Organization of neural networks in the neocortex.

Abstract

Implanted semimicroelectrodes were used in conscious cats to record spike discharges from groups of close-lying neurons, i.e., multineuron activity, in the deep layers of the frontal and motor areas of the cortex at different levels of food motivation. Spike activity was extracted from 4-7 neurons and interneuronal interactions were studied by cross-correlation analysis between neighboring neurons in each zone (local networks) and between neurons in two zones (distributed networks) with analysis epochs of 0-100 msec. The results showed that neurons in local networks can be divided into two subgroups: neurons with high-amplitude spikes and a predominance of output (divergent) connections and neurons with low-amplitude spikes and a predominance of input (convergent) connections. Local networks are based on powerful monosynaptic connections (with delays of up to 2 msec) between large and small neurons. Most connections in distributed networks were between small neurons in local networks of the frontal cortex and large neurons in local networks in the motor cortex. Food deprivation for 24 h mainly affected late (with delays of 2-100 msec) cross-correlation interneuronal relationships in both local and distributed networks.