Multiplicative Gain Modulation Arises Through Unsupervised Learning in a Predictive Coding Model of Cortical Function

Kris De Meyer, Michael W. Spratling
2011 Neural Computation  
The combination of two or more population-coded signals in a neural model of predictive coding can give rise to multiplicative gain modulation in the response properties of individual neurons. Synaptic weights generating these multiplicative response properties can be learned using an unsupervised, Hebbian, learning rule. The behaviour of the model is compared to empirical data on gaze-dependent gain modulation of cortical cells, and found to be in good agreement with a range of physiological
more » ... of physiological observations. Furthermore, it is demonstrated that the model can learn to represent a set of basis functions. The current paper thus connects an often-observed neurophysiological phenomenon and important neurocomputational principle (gain modulation) with an influential theory of brain operation (predictive coding).
doi:10.1162/neco_a_00130 pmid:21395434 fatcat:ffhvblababb6ffskdqp74bn6ea