Alessandro TORCINI | Exact neural mass model for synaptic-based working memory
Alessandro TORCINI (LPTM, Université de Cergy-Pontoise)
Laboratoire de Physique Théorique et Modélisation
Université de Cergy-Pontoise
Cergy-Pontoise, France
Abstract:
Working Memory (WM) is the ability to temporarily store and manipulate stimuli representations that are no longer available to the senses. We have developed an innovative coarse-grained population model able to mimic several operations associated to WM. The novelty of the model consists in reproducing exactly the dynamics of spiking neural networks with realistic synaptic plasticity composed of hundreds of thousands neurons in terms of a few macroscopic variables. These variables
give access to experimentally measurable quantities such as local field potentials and electroencephalografic signals. Memory operations are joined to sustained or transient oscillations emerging in different frequency bands, in accordance with experimental results for primate and
humans performing WM tasks. We have designed an architecture composed of many excitatory populations and a common inhibitory pool able to store and retain several memory items. The capacity of our multi-item architecture is around 3-5 items, a value corresponding to the WM capacities measured in many experiments. Furthermore, the maximal capacity is achievable only for presentation rates within an optimal frequency range. Finally, we have defined a measure of the memory load analogous to the event-related potentials employed to test humans’ WM capacity during visual memory tasks.
Link to the preprint : https://www.biorxiv.org/content/10.1101/2020.06.24.168880v2 Paper in press in PLOS Comp Biology