Hebbian crosstalk prevents nonlinear unsupervised learning
Learning is thought to occur by localized, activity-induced changes in the strength of synaptic connections between neurons. Recent work has shown that activity-dependent changes at one connection can affect changes at others ("crosstalk"). We studied the role of such crosstalk in nonlinea...
| Format: | Article |
|---|---|
| Language: | English |
| Published: |
Frontiers Media S.A.
2009-09-01
|
| Series: | Frontiers in Computational Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/neuro.10.011.2009/full |
| Summary: | Learning is thought to occur by localized, activity-induced changes in the strength of synaptic connections between neurons. Recent work has shown that activity-dependent changes 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 (ICA). 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. |
|---|---|
| ISSN: | 1662-5188 |