Memory stacking in hierarchical networks

Tutkimustuotos: Lehtiartikkelivertaisarvioitu

Tutkijat

Organisaatiot

  • Leibniz Institute for Neurobiology

Kuvaus

Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to study how such hierarchical structures affect temporal binding in neural networks. We equipped individual units in different types of feed forward networks with local memory mechanisms storing recent inputs and observed how this affected the ability of the networks to process stimuli context dependently. Our findings illustrate that these local memories stack up in hierarchical structures and hence allow network units to exhibit selectivity to spectral sequences longer than the time spans of the local memories. We also illustrate that short-term synaptic plasticity is a potential local memory mechanism within the auditory cortex, and we show that it can bring robustness to context dependence against variation in the temporal rate of stimuli, while introducing nonlinearities to response profiles that are not well captured by standard linear spectrotemporal receptive field models. The results therefore indicate that short-term synaptic plasticity might provide hierarchically structured auditory cortex with computational capabilities important for robust representations of spectrotemporal patterns.

Yksityiskohdat

AlkuperäiskieliEnglanti
Sivut327-353
Sivumäärä27
JulkaisuNeural Computation
Vuosikerta28
Numero2
TilaJulkaistu - 1 helmikuuta 2016
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

ID: 1500877