The effect of intracortical competition on the formation of topographic maps in models of Hebbian learning |
| |
Authors: | C Piepenbrock K Obermayer |
| |
Institution: | Fachbereich Informatik, Technische Universit?t Berlin, FR2-1, Franklinstrasse 28/29, D-10587 Berlin, Germany, DE
|
| |
Abstract: | Correlation-based learning (CBL) models and self-organizing maps (SOM) are two classes of Hebbian models that have both been
proposed to explain the activity-driven formation of cortical maps. Both models differ significantly in the way lateral cortical
interactions are treated, leading to different predictions for the formation of receptive fields. The linear CBL models predict
that receptive field profiles are determined by the average values and the spatial correlations of the second order of the
afferent activity patterns, wheras SOM models map stimulus features. Here, we investigate a class of models which are characterized
by a variable degree of lateral competition and which have the CBL and SOM models as limit cases. We show that there exists
a critical value for intracortical competition below which the model exhibits CBL properties and above which feature mapping
sets in. The class of models is then analyzed with respect to the formation of topographic maps between two layers of neurons.
For Gaussian input stimuli we find that localized receptive fields and topographic maps emerge above the critical value for
intracortical competition, and we calculate this value as a function of the size of the input stimuli and the range of the
lateral interaction function. Additionally, we show that the learning rule can be derived via the optimization of a global
cost function in a framework of probabilistic output neurons which represent a set of input stimuli by a sparse code.
Received: 23 June 1999 / Accepted in revised form: 05 November 1999 |
| |
Keywords: | |
本文献已被 PubMed SpringerLink 等数据库收录! |
|