BIOPHYSICAL CHARACTERIZATION OF V1 NEURONS

Understanding of the neural processing in a network as complex as the cortical circuits requires a detailed knowledge of its constituent neurons. A lot of research has been focussing on the connectivity between cells, synaptic facilitation and depression, and the resulting network behaviour. However cortical information processing depends not only on the connectivity, but also on cell-specific profiles of synaptic integration. Knowledge about the intrinsic electrophysiological characteristics of cortical cells is essential to understand what computations a cell is able to perform on its own. There is evidence for a great diversity of neuronal morphologies in the cortex, but it still unclear, how these different cell classes are related to different functional roles. In primary visual cortex (V1), cells are usually classified according to their receptive field type, neglecting the differences in their electrophysiological profiles. This classification is useful to investigate the thalamocortical afferents of cells. But to gain insights in cortical information processing, determining the input-output relationship of the component neurons is crucial. It can account for the responsiveness of a cell to different contrasts, the amount of contrast adaptation and various other phenomena. In this paper the intrinsic electrophysiological properties of cells in V1 of the cat were investigated and cells were classified into distinct groups. Passive and active membrane characteristics were quantified in order to perform a cluster analysis. Sinusoidal currents were injected to determine, how cells behave under more natural like conditions and how they are affected by the parameters previously obtained. The results are compared to currently established cell classification schemes and examined concerning possible functional implications of their biophysical properties.