Resonance with subthreshold oscillatory drive organizes activity and optimizes learning in neural networks.

ABSTRACT: Network oscillations across and within brain areas are critical for learning and performance of memory tasks. While a large amount of work has focused on the generation of neural oscillations, their effect on neuronal populations' spiking activity and information encoding is less known. Here, we use computational modeling to demonstrate that a shift in resonance responses can interact with oscillating input to ensure that networks of neurons properly encode new information represented in external inputs to the weights of recurrent synaptic connections. Using a neuronal network model, we find that due to an input current-dependent shift in their resonance response, individual neurons in a network will arrange their phases of firing to represent varying strengths of their respective inputs.

SUBMITTER: Roach JP 

PROVIDER: S-EPMC5879670 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature