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Poster
in
Workshop: Memory in Artificial and Real Intelligence (MemARI)

Exploring The Precision of Real Intelligence Systems at Synapse Resolution

Mohammad Samavat · Tom Bartol · Kristen Harris · Terrence Sejnowski

Keywords: [ hippocampus ] [ Learning and Memory ] [ Synaptic Plasticity ] [ Statistics ]


Abstract:

Synapses are the fundamental units of storage of information in neural circuits and their structure and strength are being adjusted through synaptic plasticity. Hence, exploring different aspects of synaptic plasticity processes in the hippocampus is crucial to understanding mechanisms of learning and memory, improving artificial intelligence algorithms, and neuromorphic computers. The scope of this manuscript is to explore the precision of this synaptic plasticity. Here we measured the precision of multiple synaptic features (Spine head volume, post synaptic density, spine neck diameter, spine neck length and number of docked vesicles). We concluded by suggesting our proposal for the surrogate of synaptic weight/strength and formulating a new hypothesis on synaptic plasticity precision. Results shows synaptic plasticity is highly precise and sub cellular resources such as mitochondria have impact on it.

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