In Silico Voltage-Sensitive Dye Imaging: A Model-Based Approach for Bridging Scales of Cortical Activity

An understanding of how microscale voltage fluctuations interact to shape mesoscale cortical information processing is lacking. Voltage-sensitive dye imaging (VSDI) is a powerful technique for interrogating membrane potential dynamics in assemblies of cortical neurons, but with effective resolution limits that can confound interpretation. To address this limitation, we developed an in silico model of VSDI in a detailed digital reconstruction of rodent neocortical microcircuitry. Using this model, we clarify and extend previous experimental findings regarding the cellular origins and spatiotemporal dynamics of VSDI signals. Furthermore, we test the capacity of VSD image sequences to discriminate between afferent thalamic inputs at various spatial locations to estimate a lower bound on the functional resolution of VSDI. In addition, we explore experimentally inaccessible circuit properties to show that during periods of spontaneous activity, membrane potential fluctuations are anticorrelated with population firing rates. This relationship is dependent on recurrent connectivity, which we demonstrate by manipulating network connections. Finally, we investigate how the reciprocity between population spiking and membrane potential is affected by long-range, extrinsic synaptic input by adding artificial excitatory synapses to a subpopulation of layer 5 neurons. Based on our findings, we suggest that the lag time of peak anticorrelation between the VSD signal and population firing rate reflects the degree of perturbing external influence on the local microcircuitry. Our approach reveals that VSDI is a richer source of information than previously appreciated and underscores the power of a bottom-up computational approach for relating scales of cortical processing