Online control of reach accuracy in mice.

Reaching movements, as a basic yet complex motor behavior, are a foundational model system in neuroscience. In particular, there has been a significant recent expansion of investigation into the neural circuit mechanisms of reach behavior in mice. Nevertheless, quantification of mouse reach kinematics remains lacking, limiting comparison to the primate literature. In this study, we quantitatively demonstrate the homology of mouse reach kinematics to primate reach and also discover novel late-phase correlational structure that implies online control. Overall, our results highlight the decelerative phase of reach as important in driving successful outcome. Specifically, we develop and implement a novel statistical machine-learning algorithm to identify kinematic features associated with successful reaches and find that late-phase kinematics are most predictive of outcome, signifying online reach control as opposed to preplanning. Moreover, we identify and characterize late-phase kinematic adjustments that are yoked to midflight position and velocity of the limb, allowing for dynamic correction of initial variability, with head-fixed reaches being less dependent on position in comparison to freely behaving reaches. Furthermore, consecutive reaches exhibit positional error correction but not hot-handedness, implying opponent regulation of motor variability. Overall, our results establish foundational mouse reach kinematics in the context of neuroscientific investigation, characterizing mouse reach production as an active process that relies on dynamic online control mechanisms.NEW & NOTEWORTHY Mice use reaching movements to grasp and manipulate objects in their environment, similar to primates. To better establish mouse reach as a model for motor control, we implement several analytical frameworks, from basic kinematic relationships to statistical machine learning, to quantify mouse reach, finding many canonical features of primate reaches are conserved in mice, as well as evidence for midflight course corrections, expanding the utility of mouse reach paradigms for motor control studies.

Cerebellar associative learning underlies skilled reach adaptation.

The cerebellum is hypothesized to refine movement through online adjustments. We examined how such predictive control may be generated using a mouse reach paradigm, testing whether the cerebellum uses within-reach information as a predictor to adjust reach kinematics. We first identified a population-level response in Purkinje cells that scales inversely with reach velocity, pointing to the cerebellar cortex as a potential site linking kinematic predictors and anticipatory control. Next, we showed that mice can learn to compensate for a predictable reach perturbation caused by repeated, closed-loop optogenetic stimulation of pontocerebellar mossy fiber inputs. Both neural and behavioral readouts showed adaptation to position-locked mossy fiber perturbations and exhibited aftereffects when stimulation was removed. Surprisingly, position-randomized stimulation schedules drove partial adaptation but no opposing aftereffects. A model that recapitulated these findings suggests that the cerebellum may decipher cause-and-effect relationships through time-dependent generalization mechanisms.

A dual Purkinje cell rate and synchrony code sculpts reach kinematics.

Cerebellar Purkinje cells (PCs) encode movement kinematics in their population firing rates. Firing rate suppression is hypothesized to disinhibit neurons in the cerebellar nuclei, promoting adaptive movement adjustments. Debates persist, however, about whether a second disinhibitory mechanism, PC simple spike synchrony, is a relevant population code. We addressed this question by relating PC rate and synchrony patterns recorded with high density probes, to mouse reach kinematics. We discovered behavioral correlates of PC synchrony that align with a known causal relationship between activity in cerebellar output. Reach deceleration was positively correlated with both Purkinje firing rate decreases and synchrony, consistent with both mechanisms disinhibiting target neurons, which are known to adjust reach velocity. Direct tests of the contribution of each coding scheme to nuclear firing using dynamic clamp, combining physiological rate and synchrony patterns ex vivo, confirmed that physiological levels of PC simple spike synchrony are highly facilitatory for nuclear firing. These findings suggest that PC firing rate and synchrony collaborate to exert fine control of movement.

Presynaptic PRRT2 Deficiency Causes Cerebellar Dysfunction and Paroxysmal Kinesigenic Dyskinesia.

PRRT2 loss-of-function mutations have been associated with familial paroxysmal kinesigenic dyskinesia (PKD), infantile convulsions and choreoathetosis, and benign familial infantile seizures. Dystonia is the foremost involuntary movement disorder manifest by patients with PKD. Using a lacZ reporter and quantitative reverse-transcriptase PCR, we mapped the temporal and spatial distribution of Prrt2 in mouse brain and showed the highest levels of expression in cerebellar cortex. Further investigation into PRRT2 localization within the cerebellar cortex revealed that Prrt2 transcripts reside in granule cells but not Purkinje cells or interneurons within cerebellar cortex, and PRRT2 is presynaptically localized in the molecular layer. Analysis of synapses in the cerebellar molecular layer via electron microscopy showed that Prrt2-/- mice have increased numbers of docked vesicles but decreased vesicle numbers overall. In addition to impaired performance on several motor tasks, approximately 5% of Prrt2-/- mice exhibited overt PKD with clear face validity manifest as dystonia. In Prrt2 mutants, we found reduced parallel fiber facilitation at parallel fiber-Purkinje cell synapses, reduced Purkinje cell excitability, and normal cerebellar nuclear excitability, establishing a potential mechanism by which altered cerebellar activity promotes disinhibition of the cerebellar nuclei, driving motor abnormalities in PKD. Overall, our findings replicate, refine, and expand upon previous work with PRRT2 mouse models, contribute to understanding of paroxysmal disorders of the nervous system, and provide mechanistic insight into the role of cerebellar cortical dysfunction in dystonia.