Inferring Synaptic Plasticity Rules in Cortical Circuits from in Vivo Data


Sukbin Lim, Neural Science, NYU Shanghai


2018.06.05 14:00-15:00


601 Pao Yue-Kong Library


Reorganization of neuronal circuits through experience-dependent modification of synaptic connections has been thought to be one of the basic mechanisms for learning and memory. This idea is supported by in-vitro experimental works that show long-term changes of synaptic strengths in different slice preparations. However, a single neuron receives inputs from many neurons in cortical circuits, and it is difficult to identify the rule governing synaptic plasticity of an individual synapse from in vivo studies.

In this talk, I would discuss a novel method to infer synaptic plasticity rules and principles of neural dynamics from neural activities obtained in vivo. The method was applied to the data obtained in monkeys performing visual learning tasks. This study can connect several experimental works of learning and long-term memory at cellular and system level, and could be applicable to other cortical circuits to further our understanding the interactions between circuit dynamics and synaptic plasticity rules.