Functional interactions among neurons within single columns of macaque V1

Recent developments in high-density neurophysiological tools now make it
possible to record from hundreds of single neurons within local, highly
interconnected neural networks. Among the many advantages of such
recordings is that they dramatically increase the quantity of
identifiable, functional interactions between neurons
thereby providing an unprecedented view of local circuits. Using
high-density, Neuropixels recordings from single neocortical columns of
primary visual cortex in nonhuman primates, we identified 1000s of
functionally interacting neuronal pairs using
established crosscorrelation approaches. Our results reveal clear and
systematic variations in the synchrony and strength of
functional interactions within single cortical columns.
Despite neurons residing within the same column, both measures
of interactions depended heavily on the vertical
distance separating neuronal pairs, as well as on the similarity of
stimulus tuning. In addition, we leveraged the statistical power afforded
by the large numbers of functionally interacting pairs
to categorize interactions between neurons based on
their crosscorrelation functions. These analyses identified distinct,
putative classes of functional interactions within the
full population. These classes of
functional interactions were corroborated by their
unique distributions across defined laminar compartments and were
consistent with known properties of V1 cortical circuitry, such as the
lead-lag relationship between simple and complex cells. Our results
provide a clear proof-of-principle for the use of high-density
neurophysiological recordings to assess circuit-level interactions within
local neuronal networks.