Yaroslav Felipe Kalle Kossio - Drifting assemblies for persistent memory
Channel: LiSNN.channel
Date: 2021-09-04

Learning in Spiking Neural Networks seminar series presents:

Speaker: Yaroslav Felipe Kalle Kossio [1]

Title: Drifting assemblies for persistent memory 

Abstract: Change is ubiquitous in living beings. In particular, the connectome and neural representations can change. Nevertheless behaviors and memories often persist over long times. In a standard model, associative memories are represented by assemblies of strongly interconnected neurons. For faithful storage these assemblies are assumed to consist of the same neurons over time. Here we propose a contrasting memory model with complete temporal remodeling of assemblies, based on experimentally observed changes of synapses and neural representations. The assemblies drift freely as noisy autonomous network activity or spontaneous synaptic turnover induce neuron exchange. The gradual exchange allows activity-dependent and homeostatic plasticity to conserve the representational structure and keep inputs, outputs and assemblies consistent. This leads to  persistent memory. Our findings  explain recent experimental results on temporal evolution of fear memory representations and suggest that memory systems need to be understood in their completeness as individual parts may constantly change.

Host: Learning in Spiking Neural Networks Initiative [2]

[1] https://scholar.google.de/citations?user=-2fN42oAAAAJ&hl=en
[2] https://www.uni-frankfurt.de/103796621/Learning_in_Spiking_Neural_Networks