Format

Send to:

Choose Destination
See comment in PubMed Commons below
Front Comput Neurosci. 2009 Sep 24;3:11. doi: 10.3389/neuro.10.011.2009. eCollection 2009.

Hebbian crosstalk prevents nonlinear unsupervised learning.

Author information

  • 1Department of Neurobiology, State University of New York Stony Brook Stony Brook, NY 11794, USA. kcox@notes.sunysb.edu

Abstract

Learning is thought to occur by localized, activity-induced changes in the strength of synaptic connections between neurons. Recent work has shown that induction of change at one connection can affect changes at others ("crosstalk"). We studied the role of such crosstalk in nonlinear Hebbian learning using a neural network implementation of independent components analysis. We find that there is a sudden qualitative change in the performance of the network at a threshold crosstalk level, and discuss the implications of this for nonlinear learning from higher-order correlations in the neocortex.

KEYWORDS:

Hebbian learning; ICA; LTP; LTP crosstalk; cortex; synaptic plasticity

PMID:
19826612
[PubMed]
PMCID:
PMC2759358
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Frontiers Media SA Icon for PubMed Central
    Loading ...
    Write to the Help Desk