An Oscillatory Neural Autoencoder Based on Frequency Modulation and Multiplexing.

ABSTRACT: Oscillatory phenomena are ubiquitous in the brain. Although there are oscillator-based models of brain dynamics, their universal computational properties have not been explored much unlike in the case of rate-coded and spiking neuron network models. Use of oscillator-based models is often limited to special phenomena like locomotor rhythms and oscillatory attractor-based memories. If neuronal ensembles are taken to be the basic functional units of brain dynamics, it is desirable to develop oscillator-based models that can explain a wide variety of neural phenomena. Autoencoders are a special type of feed forward networks that have been used for construction of large-scale deep networks. Although autoencoders based on rate-coded and spiking neuron networks have been proposed, there are no a

SUBMITTER: Soman K 

PROVIDER: S-EPMC6048285 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature