Synapses learn to utilize stochastic pre-synaptic release for the prediction of postsynaptic dynamics.

ABSTRACT: Synapses in the brain are highly noisy, which leads to a large trial-by-trial variability. Given how costly synapses are in terms of energy consumption these high levels of noise are surprising. Here we propose that synapses use noise to represent uncertainties about the somatic activity of the postsynaptic neuron. To show this, we developed a mathematical framework, in which the synapse as a whole interacts with the soma of the postsynaptic neuron in a similar way to an agent that is situated and behaves in an uncertain, dynamic environment. This framework suggests that synapses use an implicit internal model of the somatic membrane dynamics that is being updated by a synaptic learning rule, which resembles experimentally well-established LTP/LTD mechanisms. In addition, this approach ent

SUBMITTER: Kappel D 

PROVIDER: S-EPMC11534197 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature