Excitatory-inhibitory network in the visual cortex: psychophysical evidence. 1997

Y Adini, and D Sagi, and M Tsodyks
Department of Neurobiology, Brain Research, The Weizmann Institute of Science, Rehovot 76100, Israel.

At early stages in visual processing cells respond to local stimuli with specific features such as orientation and spatial frequency. Although the receptive fields of these cells have been thought to be local and independent, recent physiological and psychophysical evidence has accumulated, indicating that the cells participate in a rich network of local connections. Thus, these local processing units can integrate information over much larger parts of the visual field; the pattern of their response to a stimulus apparently depends on the context presented. To explore the pattern of lateral interactions in human visual cortex under different context conditions we used a novel chain lateral masking detection paradigm, in which human observers performed a detection task in the presence of different length chains of high-contrast-flanked Gabor signals. The results indicated a nonmonotonic relation of the detection threshold with the number of flankers. Remote flankers had a stronger effect on target detection when the space between them was filled with other flankers, indicating that the detection threshold is caused by dynamics of large neuronal populations in the neocortex, with a major interplay between excitation and inhibition. We considered a model of the primary visual cortex as a network consisting of excitatory and inhibitory cell populations, with both short- and long-range interactions. The model exhibited a behavior similar to the experimental results throughout a range of parameters. Experimental and modeling results indicated that long-range connections play an important role in visual perception, possibly mediating the effects of context.

UI MeSH Term Description Entries
D008962 Models, Theoretical Theoretical representations that simulate the behavior or activity of systems, processes, or phenomena. They include the use of mathematical equations, computers, and other electronic equipment. Experimental Model,Experimental Models,Mathematical Model,Model, Experimental,Models (Theoretical),Models, Experimental,Models, Theoretic,Theoretical Study,Mathematical Models,Model (Theoretical),Model, Mathematical,Model, Theoretical,Models, Mathematical,Studies, Theoretical,Study, Theoretical,Theoretical Model,Theoretical Models,Theoretical Studies
D005246 Feedback A mechanism of communication within a system in that the input signal generates an output response which returns to influence the continued activity or productivity of that system. Feedbacks
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D014793 Visual Cortex Area of the OCCIPITAL LOBE concerned with the processing of visual information relayed via VISUAL PATHWAYS. Area V2,Area V3,Area V4,Area V5,Associative Visual Cortex,Brodmann Area 18,Brodmann Area 19,Brodmann's Area 18,Brodmann's Area 19,Cortical Area V2,Cortical Area V3,Cortical Area V4,Cortical Area V5,Secondary Visual Cortex,Visual Cortex Secondary,Visual Cortex V2,Visual Cortex V3,Visual Cortex V3, V4, V5,Visual Cortex V4,Visual Cortex V5,Visual Cortex, Associative,Visual Motion Area,Extrastriate Cortex,Area 18, Brodmann,Area 18, Brodmann's,Area 19, Brodmann,Area 19, Brodmann's,Area V2, Cortical,Area V3, Cortical,Area V4, Cortical,Area V5, Cortical,Area, Visual Motion,Associative Visual Cortices,Brodmanns Area 18,Brodmanns Area 19,Cortex Secondary, Visual,Cortex V2, Visual,Cortex V3, Visual,Cortex, Associative Visual,Cortex, Extrastriate,Cortex, Secondary Visual,Cortex, Visual,Cortical Area V3s,Extrastriate Cortices,Secondary Visual Cortices,V3, Cortical Area,V3, Visual Cortex,V4, Area,V4, Cortical Area,V5, Area,V5, Cortical Area,V5, Visual Cortex,Visual Cortex Secondaries,Visual Cortex, Secondary,Visual Motion Areas

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