Abstract
We present a simplified binocular neural network model of the primary visual cortex with separate ON/OFF-pathways and modifiable afferent as well as intracortical synaptic couplings. Natural image stimuli drive the weight adaptation which follows Hebbian learning rules stabilized with constant norm and constant sum constraints. The simulations consider the development of orientation selective ...
Abstract
We present a simplified binocular neural network model of the primary visual cortex with separate ON/OFF-pathways and modifiable afferent as well as intracortical synaptic couplings. Natural image stimuli drive the weight adaptation which follows Hebbian learning rules stabilized with constant norm and constant sum constraints. The simulations consider the development of orientation selective cortical cells and orientation maps under different conditions concerning stimulus patterns and lateral couplings. Strong short range excitatory lateral connections emerge between individual cortical neurons with inhibitory couplings being less specific and rather diffuse.
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