Conserved structures of neural activity in sensorimotor cortex of freely moving rats allow cross-subject decoding

Abstract

Our knowledge about neuronal activity in the sensorimotor cortex relies primarily on stereotyped movements that are strictly controlled in experimental settings. It remains unclear how results can be carried over to less constrained behavior like that of freely moving subjects. Toward this goal, we developed a self-paced behavioral paradigm that encouraged rats to engage in different movement types. We employed bilateral electrophysiological recordings across the entire sensorimotor cortex and simultaneous paw tracking. These techniques revealed behavioral coupling of neurons with lateralization and an anterior–posterior gradient from the premotor to the primary sensory cortex. The structure of population activity patterns was conserved across animals despite the severe under-sampling of the total number of neurons and variations in electrode positions across individuals. We demonstrated cross-subject and cross-session generalization in a decoding task through alignments of low-dimensional neural manifolds, providing evidence of a conserved neuronal code.

Neuronal tuning to threat exposure remains stable in the mouse prefrontal cortex over multiple days

“…Our finding of a preserved structure of population activity both in time and across subjects bears similarity to and extends upon previous reports: Stable latent dynamics of population activity despite changing cell identities on different recording days have been observed in monkey motor cortex upon learning of a motor task [ 34 ]. Moreover, latent dynamics of population activity in motor cortex [ 35 ], orbitofrontal cortex [ 36 ], and hippocampus [ 37 – 39 ] are preserved across individuals executing learned tasks and appear in sensory-motor cortex during foraging for rewards [ 40 ]. Our results imply that stable and preserved population activity patterns are not restricted to cognitive or motor behaviors but that they also characterize the mPFC during innate stress coping.…”

Global motor dynamics - Invariant neural representations of motor behavior in distributed brain-wide recordings

“…To capture these dynamics into a low-dimensional representation, multiple techniques are available to reduce the neural space into a single manifold that describe the underlying neural dynamics [15][16][17][18][19][20] . Manifolds are demonstrated to capture robust representations of latent dynamics 21 and to be predictive for multiple types of behaviors 22,23 and subjects 24 . In the context of decoding motor behavior, these neural manifold approaches have almost exclusively been used to decode spiking activity recorded in the primary motor cortex, although the methods are well suited for local field potentials recorded with sEEG electrodes.…”