Mixed signal learning by spike correlation propagation in feedback inhibitory circuits.

ABSTRACT: The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning al

SUBMITTER: Hiratani N 

PROVIDER: S-EPMC4409403 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature