High-frequency oscillations in cortical networks have been linked to a variety of cognitive and perceptual processes. They have also been recorded in small cortical slices in vitro, indicating that neuronal synchronization at these frequencies is generated in the local cortical circuit. However, in vitro experiments have hitherto necessitated exogenous pharmacological or electrical stimulation to generate robust synchronized activity in the /␥ range. Here, we demonstrate that the isolated cortical microcircuitry generates  and ␥ oscillations spontaneously in the absence of externally applied neuromodulators or synaptic agonists. We show this in a spontaneously active slice preparation that engages in slow oscillatory activity similar to activity during slow-wave sleep.  and ␥ synchronization appeared during the up states of the slow oscillation. Simultaneous intracellular and extracellular recordings revealed synchronization between the timing of incoming synaptic events and population activity. This rhythm was mechanistically similar to pharmacologically induced ␥ rhythms, as it also included sparse, irregular firing of neurons within the population oscillation, predominant involvement of inhibitory neurons, and a decrease of oscillation frequency after barbiturate application. Finally, we show in a computer model how a synaptic loop between excitatory and inhibitory neurons can explain the emergence of both the slow (Ͻ1 Hz) and the -range oscillations in the neocortical network. We therefore conclude that oscillations in the /␥ range that share mechanisms with activity reported in vivo or in pharmacologically activated in vitro preparations can be generated during slow oscillatory activity in the local cortical circuit, even without exogenous pharmacological or electrical stimulation.
Neurons throughout the rat vibrissa somatosensory pathway are sensitive to the angular direction of whisker movement. Could this sensitivity help rats discriminate stimuli? Here we use a simple computational model of cortical neurons to analyze the robustness of directional selectivity. In the model, directional preference emerges from tuning of synaptic conductance amplitude and latency, as in recent experimental findings. We find that directional selectivity during stimulation with random deflection sequences is strongly dependent on the mean deflection frequency: Selectivity is weakened at high frequencies even when each individual deflection evokes strong directional tuning. This variability of directional selectivity is due to generic properties of synaptic integration by the neuronal membrane, and is therefore likely to hold under very general physiological conditions. Our results suggest that directional selectivity depends on stimulus context. It may participate in tasks involving brief whisker contact, such as detection of object position, but is likely to be weakened in tasks involving sustained whisker exploration (e.g., texture discrimination).
Local neocortical circuits are characterized by stereotypical physiological and structural features that subserve generic computational operations. These basic computations of the cortical microcircuit emerge through the interplay of neuronal connectivity, cellular intrinsic properties, and synaptic plasticity dynamics. How these interacting mechanisms generate specific computational operations in the cortical circuit remains largely unknown. Here, we identify the neurophysiological basis of both the rate of change and anticipation computations on synaptic inputs in a cortical circuit. Through biophysically realistic computer simulations and neuronal recordings, we show that the rate-of-change computation is operated robustly in cortical networks through the combination of two ubiquitous brain mechanisms: short-term synaptic depression and spike-frequency adaptation. We then show how this rate-of-change circuit can be embedded in a convergently connected network to anticipate temporally incoming synaptic inputs, in quantitative agreement with experimental findings on anticipatory responses to moving stimuli in the primary visual cortex. Given the robustness of the mechanism and the widespread nature of the physiological machinery involved, we suggest that rate-of-change computation and temporal anticipation are principal, hard-wired functions of neural information processing in the cortical microcircuit.
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