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We present a nonlinear field model based on linear couplings for inhibition effects in early vision. The model is fitted to data from single unit recordings in the primary visual cortex of the cat. We focus on the prominent effect that responses to second stimuli are amplified, reduced, or unaffected depending on the temporal and spatial distance of the stimuli. The model is adjusted using an elaborated...
There is a growing interest in using dynamic neural fields for modeling biological and technical systems, but constructive ways to set up such models are still missing. We discuss gradient-based, evolutionary and hybrid algorithms for data-driven adaptation of neural field parameters. The proposed methods are evaluated using artificial and neuro-physiological data.
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