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

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 One-sentence summarySimilarities in neural population structures across the sensorimotor cortex enable generalization across animals in the decoding of unconstrained behavior. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/433869v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@4dffbborg.highwire.dtl.DTLVardef@d07d55org.highwire.dtl.DTLVardef@1d459eborg.highwire.dtl.DTLVardef@5b5d78_HPS_FORMAT_FIGEXP M_FIG Conserved structures of neural activity in freely moving rats allow for cross-subject decoding. (a) We conducted electrophysiological recordings across the bilateral sensorimotor cortex of six freely moving rats. Neural activities were projected into a low-dimensional space with LEMs (22). (b) In a decoding task, points in the aligned low-dimensional neural state space were used as input for a classifier that predicted behavioral labels. Importantly, training and testing data originated from different rats. (c) Our procedure led to successful cross-subject generalization for sessions with sufficient numbers of recorded units. The rat and brain drawings are adapted from scalablebrainatlas.incf.org and SciDraw. C_FIG