Gabrielle Girardeau

Lab website

Dr Gabrielle Girardeau is a neurophysiologist who earned her degree in Biology from Pierre and Marie Curie University. She furthered her education with a master’s degree and completed her PhD in Paris. Her research focuses on the mechanisms of memory enhancement (episodic memory, emotional memory) during sleep, employing electrophysiological recordings in rodents and in vivo techniques for manipulating neural networks. After serving as a postdoctoral researcher at NYU Langone Medical Center in the Buzsaki Lab for 5 years, she established her own lab as a junior team leader at the Institut du Fer-à-Moulin in Paris (INSERM; National Institute for Health and Medical Research) in 2018.
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Neural mechanisms for emotional memory processing during sleep

The gradual reinforcement of memories, called “consolidation”, is a process occurring partially during sleep and mediated by various patterns of coordinated neural activity. The formation of contextualized emotional memories involves a large network of structures, among which the hippocampus and the baso-lateral amygdala (BLA) are central. In the dorsal hippocampus, fast oscillations (sharp-wave ripples) during non-REM sleep mediate the consolidation of spatial memories through the reactivation of place cell activity. On the other hand, emotional information is processed primarily in the ventral hippocampus and amygdala, which are reciprocally connected. Using large-scale electrophysiology in freely-moving rats, we investigate how the association of contextual and aversive information involves changes in neural synchronization at the level of local field potential and neuronal assemblies along the dorso-ventral hippocampus-BLA axis during Non-REM sleep.

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Gašper Tkačik

Lab website

Prof. Gašper Tkačik is a computational neuroscientist who earned his degree in physics in 2001 from the University of Ljubljana. He pursued further studies at Princeton University with William Bialek and Curtis Callan, earning a PhD in physics. Subsequently, he worked as a postdoctoral researcher at the University of Pennsylvania before founding his own group at the Institute of Science and Technology Austria. His research at IST Austria focuses on Information Processing in Biological Systems. His ongoing projects include investigating collective dynamics, visual encoding in the retina, genetic regulation during early embryogenesis, and the evolution of gene regulation.

Neural coding: from data to optimality theories

The question of how neural populations encode complex, high dimensional stimuli has presented us with an interesting playground where optimality theories meet statistical inference from large-scale neural recordings. In this talk, I will briefly outline our recent efforts to make this connection statistically rigorous, and present a few vignettes related to efficient coding. This influential optimality theory, originally put forward to explain neural responses in the sensory periphery, can be productively extended into new regimes relevant for central neural processing: adaptive coding in the primary visual cortex, texture coding in higher-order visual cortices, and place encoding in the hippocampus. Our results suggest that resource and noise constraints might strongly influence neural representations across the entire processing hierarchy, making them amenable to theoretical prediction.

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