Year: 1994
Type: book-chapter
Abstract: Almost all models of orientation and direction selectivity in visual cortex are based on feedforward connection schemes, where geniculate input provides all excitation to both pyramidal and inhibitory \nneurons. The latter neurons then suppress the response of the former for non-optimal stimuli. However, anatomical studies show that up to 90 % of the excitatory synaptic input onto any cortical cell is provided by other cortical cells. The massive excitatory feedback nature of cortical circuits is embedded in the canonical \nmicrocircuit of Douglas &. Martin (1991). We here investigate analytically and through biologically realistic simulations the functioning of a detailed model of this circuitry, operating in a hysteretic mode. In the model, weak geniculate input is dramatically amplified \nby intracortical excitation, while inhibition has a dual role: (i) to prevent the early geniculate-induced excitation in the null direction \nand (ii) to restrain excitation and ensure that the neurons \nfire only when the stimulus is in their receptive-field. Among the cortical function, paralleling proposals for short-term memory, and strong limitations on linearity tests that use gratings. Properties \nof visual cortical neurons are compared in detail to this model and to a classical model of direction selectivity that does not include excitatory corti co-cortical connections. The model explain a number \nof puzzling features of direction-selective simple cells, including the small somatic input conductance changes that have been measured experimentally during stimulation in the null direction. The model also allows us to understand why the velocity-response curve of area 17 neurons is different from that of their LG N afferents, \nand the origin of expansive and compressive nonlinearities in the contrast-response curve of striate cortical neurons.
Institutions: California Institute of Technology, University of Oxford
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2104639290