Input and Output Gain Modulation by the Lateral Interhemispheric Network in Early Visual Cortex

• Autor(a) principal: Wunderle, Thomas
• Data de Publicação: 2015
• Outros Autores: Eriksson, David, Peiker, Christiane, Schmidt, Kerstin Erika
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRN
• Texto Completo: https://repositorio.ufrn.br/jspui/handle/123456789/23131
• topic: contrast gain; corpus callosum; lateral connection; primary visual cortex; response gain; reversible deactivation

Neurons in the cerebral cortex are constantly integrating different types of inputs. Dependent on their origin, these inputs can be modulatory in many ways and, for example, change the neuron's responsiveness, sensitivity, or selectivity. To investigate the modulatory role of lateral input from the same level of cortical hierarchy, we recorded in the primary visual cortex of cats while controlling synaptic input from the corresponding contralateral hemisphere by reversible deactivation. Most neurons showed a pronounced decrease in their response to a visual stimulus of different contrasts and orientations. This indicates that the lateral network acts via an unspecific gain-setting mechanism, scaling the output of a neuron. However, the interhemispheric input also changed the contrast sensitivity of many neurons, thereby acting on the input. Such a contrast gain mechanism has important implications because it extends the role of the lateral network from pure response amplification to the modulation of a specific feature. Interestingly, for many neurons, we found a mixture of input and output gain modulation. Based on these findings and the known physiology of callosal connections in the visual system, we developed a simple model of lateral interhemispheric interactions. We conclude that the lateral network can act directly on its target, leading to a sensitivity change of a specific feature, while at the same time it also can act indirectly, leading to an unspecific gain setting. The relative contribution of these direct and indirect network effects determines the outcome for a particular neuron.