Conjoint specification of action by neocortex and striatum

Abstract

The interplay between two major forebrain structures - cortex and subcortical striatum - is critical for flexible, goal-directed action. Traditionally, it has been proposed that striatum is critical for selecting what type of action is initiated while the primary motor cortex is involved in the online control of movement execution. Recent data indicates that striatum may also be critical for specifying movement execution. These alternatives have been difficult to reconcile because when comparing very distinct actions, as in the vast majority of work to date, they make essentially indistinguishable predictions. Here, we develop quantitative models to reveal a somewhat paradoxical insight: only comparing neural activity during similar actions makes strongly distinguishing predictions. We thus developed a novel reach-to-pull task in which mice reliably selected between two similar, but distinct reach targets and pull forces. Simultaneous cortical and subcortical recordings were uniquely consistent with a model in which cortex and striatum jointly specify flexible parameters of action during movement execution.One sentence summaryMotor cortex and subcortical striatum act in concert to specify the movement parameters of a reach-to-pull action in mice.

Nonlinear manifolds underlie neural population activity during behaviour

“…The monkeys reached to eight different targets by producing a relatively large variety of muscle activation patterns 74,75 , including arm flexion and extension. The mice, in contrast, reached in only one direction-away from the body 14,47 . Thus, the mice performed a far simpler behaviour and thus their neural activity may have explored only a small portion of the motor cortical state space.…”

“…We further confirmed the link between circuit connectivity and manifold nonlinearity experimentally. Neural manifolds from the architecturally distinct mouse motor cortex and dorsolateral striatum showed different degrees of nonlinearity during the same behaviour even while providing comparable predictions of movement kinematics 14,47 . Based on our RNN results, we argue that this difference arises at least in part from their distinct cytoarchitecture [61][62][63][64] .…”

“…We analysed simultaneous motor cortical and striatal population recordings from four mice performing a reaching, grasping and pulling task 14,47 (Methods; Figure 4A,B) (motor cortical neurons: 54-96 depending on the session; average, 76±15, mean±s.d. ; striatal neurons: (62-106 depending on the session; average, 83±14, mean±s.d.).…”

“…There, manifolds underlying a broad range of attempted movements were much more nonlinear than those underlying a more limited repertoire. Next, we addressed our third hypothesis that manifold nonlinearity is determined by circuit properties through comparison of manifolds underlying the activity of simultaneously recorded populations from two cytoarchitecturally distinct motor regions of the mouse brain-motor cortex and the dorsolateral striatum-during a grasping and pulling task 14,47,48 . Manifold nonlinearity was indeed markedly different between these two regions, with striatal manifolds being much more nonlinear than motor cortical manifolds.…”

De novo motor learning creates structure in neural activity that shapes adaptation

“…Thus, our model is largely region-agnostic, and it is still unclear where these neural changes due to motor learning and adaptation may occur. Motor learning seems to be associated with activity changes across cortical regions such as the premotor cortex 5,6,29,64 , primary motor cortex 29,65,66 , parietal cortex 67,68 , as well as other structures such as the cerebellum [69][70][71] and perhaps even basal ganglia [72][73][74][75] . How these different regions interact to affect skill learning and adaptation is an ongoing area of study, and future work could use modular and area-specific networks that are constrained by neural data to tease apart their contributions [61][62][63] .…”