  Although neurons in columns of visual cortex of adult carnivores and primates
share similar orientation tuning preferences, responses of nearby neurons are
surprisingly sparse and temporally uncorrelated, especially in response to
complex visual scenes. The mechanisms underlying this counter-intuitive
combination of response properties are still unknown. Here we present a
computational model of columnar visual cortex which explains experimentally
observed integration of complex features across the visual field, and which is
consistent with anatomical and physiological profiles of cortical excitation
and inhibition. In this model, sparse local excitatory connections within
columns, coupled with strong unspecific local inhibition and
functionally-specific long-range excitatory connections across columns, give
rise to competitive dynamics that reproduce experimental observations. Our
results explain surround modulation of responses to simple and complex visual
stimuli, including reduced correlation of nearby excitatory neurons, increased
excitatory response selectivity, increased inhibitory selectivity, and complex
orientation-tuning of surround modulation.
