Computational roles of plastic probabilistic synapses. (February 2019)

• Record Type: Journal Article
• Authors: Llera-Montero, Milton; Sacramento, João; Costa, Rui Ponte
• Is Part Of: Current opinion in neurobiology. Volume 54(2019)
• Page Start: 90
• Page End: 97
• Publication Date: 2019-02
• Subjects: Neurobiology -- Periodicals; 573.8
• DOI: 10.1016/j.conb.2018.09.002
• Languages: English
• ISSNs: 0959-4388

Abstract

Highlights: Computational and experimental research suggest that synapses adapt their transmission statistics during learning. Optimisation of probabilistic synapses occurs jointly in presynaptic and postsynaptic terminals during synaptic plasticity. Recent developments in statistical learning point to a reevaluation of the function of probabilistic synapses in cortical circuits. Insights on the biology of probabilistic synapses may inspire new learning algorithms. Abstract : The probabilistic nature of synaptic transmission has remained enigmatic. However, recent developments have started to shed light on why the brain may rely on probabilistic synapses. Here, we start out by reviewing experimental evidence on the specificity and plasticity of synaptic response statistics. Next, we overview different computational perspectives on the function of plastic probabilistic synapses for constrained, statistical and deep learning. We highlight that all of these views require some form of optimisation of probabilistic synapses, which has recently gained support from theoretical analysis of long-term synaptic plasticity experiments. Finally, we contrast these different computational views and propose avenues for future research. Overall, we argue that the time is ripe for a better understanding of the computational functions of probabilistic synapses.