Estimating null and potent modes of feedforward communication in a computational model of cortical activity

Abstract

Communication across anatomical areas of the brain is key to both sensory and motor processes. Dimensionality reduction approaches have shown that the covariation of activity across cortical areas follows well-delimited patterns. Some of these patterns fall within the "potent space" of neural interactions and generate downstream responses; other patterns fall within the "null space" and prevent the feedforward propagation of synaptic inputs. Despite growing evidence for the role of null space activity in visual processing as well as preparatory motor control, a mechanistic understanding of its neural origins is lacking. Here, we developed a mean-rate model that allowed for the systematic control of feedforward propagation by potent and null modes of interaction. In this model, altering the number of null modes led to no systematic changes in firing rates, pairwise correlations, or mean synaptic strengths across areas, making it difficult to characterize feedforward communication with common measures of functional connectivity. A novel measure termed the null ratio captured the proportion of null modes relayed from one area to another. Applied to simultaneous recordings of primate cortical areas V1 and V2 during image viewing, the null ratio revealed that feedforward interactions have a broad null space that may reflect properties of visual stimuli.

Differential kinematic coding in sensorimotor striatum across species-typical and learned behaviors reflects a difference in control

“…While both areas are active during locomotion 28,69,91 , neither is required for generating the repetitive movement patterns 39,69 . This has prompted the idea that neural activity are, in such circumstances, in the 'null-space' for brainstem-and spinal cord-generated behaviors, i.e., aligned with dynamics in the downstream control circuits in such a way that makes the activity ineffective in driving changes 69,[92][93][94] . Since the 'null-space' for a circuit likely depends on the state of the downstream control regions, the activity of its neurons should reflect ongoing behavior (i.e.…”