Cortical sensory responses are highly variable across stimulus presentations. This variability can be correlated across neurons (due to some combination of dense intracortical connectivity, cortical activity level, and cortical state), with fundamental implications for population coding. Yet the interpretation of correlated response variability (or "noise correlation") has remained fraught with difficulty, in part because of the restriction to extracellular neuronal spike recordings. Here, we measured response variability and its correlation at the most microscopic level of electrical neural activity, the membrane potential, by obtaining dual whole cell recordings from pairs of cortical pyramidal neurons during visual processing in the turtle whole brain ex vivo preparation. We found that during visual stimulation, correlated variability adapts toward an intermediate level and that this correlation dynamic is likely mediated by intracortical mechanisms. A model network with external inputs, synaptic depression, and structure reproduced the observed dynamics of correlated variability. These results suggest that intracortical adaptation self-organizes cortical circuits toward a balanced regime at which correlated variability is maintained at an intermediate level.
NEW & NOTEWORTHY Correlated response variability has profound implications for stimulus encoding, yet our understanding of this phenomenon is based largely on spike data. Here, we investigate the dynamics and mechanisms of membrane potential-correlated variability (CC) in visual cortex with a combined experimental and computational approach. We observe a visually evoked increase in CC, followed by a fast return to baseline. Our results further suggest a link between this observation and the adaptation-mediated dynamics of emergent network phenomena.
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