Êtes-vous un étudiant de l'EPFL à la recherche d'un projet de semestre?
Travaillez avec nous sur des projets en science des données et en visualisation, et déployez votre projet sous forme d'application sur Graph Search.
Synaptic plasticity underlies the brain’s ability to learn and adapt. This process is often studied in small groups of neurons in vitro or indirectly through its effects on behavior in vivo. Due to the limitations of available experimental techniques, investigating synaptic plasticity at the micro-circuit level relies on simulation-based approaches. Although modeling studies provide valuable insights, they are usually limited in scale and generality. To overcome these limitations, we extended a previously published and validated large-scale cortical network model with a recently developed calcium-based model of functional plasticity between excitatory cells. We calibrated the network to mimic an in vivo state characterized by low synaptic release probability and low-rate asynchronous firing, and exposed it to ten different stimuli. We found that synaptic plasticity sparsely and specifically strengthened synapses forming spatial clusters on postsynaptic dendrites and those between populations of co-firing neurons, also known as cell assemblies: among 312 million synapses, only 5% experienced noticeable plasticity and cross-assembly synapses underwent three times more changes than average. Furthermore, as occasional large-amplitude potentiation was counteracted by more frequent synaptic depression, the network remained stable without explicitly modeling homeostatic plasticity. When comparing the network’s responses to the different stimuli before and after plasticity, we found that it became more stimulus-specific after plasticity, manifesting in prolonged activity after selected stimuli and more unique groups of neurons responding exclusively to a single pattern. Taken together, we present the first stable simulation of Hebbian plasticity without homeostatic terms at this level of detail and analyze the rules determining the sparse changes.
Matthias Wolf, Henry Markram, Felix Schürmann, Eilif Benjamin Muller, Srikanth Ramaswamy, Michael Reimann, Daniel Keller, Werner Alfons Hilda Van Geit, James Gonzalo King, Pramod Shivaji Kumbhar, Alexis Arnaudon, Jean-Denis Georges Emile Courcol, Rajnish Ranjan, Armando Romani, András Ecker, Michael Emiel Gevaert, Vishal Sood, Sirio Bolaños Puchet, James Bryden Isbister, Judit Planas Carbonell, Daniela Egas Santander, Maria Reva, Genrich Ivaska, Natali Barros Zulaica, Mustafa Anil Tuncel, Christoph Pokorny, Elvis Boci, Jorge Blanco Alonso, Aleksandra Zuzanna Teska, Darshan Mandge, Polina Litvak, Gianluca Ficarelli, Weina Ji, Giuseppe Chindemi, Christian Andreas Rössert, Omar Awile, Joni Henrikki Herttuainen, Samuel Lieven D. Lapere, Thomas Brice Delemontex, Tanguy Pierre Louis Damart, Alexander Dietz