Conference in French: Puzzles about long-term memory and learning
by Vincent HAKIM
3 June 2019 - 3 June 2019
Paris, France
Abstract:
Synapses are important biological structures that serve to transmit information between neurons and are thought to be the sites of learning and memory. Yet, it remains enigmatic how memory can be retained for years while synaptic components turnover over the course of hours. Similarly, when learning a complex task, the received feedback seems most often global and poorly informative. It is then quite unclear how the strengths of numerous different synapses can be properly adjusted, the so-called « credit-assignment problem ». After recalling some elements of synapse biophysics and relevant experimental findings, I will discuss our recent work in collaboration with the teams of A. Triller and B. Barbour at IBENS, aiming at addressing these two puzzles.
References:
An aggregation-removal model for the formation and size determination of post-synaptic scaffold domains. Ranft J, Almeida LG, Rodriguez PC, Triller A, Hakim V. PLoS Comput Biol. 2017 Apr 24;13(4): e1005516. doi:10.1371/journal.pcbi.1005516.
Cerebellar learning using perturbations. Bouvier G, Aljadeff J, Clopath C, Bimbard C, Ranft J, Blot A, Nadal JP, Brunel N, Hakim V, Barbour B. Elife. 2018 Nov 12;7. pii: e31599. doi:10.7554/eLife.31599.
Synapses are important biological structures that serve to transmit information between neurons and are thought to be the sites of learning and memory. Yet, it remains enigmatic how memory can be retained for years while synaptic components turnover over the course of hours. Similarly, when learning a complex task, the received feedback seems most often global and poorly informative. It is then quite unclear how the strengths of numerous different synapses can be properly adjusted, the so-called « credit-assignment problem ». After recalling some elements of synapse biophysics and relevant experimental findings, I will discuss our recent work in collaboration with the teams of A. Triller and B. Barbour at IBENS, aiming at addressing these two puzzles.
References:
An aggregation-removal model for the formation and size determination of post-synaptic scaffold domains. Ranft J, Almeida LG, Rodriguez PC, Triller A, Hakim V. PLoS Comput Biol. 2017 Apr 24;13(4): e1005516. doi:10.1371/journal.pcbi.1005516.
Cerebellar learning using perturbations. Bouvier G, Aljadeff J, Clopath C, Bimbard C, Ranft J, Blot A, Nadal JP, Brunel N, Hakim V, Barbour B. Elife. 2018 Nov 12;7. pii: e31599. doi:10.7554/eLife.31599.