. Bio 15(11).
Ebitz, R. B., Albarran, E., & Moore, T. (2018). “Exploration disrupts choice predictive signals and alters population dynamics in prefrontal cortex.” Neuron 97 (2), 450-61.
Control Architectures
Ebitz, R. B., Tu, J. C. & Hayden, B. Y. (2020). “Rule adherence warps feature encoding in decision circuits.” PLoS Biology 18(11).
Ebitz, R. B. & Moore, T. (2019). “Both a gauge and a filter: Cognitive modulations of pupil size.” Frontiers in Neurology 9, 1190.
Ebitz, R. B. & Hayden, B. Y. (2021). “The population doctrine revolution in cognitive neuroscience.” Neuron, in press.
Ebitz, R. B., Moore, T. (2017). “Selective modulation of the pupil light reflex by microstimulation of prefrontal cortex.” Journal of Neuroscience 37 (19), 5008-18.
Ebitz, R. B. & Hayden, B. (2016). “Dorsal anterior cingulate: A Rorschach test for cognitive neuroscience.” Nature Neuroscience, 19, 1278–79.
Ebitz, R. B., Platt, M. L. (2015). “Neuronal activity in primate dorsal anterior cingulate cortex signals task conflict and predicts adjustments in pupil-linked arousal.” Neuron 85(3), 628-40.
Ebitz, R. B., Pearson, J., Platt, M. L. (2014). “Pupil size and social vigilance in rhesus macaques.” Frontiers in Neuroscience 8(100).
Ebitz, R. B., Watson, K. K., & Platt, M. L. (2013). “Oxytocin reduces social vigilance in rhesus macaques.” Proceedings of the National Academy of Sciences, 110(28), 11630-5.
Disciplines
- Neurosciences
- Psychology
- Biomedical Sciences
- Biology and Related Sciences
Areas of expertise
- Cognition
- Neuronal Systems
- Motivation, Emotions and Rewards
- Modelization and Simulation
- Neuronal Modeling
- Modeling of Learning Processes
- Learning and Memory (Psychology - Biological Aspects)