Strong and localized recurrence controls the dimensionality of neural activity across brain areas

The brain contains an astronomical number of neurons, but it is their collective activity that underlies brain function. The number of degrees of freedom that this activity explores (its dimensionality) is therefore a fundamental signature of neural dynamics. However, it is not known what controls dimensionality in the biological brain. Through analysis of high-density Neuropixels recordings, here, we argue that areas across the mouse cortex predominantly operate in a sensitive regime that gives recurrent synaptic networks a strong role in regulating dimensionality. This control is expressed across time, as cortical activity transitions among states with different dimensionalities. Moreover, this control is mediated through highly tractable features of synaptic networks (network motifs). Analyzing a massive synaptic physiology dataset, we find that motifs impacting dimensionality are prevalent in both mouse and human brains. Thus, local circuitry scales up systematically to help control the degrees of freedom that brain networks may explore and exploit.