Neural responses are typically characterized by computing the mean firing rate. Yet response variability can exist across trials. Many studies have examined the impact of a stimulus on the mean response, yet few have examined the impact on response variability. We measured neural variability in 13 extracellularly-recorded datasets and one intracellularly-recorded dataset from 7 areas spanning the four cortical lobes. In every case, stimulus onset caused a decline in neural variability. This occurred even when the stimulus produced little change in mean firing rate. The variability decline was observable in membrane potential recordings, in the spiking of individual neurons, and in correlated spiking variability measured with implanted 96-electrode arrays. The variability decline was observed for all stimuli tested, regardless of whether the animal was awake, behaving, or anaesthetized. This widespread variability decline suggests a rather general property of cortex: that its state is stabilized by an input.

How can neural activity propagate through cortical networks built with weak, stochastic synapses? We find precise repetitions of spontaneous patterns of synaptic inputs in neocortical neurons in vivo and in vitro. These patterns repeat after minutes, maintaining millisecond accuracy. Calcium imaging of slices reveals reactivation of sequences of cells during the occurrence of repeated intracellular synaptic patterns. The spontaneous activity drifts with time, engaging different cells. Sequences of active neurons have distinct spatial structures and are repeated in the same order over tens of seconds, revealing modular temporal dynamics. Higher order sequences are replayed with compressed timing.

The input conductance of cells in the cat primary visual cortex (V1) has been shown recently to grow substantially during visual stimulation. Because increasing conductance can have a divisive effect on the synaptic input, theoretical proposals have ascribed to it specific functions. According to the veto model, conductance increases would serve to sharpen orientation tuning by increasing most at off-optimal orientations. According to the normalization model, conductance increases would control the cell's gain, by being independent of stimulus orientation and by growing with stimulus contrast. We set out to test these proposals and to determine the visual properties and possible synaptic origin of the conductance increases. We recorded the membrane potential of cat V1 cells while injecting steady currents and presenting drifting grating patterns of varying contrast and orientation. Input conductance grew with stimulus contrast by 20-300%, generally more in simple cells (40-300%) than in complex cells (20-120%), and in simple cells was strongly modulated in time. Conductance was invariably maximal for stimuli of the preferred orientation. Thus conductance changes contribute to a gain control mechanism, but the strength of this gain control does not depend uniquely on contrast. By assuming that the conductance changes are entirely synaptic, we further derived the excitatory and inhibitory synaptic conductances underlying the visual responses. In simple cells, these conductances were often arranged in push-pull: excitation increased when inhibition decreased and vice versa. Excitation and inhibition had similar preferred orientations and did not appear to differ in tuning width, suggesting that the intracortical synaptic inputs to simple cells of cat V1 originate from cells with similar orientation tuning. This finding is at odds with models where orientation tuning in simple cells is achieved by inhibition at off-optimal orientations or sharpened by inhibition that is more broadly tuned than excitation.

SUMMARY In what regime does the cortical circuit operate? Our intracellular studies of surround suppression in cat primary visual cortex (V1) provide strong evidence on this question. Although suppression has been thought to arise from an increase in lateral inhibition, we find that the inhibition that cells receive is reduced, not increased, by a surround stimulus. Instead, suppression is mediated by a withdrawal of excitation. Thalamic recordings and previous work show that these effects cannot be explained by a withdrawal of thalamic input. We find in theoretical work that this behavior can only arise if V1 operates as an inhibition-stabilized network (ISN), in which excitatory recurrence alone is strong enough to destabilize visual responses but feedback inhibition maintains stability. We confirm two strong tests of this scenario experimentally, and show through simulation that observed cell-to-cell variability in surround effects, from facilitation to suppression, can arise naturally from variability in the ISN.

The origin of orientation selectivity in the responses of simple cells in cat visual cortex serves as a model problem for understanding cortical circuitry and computation. The feed-forward model posits that this selectivity arises simply from the arrangement of thalamic inputs to a simple cell. Much evidence, including a number of recent intracellular studies, supports a primary role of the thalamic inputs in determining simple cell response properties, including orientation tuning. This mechanism alone, however, cannot explain the invariance of orientation tuning to changes in stimulus contrast. Simple cells receive push-pull inhibition: ON inhibition in OFF subregions and vice versa. Addition of such inhibition to the feed-forward model can account for this contrast invariance, provided the inhibition is sufficiently strong. The predictions of "normalization" and "feedback" models are reviewed and compared with the predictions of this modified feed-forward model and with experimental results. The modified feed-forward and the feedback models ascribe fundamentally different functions to cortical processing.