Somatosensory Cortex Plays an Essential Role in Forelimb Motor Adaptation in Mice

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, we exploited a recently developed non-invasive deep brain stimulation technique called transcranial temporal interference stimulation (tTIS) during reinforcement motor learning with concurrent neuroimaging, in a randomized, sham-controlled, double-blind study. Striatal tTIS applied at 80 Hz, but not at 20 Hz, abolished the benefits of reinforcement on motor learning. This effect was related to a selective modulation of neural activity within the striatum. Moreover, 80 Hz, but not 20 Hz, tTIS increased the neuromodulatory influence of the striatum on frontal areas involved in reinforcement motor learning. These results show that tTIS can non-invasively and selectively modulate a striatal mechanism involved in reinforcement learning, expanding our tools for the study of causal relationships between deep brain structures and human behaviour.

Corticospinal Modulation of Precision Movements

Recently we demonstrated a critical role for temporal coding of corticospinal activity in a prehension movement requiring precise forelimb control. Learning of precision isometric pull drives large-scale remodeling of corticospinal motor networks. Optogenetic modulation of corticospinal activity and full transection of the corticospinal tract disrupted critical functions of the network in expert animals resulting in impaired modulation of precise movements. In contrast, we observed more widespread corticospinal co-activation and limited temporal coding on a similar, yet more simplistic prehension task, adaptive isometric pull. Disrupting corticospinal neuron activity had much more limited effects on adaptive isometric pull, which was found to be corticospinal independent by transection of the corticospinal tract. Here we discuss these results in context of known roles for corticospinal and corticostriatal neurons in motor control, as well as some of the questions our study raised.

Exploration biases forelimb reaching strategies

The brain can generate actions, such as reaching to a target, using different movement strategies. We investigate how such strategies are learned in a task where perched head-fixed mice learn to reach to an invisible target area from a set start position using a joystick. This can be achieved by learning to move in a specific direction or to a specific endpoint location. As mice learn to reach the target, they refine their variable joystick trajectories into controlled reaches, which depend on the sensorimotor cortex. We show that individual mice learned strategies biased to either direction- or endpoint-based movements. This endpoint/direction bias correlates with spatial directional variability with which the workspace was explored during training. Model-free reinforcement learning agents can generate both strategies with similar correlation between variability during training and learning bias. These results provide evidence that reinforcement of individual exploratory behavior during training biases the reaching strategies that mice learn.

A theory of brain-computer interface learning via low-dimensional control

A remarkable demonstration of the flexibility of mammalian motor systems is primates' ability to learn to control brain-computer interfaces (BCIs). This constitutes a completely novel motor behavior, yet primates are capable of learning to control BCIs under a wide range of conditions. BCIs with carefully calibrated decoders, for example, can be learned with only minutes to hours of practice. With a few weeks of practice, even BCIs with randomly constructed decoders can be learned. What are the biological substrates of this learning process? Here, we develop a theory based on a re-aiming strategy, whereby learning operates within a low-dimensional subspace of task-relevant inputs driving the local population of recorded neurons. Through comprehensive numerical and formal analysis, we demonstrate that this theory can provide a unifying explanation for disparate phenomena previously reported in three different BCI learning tasks, and we derive a novel experimental prediction that we verify with previously published data. By explicitly modeling the underlying neural circuitry, the theory reveals an interpretation of these phenomena in terms of biological constraints on neural activity.

Integrating across behaviors and timescales to understand the neural control of movement

The nervous system evolved to enable navigation throughout the environment in the pursuit of resources. Evolutionarily newer structures allowed increasingly complex adaptations but necessarily added redundancy. A dominant view of movement neuroscientists is that there is a one-to-one mapping between brain region and function. However, recent experimental data is hard to reconcile with the most conservative interpretation of this framework, suggesting a degree of functional redundancy during the performance of well-learned, constrained behaviors. This apparent redundancy likely stems from the bidirectional interactions between the various cortical and subcortical structures involved in motor control. We posit that these bidirectional connections enable flexible interactions across structures that change depending upon behavioral demands, such as during acquisition, execution or adaptation of a skill. Observing the system across both multiple actions and behavioral timescales can help isolate the functional contributions of individual structures, leading to an integrated understanding of the neural control of movement.

Task-driven neural network models predict neural dynamics of proprioception

Proprioception tells the brain the state of the body based on distributed sensory neurons. Yet, the principles that govern proprioceptive processing are poorly understood. Here, we employ a task-driven modeling approach to investigate the neural code of proprioceptive neurons in cuneate nucleus (CN) and somatosensory cortex area 2 (S1). We simulated muscle spindle signals through musculoskeletal modeling and generated a large-scale movement repertoire to train neural networks based on 16 hypotheses, each representing different computational goals. We found that the emerging, task-optimized internal representations generalize from synthetic data to predict neural dynamics in CN and S1 of primates. Computational tasks that aim to predict the limb position and velocity were the best at predicting the neural activity in both areas. Since task optimization develops representations that better predict neural activity during active than passive movements, we postulate that neural activity in the CN and S1 is top-down modulated during goal-directed movements.

Prefrontal projections modulate recurrent circuitry in the insular cortex to support short-term memory

Short-term memory (STM) maintains information during a short delay period. How long-range and local connections interact to support STM encoding remains elusive. Here, we tackle the problem focusing on long-range projections from the medial prefrontal cortex (mPFC) to the anterior agranular insular cortex (aAIC) in head-fixed mice performing an olfactory delayed-response task. Optogenetic and electrophysiological experiments reveal the behavioral importance of the two regions in encoding STM information. Spike-correlogram analysis reveals strong local and cross-region functional coupling (FC) between memory neurons encoding the same information. Optogenetic suppression of mPFC-aAIC projections during the delay period reduces behavioral performance, the proportion of memory neurons, and memory-specific FC within the aAIC, whereas optogenetic excitation enhances all of them. mPFC-aAIC projections also bidirectionally modulate the efficacy of STM-information transfer, measured by the contribution of FC spiking pairs to the memory-coding ability of following neurons. Thus, prefrontal projections modulate insular neurons' functional connectivity and memory-coding ability to support STM.

μSim: A goal-driven framework for elucidating the neural control of movement through musculoskeletal modeling

How does the motor cortex (MC) produce purposeful and generalizable movements from the complex musculoskeletal system in a dynamic environment? To elucidate the underlying neural dynamics, we use a goal-driven approach to model MC by considering its goal as a controller driving the musculoskeletal system through desired states to achieve movement. Specifically, we formulate the MC as a recurrent neural network (RNN) controller producing muscle commands while receiving sensory feedback from biologically accurate musculoskeletal models. Given this real-time simulated feedback implemented in advanced physics simulation engines, we use deep reinforcement learning to train the RNN to achieve desired movements under specified neural and musculoskeletal constraints. Activity of the trained model can accurately decode experimentally recorded neural population dynamics and single-unit MC activity, while generalizing well to testing conditions significantly different from training. Simultaneous goal- and data- driven modeling in which we use the recorded neural activity as observed states of the MC further enhances direct and generalizable single-unit decoding. Finally, we show that this framework elucidates computational principles of how neural dynamics enable flexible control of movement and make this framework easy-to-use for future experiments.

The human somatosensory cortex contributes to the encoding of newly learned movements

Recent studies have indicated somatosensory cortex involvement in motor learning and retention. However, the nature of its contribution is unknown. One possibility is that the somatosensory cortex is transiently engaged during movement. Alternatively, there may be durable learning-related changes which would indicate sensory participation in the encoding of learned movements. These possibilities are dissociated by disrupting the somatosensory cortex following learning, thus targeting learning-related changes which may have occurred. If changes to the somatosensory cortex contribute to retention, which, in effect, means aspects of newly learned movements are encoded there, disruption of this area once learning is complete should lead to an impairment. Participants were trained to make movements while receiving rotated visual feedback. The primary motor cortex (M1) and the primary somatosensory cortex (S1) were targeted for continuous theta-burst stimulation, while stimulation over the occipital cortex served as a control. Retention was assessed using active movement reproduction, or recognition testing, which involved passive movements produced by a robot. Disruption of the somatosensory cortex resulted in impaired motor memory in both tests. Suppression of the motor cortex had no impact on retention as indicated by comparable retention levels in control and motor cortex conditions. The effects were learning specific. When stimulation was applied to S1 following training with unrotated feedback, movement direction, the main dependent variable, was unaltered. Thus, the somatosensory cortex is part of a circuit that contributes to retention, consistent with the idea that aspects of newly learned movements, possibly learning-updated sensory states (new sensory targets) which serve to guide movement, may be encoded there.

Quantifying motor adaptation in a sport-specific table tennis setting

Studies on motor adaptation aim to better understand the remarkable, largely implicit capacity of humans to adjust to changing environmental conditions. So far, this phenomenon has mainly been investigated in highly controlled laboratory setting, allowing only limited conclusions and consequences for everyday life scenarios. Natural movement tasks performed under externally valid conditions would provide important support on the transferability of recent laboratory findings. Therefore, one major goal of the current study was to create and assess a new table tennis paradigm mapping motor adaptation in a more natural and sport-specific setting. High-speed cinematographic measurements were used to determine target accuracy in a motor adaptation table tennis paradigm in 30 right-handed participants. In addition, we investigated if motor adaptation was affected by temporal order of perturbations (serial vs. random practice). In summary, we were able to confirm and reproduce typical motor adaptation effects in a sport-specific setting. We found, according to previous findings, an increase in target errors with perturbation onset that decreased during motor adaptation. Furthermore, we observed an increase in target errors with perturbation offset (after-effect) that decrease subsequently during washout phase. More importantly, this motor adaptation phenomenon did not differ when comparing serial vs. random perturbation conditions.

Disruption of somatosensory cortex impairs motor learning and retention

This study tests for a function of the somatosensory cortex, that, in addition to its role in processing somatic afferent information, somatosensory cortex contributes both to motor learning and the stabilization of motor memory. Continuous theta-burst magnetic stimulation (cTBS) was applied, before force-field training to disrupt activity in either the primary somatosensory cortex, primary motor cortex, or a control zone over the occipital lobe. Tests for retention and relearning were conducted after a 24 h delay. Analysis of movement kinematic measures and force-channel trials found that cTBS to somatosensory cortex disrupted both learning and subsequent retention, whereas cTBS to motor cortex had little effect on learning but possibly impaired retention. Basic movement variables are unaffected by cTBS suggesting that the stimulation does not interfere with movement but instead disrupts changes in the cortex that are necessary for learning. In all experimental conditions, relearning in an abruptly introduced force field, which followed retention testing, showed extensive savings, which is consistent with previous work suggesting that more cognitive aspects of learning and retention are not dependent on either of the cortical zones under test. Taken together, the findings are consistent with the idea that motor learning is dependent on learning-related activity in the somatosensory cortex.NEW & NOTEWORTHY This study uses noninvasive transcranial magnetic stimulation to test the contribution of somatosensory and motor cortex to human motor learning and retention. Continuous theta-burst stimulation is applied before learning; participants return 24 h later to assess retention. Disruption of the somatosensory cortex is found to impair both learning and retention, whereas disruption of the motor cortex has no effect on learning. The findings are consistent with the idea that motor learning is dependent upon learning-related plasticity in somatosensory cortex.

Layer 5 Intratelencephalic Neurons in the Motor Cortex Stably Encode Skilled Movement

The primary motor cortex (M1) and the dorsal striatum play a critical role in motor learning and the retention of learned behaviors. Motor representations of corticostriatal ensembles emerge during motor learning. In the coordinated reorganization of M1 and the dorsal striatum for motor learning, layer 5a (L5a) which connects M1 to the ipsilateral and contralateral dorsal striatum, should be a key layer. Although M1 L5a neurons represent movement-related activity in the late stage of learning, it is unclear whether the activity is retained as a memory engram. Here, using Tlx3-Cre male transgenic mice, we conducted two-photon calcium imaging of striatum-projecting L5a intratelencephalic (IT) neurons in forelimb M1 during late sessions of a self-initiated lever-pull task and in sessions after 6 d of nontraining following the late sessions. We found that trained male animals exhibited stable motor performance before and after the nontraining days. At the same time, we found that M1 L5a IT neurons strongly represented the well-learned forelimb movement but not uninstructed orofacial movements. A subset of M1 L5a IT neurons consistently coded the well-learned forelimb movement before and after the nontraining days. Inactivation of M1 IT neurons after learning impaired task performance when the lever was made heavier or when the target range of the pull distance was narrowed. These results suggest that a subset of M1 L5a IT neurons continuously represent skilled movement after learning and serve to fine-tune the kinematics of well-learned movement.SIGNIFICANCE STATEMENT Motor memory persists even when it is not used for a while. IT neurons in L5a of the M1 gradually come to represent skilled forelimb movements during motor learning. However, it remains to be determined whether these changes persist over a long period and how these neurons contribute to skilled movements. Here, we show that a subset of M1 L5a IT neurons retain information for skilled forelimb movements even after nontraining days. Furthermore, suppressing the activity of these neurons during skilled forelimb movements impaired behavioral stability and adaptability. Our results suggest the importance of M1 L5a IT neurons for tuning skilled forelimb movements over a long period.

Plantar somatosensory restoration enhances gait, speed perception, and motor adaptation

Lower limb loss is a major insult to the body's nervous and musculoskeletal systems. Despite technological advances in prosthesis design, artificial limbs are not yet integrated into the body's physiological systems. Therefore, lower limb amputees (LLAs) experience lower balance confidence, higher fear of falls, and impaired gait compared with their able-bodied peers (ABs). Previous studies have demonstrated that restored sensations perceived as originating directly from the missing limb via neural interfaces improve balance and performance in certain ambulatory tasks; however, the effects of such evoked sensations on neural circuitries involved in the locomotor activity are not well understood. In this work, we investigated the effects of plantar sensation elicited by peripheral nerve stimulation delivered by multicontact nerve cuff electrodes on gait symmetry and stability, speed perception, and motor adaptation. We found that restored plantar sensation increased stance time and propulsive force on the prosthetic side, improved gait symmetry, and yielded an enhanced perception of prosthetic limb movement. Our results show that the locomotor adaptation among LLAs with plantar sensation became similar to that of ABs. These findings suggest that our peripheral nerve-based approach to elicit plantar sensation directly affects central nervous pathways involved in locomotion and motor adaptation during walking. Our neuroprosthesis provided a unique model to investigate the role of somatosensation in the lower limb during walking and its effects on perceptual recalibration after a locomotor adaptation task. Furthermore, we demonstrated how plantar sensation in LLAs could effectively increase mobility, improve walking dynamics, and possibly reduce fall risks.

Brain-machine interface learning is facilitated by specific patterning of distributed cortical feedback

Neuroprosthetics offer great hope for motor-impaired patients. One obstacle is that fine motor control requires near-instantaneous, rich somatosensory feedback. Such distributed feedback may be recreated in a brain-machine interface using distributed artificial stimulation across the cortical surface. Here, we hypothesized that neuronal stimulation must be contiguous in its spatiotemporal dynamics to be efficiently integrated by sensorimotor circuits. Using a closed-loop brain-machine interface, we trained head-fixed mice to control a virtual cursor by modulating the activity of motor cortex neurons. We provided artificial feedback in real time with distributed optogenetic stimulation patterns in the primary somatosensory cortex. Mice developed a specific motor strategy and succeeded to learn the task only when the optogenetic feedback pattern was spatially and temporally contiguous while it moved across the topography of the somatosensory cortex. These results reveal spatiotemporal properties of the sensorimotor cortical integration that set constraints on the design of neuroprosthetics.

Dissociable roles of thalamic nuclei in the refinement of reaches to spatial targets

Reaches are complex movements that are critical for survival, and encompass the control of different aspects such as direction, speed, and endpoint precision. Complex movements have been postulated to be learned and controlled through distributed motor networks, of which the thalamus is a highly connected node. Still, the role of different thalamic circuits in learning and controlling specific aspects of reaches has not been investigated. We report dissociable roles of two distinct thalamic nuclei - the parafascicular (Pf) and ventroanterior/ventrolateral (VAL) nuclei - in the refinement of spatial target reaches in mice. Using 2-photon calcium imaging in a head-fixed joystick task where mice learned to reach to a target in space, we found that glutamatergic neurons in both areas were most active during reaches early in learning. Reach-related activity in both areas decreased late in learning, as movement direction was refined and reaches increased in accuracy. Furthermore, the population dynamics of Pf, but not VAL, covaried in different subspaces in early and late learning, but eventually stabilized in late learning. The neural activity in Pf, but not VAL, encoded the direction of reaches in early but not late learning. Accordingly, bilateral lesions of Pf before, but not after learning, strongly and specifically impaired the refinement of reach direction. VAL lesions did not impact direction refinement, but instead resulted in increased speed and target overshoot. Our findings provide new evidence that the thalamus is a critical motor node in the learning and control of reaching movements, with specific subnuclei controlling distinct aspects of the reach early in learning.

Activity in Barrel Cortex Related to Trace Eyeblink Conditioning

In mammals several memory systems are responsible for learning and storage of associative memory. Even apparently simple behavioral tasks, like pavlovian conditioning, have been suggested to engage, for instance, implicit and explicit memory processes. Here, we used single-whisker tactile trace eyeblink conditioning (TTEBC) to investigate learning and its neuronal bases in the mouse barrel column, the primary neocortical tactile representation of one whisker. Behavioral analysis showed that conditioned responses (CRs) are spatially highly restricted; they generalize from the principal whisker only to its direct neighbors. Within the respective neural representation, the principal column and its direct neighbors, spike activity showed a learning-related spike rate suppression starting during the late phase of conditioning stimulus (CS) presentation that was sustained throughout the stimulus-free trace period (Trace). Trial-by-trial analysis showed that learning-related activity was independent from the generation of eyelid movements within a trial, and set in around the steepest part of the learning curve. Optogenetic silencing of responses and their learning-related changes during CS and Trace epochs blocked CR acquisition but not its recall after learning. Silencing during the Trace alone, which carried major parts of the learning-related changes, had no effect. In summary, we demonstrate specific barrel column spike rate plasticity during TTEBC that can be partially decoupled from the CR, the learned eye closure, a hallmark of implicit learning. Our results, thus, point to a possible role of the barrel column in contributing to other kinds of memory as well.

Disentangling the role of NAc D1 and D2 cells in hedonic eating

Overeating is driven by both the hedonic component ('liking') of food, and the motivation ('wanting') to eat it. The nucleus accumbens (NAc) is a key brain center implicated in these processes, but how distinct NAc cell populations encode 'liking' and 'wanting' to shape overconsumption remains unclear. Here, we probed the roles of NAc D1 and D2 cells in these processes using cell-specific recording and optogenetic manipulation in diverse behavioral paradigms that disentangle reward traits of 'liking' and 'wanting' related to food choice and overeating in healthy mice. Medial NAc shell D2 cells encoded experience-dependent development of 'liking', while D1 cells encoded innate 'liking' during the first food taste. Optogenetic control confirmed causal links of D1 and D2 cells to these aspects of 'liking'. In relation to 'wanting', D1 and D2 cells encoded and promoted distinct aspects of food approach: D1 cells interpreted food cues while D2 cells also sustained food-visit-length that facilitates consumption. Finally, at the level of food choice, D1, but not D2, cell activity was sufficient to switch food preference, programming subsequent long-lasting overconsumption. By revealing complementary roles of D1 and D2 cells in consumption, these findings assign neural bases to 'liking' and 'wanting' in a unifying framework of D1 and D2 cell activity.

Similar somatotopy for active and passive digit representation in primary somatosensory cortex

Scientists traditionally use passive stimulation to examine the organisation of primary somatosensory cortex (SI). However, given the close, bidirectional relationship between the somatosensory and motor systems, active paradigms involving free movement may uncover alternative SI representational motifs. Here, we used 7 Tesla functional magnetic resonance imaging to compare hallmark features of SI digit representation between active and passive tasks which were unmatched on task or stimulus properties. The spatial location of digit maps, somatotopic organisation, and inter-digit representational structure were largely consistent between tasks, indicating representational consistency. We also observed some task differences. The active task produced higher univariate activity and multivariate representational information content (inter-digit distances). The passive task showed a trend towards greater selectivity for digits versus their neighbours. Our findings highlight that, while the gross features of SI functional organisation are task invariant, it is important to also consider motor contributions to digit representation.

Post-ischemic reorganization of sensory responses in cerebral cortex

Introduction

Sensorimotor integration is critical for generating skilled, volitional movements. While stroke tends to impact motor function, there are also often associated sensory deficits that contribute to overall behavioral deficits. Because many of the cortico-cortical projections participating in the generation of volitional movement either target or pass-through primary motor cortex (in rats, caudal forelimb area; CFA), any damage to CFA can lead to a subsequent disruption in information flow. As a result, the loss of sensory feedback is thought to contribute to motor dysfunction even when sensory areas are spared from injury. Previous research has suggested that the restoration of sensorimotor integration through reorganization or de novo neuronal connections is important for restoring function. Our goal was to determine if there was crosstalk between sensorimotor cortical areas with recovery from a primary motor cortex injury. First, we investigated if peripheral sensory stimulation would evoke responses in the rostral forelimb area (RFA), a rodent homologue to premotor cortex. We then sought to identify whether intracortical microstimulation-evoked activity in RFA would reciprocally modify the sensory response.

Methods

We used seven rats with an ischemic lesion of CFA. Four weeks after injury, the rats' forepaw was mechanically stimulated under anesthesia and neural activity was recorded in the cortex. In a subset of trials, a small intracortical stimulation pulse was delivered in RFA either individually or paired with peripheral sensory stimulation.

Results

Our results point to post-ischemic connectivity between premotor and sensory cortex that may be related to functional recovery. Premotor recruitment during the sensory response was seen with a peak in spiking within RFA after the peripheral solenoid stimulation despite the damage to CFA. Furthermore, stimulation in RFA modulated and disrupted the sensory response in sensory cortex.

Discussion

The presence of a sensory response in RFA and the sensitivity of S1 to modulation by intracortical stimulation provides additional evidence for functional connectivity between premotor and somatosensory cortex. The strength of the modulatory effect may be related to the extent of the injury and the subsequent reshaping of cortical connections in response to network disruption.

Contrasting action and posture coding with hierarchical deep neural network models of proprioception

Biological motor control is versatile, efficient, and depends on proprioceptive feedback. Muscles are flexible and undergo continuous changes, requiring distributed adaptive control mechanisms that continuously account for the body's state. The canonical role of proprioception is representing the body state. We hypothesize that the proprioceptive system could also be critical for high-level tasks such as action recognition. To test this theory, we pursued a task-driven modeling approach, which allowed us to isolate the study of proprioception. We generated a large synthetic dataset of human arm trajectories tracing characters of the Latin alphabet in 3D space, together with muscle activities obtained from a musculoskeletal model and model-based muscle spindle activity. Next, we compared two classes of tasks: trajectory decoding and action recognition, which allowed us to train hierarchical models to decode either the position and velocity of the end-effector of one's posture or the character (action) identity from the spindle firing patterns. We found that artificial neural networks could robustly solve both tasks, and the networks' units show tuning properties similar to neurons in the primate somatosensory cortex and the brainstem. Remarkably, we found uniformly distributed directional selective units only with the action-recognition-trained models and not the trajectory-decoding-trained models. This suggests that proprioceptive encoding is additionally associated with higher-level functions such as action recognition and therefore provides new, experimentally testable hypotheses of how proprioception aids in adaptive motor control.

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.

Task-specific modulation of corticospinal neuron activity during motor learning in mice

Motor skill learning relies on the plasticity of the primary motor cortex as task acquisition drives cortical motor network remodeling. Large-scale cortical remodeling of evoked motor outputs occurs during the learning of corticospinal-dependent prehension behavior, but not simple, non-dexterous tasks. Here we determine the response of corticospinal neurons to two distinct motor training paradigms and assess the role of corticospinal neurons in the execution of a task requiring precise modulation of forelimb movement and one that does not. In vivo calcium imaging in mice revealed temporal coding of corticospinal activity coincident with the development of precise prehension movements, but not more simplistic movement patterns. Transection of the corticospinal tract and optogenetic regulation of corticospinal activity show the necessity for patterned corticospinal network activity in the execution of precise movements but not simplistic ones. Our findings reveal a critical role for corticospinal network modulation in the learning and execution of precise motor movements.

Exploration biases how forelimb reaches to a spatial target are learned

The brain can learn to generate actions, such as reaching to a target, using different movement strategies. Understanding how different variables bias which strategies are learned to produce such a reach is important for our understanding of the neural bases of movement. Here we introduce a novel spatial forelimb target task in which perched head-fixed mice learn to reach to a circular target area from a set start position using a joystick. These reaches can be achieved by learning to move into a specific direction or to a specific endpoint location. We find that mice gradually learn to successfully reach the covert target. With time, they refine their initially exploratory complex joystick trajectories into controlled targeted reaches. The execution of these controlled reaches depends on the sensorimotor cortex. Using a probe test with shifting start positions, we show that individual mice learned to use strategies biased to either direction or endpoint-based movements. The degree of endpoint learning bias was correlated with the spatial directional variability with which the workspace was explored early in training. Furthermore, we demonstrate that reinforcement learning model agents exhibit a similar correlation between directional variability during training and learned strategy. These results provide evidence that individual exploratory behavior during training biases the control strategies that mice use to perform forelimb covert target reaches.

Machine-learning-based video analysis of grasping behavior during recovery from cervical spinal cord injury

Comprehensive characterizations of hand grasping behaviors after cervical spinal cord injuries are fundamental for developing rehabilitation strategies to promote recovery in spinal-cord-injured primates. We used the machine-learning-based video analysis software, DeepLabCut, to sensitively quantify kinematic aspects of grasping behavioral deficits in squirrel monkeys with C5-level spinal cord injuries. Three squirrel monkeys were trained to grasp sugar pellets from wells of varying depths before and after a left unilateral lesion of the cervical dorsal column. Using DeepLabCut, we identified post-lesion deficits in kinematic grasping behavior that included changes in digit orientation, increased variance in vertical and horizontal digit movement, and longer time to complete the task. While video-based analyses of grasping behavior demonstrated deficits in fine-scale digit function that persisted through at least 14 weeks post-injury, traditional end-point behavioral analyses showed a recovery of global hand function as evidenced by recovery of the proportion of successful retrievals by approximately 14 weeks post-injury. The combination of traditional end-point and video-based kinematic analyses provides a more comprehensive characterization of grasping behavior and highlights that global grasping performance may recover despite persistent fine-scale kinematic deficits in digit function. Machine-learning-based video analysis of kinematic digit function, in conjunction with traditional end-point behavioral analyses of grasping behavior, provide sensitive and specific indices for monitoring recovery of fine-grained hand sensorimotor behavior after spinal cord injury that can aid future studies that seek to develop targeted therapeutic interventions for improving behavioral outcomes.

How the conception of control influences our understanding of actions

Wilful movement requires neural control. Commonly, neural computations are thought to generate motor commands that bring the musculoskeletal system - that is, the plant - from its current physical state into a desired physical state. The current state can be estimated from past motor commands and from sensory information. Modelling movement on the basis of this concept of plant control strives to explain behaviour by identifying the computational principles for control signals that can reproduce the observed features of movements. From an alternative perspective, movements emerge in a dynamically coupled agent-environment system from the pursuit of subjective perceptual goals. Modelling movement on the basis of this concept of perceptual control aims to identify the controlled percepts and their coupling rules that can give rise to the observed characteristics of behaviour. In this Perspective, we discuss a broad spectrum of approaches to modelling human motor control and their notions of control signals, internal models, handling of sensory feedback delays and learning. We focus on the influence that the plant control and the perceptual control perspective may have on decisions when modelling empirical data, which may in turn shape our understanding of actions.

Analogous cognitive strategies for tactile learning in the rodent and human brain

Evolution has molded individual species' sensory capacities and abilities. In rodents, who mostly inhabit dark tunnels and burrows, the whisker-based somatosensory system has developed as the dominant sensory modality, essential for environmental exploration and spatial navigation. In contrast, humans rely more on visual and auditory inputs when collecting information from their surrounding sensory space in everyday life. As a result of such species-specific differences in sensory dominance, cognitive relevance and capacities, the evidence for analogous sensory-cognitive mechanisms across species remains sparse. However, recent research in rodents and humans yielded surprisingly comparable processing rules for detecting tactile stimuli, integrating touch information into percepts, and goal-directed rule learning. Here, we review how the brain, across species, harnesses such processing rules to establish decision-making during tactile learning, following canonical circuits from the thalamus and the primary somatosensory cortex up to the frontal cortex. We discuss concordances between empirical and computational evidence from micro- and mesoscopic circuit studies in rodents to findings from macroscopic imaging in humans. Furthermore, we discuss the relevance and challenges for future cross-species research in addressing mutual context-dependent evaluation processes underpinning perceptual learning.

Post-Ischemic Reorganization of Sensory Responses in Cerebral Cortex

Sensorimotor integration is critical for generating skilled, volitional movements. While stroke tends to impact motor function, there are also often associated sensory deficits that contribute to overall behavioral deficits. Because many of the cortico-cortical projections participating in the generation of volitional movement either target or pass-through primary motor cortex (in rats, caudal forelimb area; CFA), any damage to CFA can lead to a subsequent disruption in information flow. As a result, the loss of sensory feedback is thought to contribute to motor dysfunction even when sensory areas are spared from injury. Previous research has suggested that the restoration of sensorimotor integration through reorganization or de novo neuronal connections is important for restoring function. Our goal was to determine if there was crosstalk between sensorimotor cortical areas with recovery from a primary motor cortex injury. First, we investigated if peripheral sensory stimulation would evoke responses in the rostral forelimb area (RFA), a rodent homologue to premotor cortex. We then sought to identify whether intracortical microstimulation-evoked activity in RFA would reciprocally modify the sensory response. We used seven rats with an ischemic lesion of CFA. Four weeks after injury, the rats' forepaw was mechanically stimulated under anesthesia and neural activity was recorded in the cortex. In a subset of trials, a small intracortical stimulation pulse was delivered in RFA either individually or paired with peripheral sensory stimulation. Our results point to post-ischemic connectivity between premotor and sensory cortex that may be related to functional recovery. Premotor recruitment during the sensory response was seen with a peak in spiking within RFA after the peripheral solenoid stimulation despite the damage to CFA. Furthermore, stimulation evoked activity in RFA modulated and disrupted the sensory response in sensory cortex, providing additional evidence for the transmission of premotor activity to sensory cortex and the sensitivity of sensory cortex to premotor cortex's influence. The strength of the modulatory effect may be related to the extent of the injury and the subsequent reshaping of cortical connections in response to network disruption.

Structural and functional map for forelimb movement phases between cortex and medulla

The cortex influences movement by widespread top-down projections to many nervous system regions. Skilled forelimb movements require brainstem circuitry in the medulla; however, the logic of cortical interactions with these neurons remains unexplored. Here, we reveal a fine-grained anatomical and functional map between anterior cortex (AC) and medulla in mice. Distinct cortical regions generate three-dimensional synaptic columns tiling the lateral medulla, topographically matching the dorso-ventral positions of postsynaptic neurons tuned to distinct forelimb action phases. Although medial AC (MAC) terminates ventrally and connects to forelimb-reaching-tuned neurons and its silencing impairs reaching, lateral AC (LAC) influences dorsally positioned neurons tuned to food handling, and its silencing impairs handling. Cortico-medullary neurons also extend collaterals to other subcortical structures through a segregated channel interaction logic. Our findings reveal a precise alignment between cortical location, its function, and specific forelimb-action-tuned medulla neurons, thereby clarifying interaction principles between these two key structures and beyond.

Reaching an understanding of cortico-medullary control of forelimb behaviors

How the neocortex modulates hindbrain and spinal circuits is of fundamental interest for understanding motor control and adaptive behaviors. New work from Yang, Kanodia, and Arber demonstrates that there is an exquisite anatomical organization and functional modulation from the anterior (motor) cortex on downstream medulla populations during forelimb behaviors in mice.

Met/HGFR triggers detrimental reactive microglia in TBI

The complexity of signaling events and cellular responses unfolding in neuronal, glial, and immune cells upon traumatic brain injury (TBI) constitutes an obstacle in elucidating pathophysiological links and targets for intervention. We use array phosphoproteomics in a murine mild blunt TBI to reconstruct the temporal dynamics of tyrosine-kinase signaling in TBI and then scrutinize the large-scale effects of perturbation of Met/HGFR, VEGFR1, and Btk signaling by small molecules. We show Met/HGFR as a selective modifier of early microglial response and that Met/HGFR blockade prevents the induction of microglial inflammatory mediators, of reactive microglia morphology, and TBI-associated responses in neurons and vasculature. Both acute and prolonged Met/HGFR inhibition ameliorate neuronal survival and motor recovery. Early elevation of HGF itself in the cerebrospinal fluid of TBI patients suggests that this mechanism has translational value in human subjects. Our findings identify Met/HGFR as a modulator of early neuroinflammation in TBI with promising translational potential.

Clinical neuroscience and neurotechnology: An amazing symbiosis

In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction.

Hypothalamic Control of Forelimb Motor Adaptation

The ability to perform skilled arm movements is central to everyday life, as limb impairments in common neurologic disorders such as stroke demonstrate. Skilled arm movements require adaptation of motor commands based on discrepancies between desired and actual movements, called sensory errors. Studies in humans show that this involves predictive and reactive movement adaptations to the errors, and also requires a general motivation to move. How these distinct aspects map onto defined neural signals remains unclear, because of a shortage of equivalent studies in experimental animal models that permit neural-level insights. Therefore, we adapted robotic technology used in human studies to mice, enabling insights into the neural underpinnings of motivational, reactive, and predictive aspects of motor adaptation. Here, we show that forelimb motor adaptation is regulated by neurons previously implicated in motivation and arousal, but not in forelimb motor control: the hypothalamic orexin/hypocretin neurons (HONs). By studying goal-oriented mouse-robot interactions in male mice, we found distinct HON signals occur during forelimb movements and motor adaptation. Temporally-delimited optosilencing of these movement-associated HON signals impaired sensory error-based motor adaptation. Unexpectedly, optosilencing affected neither task reward or execution rates, nor motor performance in tasks that did not require adaptation, indicating that the temporally-defined HON signals studied here were distinct from signals governing general task engagement or sensorimotor control. Collectively, these results reveal a hypothalamic neural substrate regulating forelimb motor adaptation.SIGNIFICANCE STATEMENT The ability to perform skilled, adaptable movements is a fundamental part of daily life, and is impaired in common neurologic diseases such as stroke. Maintaining motor adaptation is thus of great interest, but the necessary brain components remain incompletely identified. We found that impaired motor adaptation results from disruption of cells not previously implicated in this pathology: hypothalamic orexin/hypocretin neurons (HONs). We show that temporally confined HON signals are associated with skilled movements. Without these newly-identified signals, a resistance to movement that is normally rapidly overcome leads to prolonged movement impairment. These results identify natural brain signals that enable rapid and effective motor adaptation.

Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure

Simulating the brain-body-environment trinity in closed loop is an attractive proposal to investigate how perception, motor activity and interactions with the environment shape brain activity, and vice versa. The relevance of this embodied approach, however, hinges entirely on the modeled complexity of the various simulated phenomena. In this article, we introduce a software framework that is capable of simulating large-scale, biologically realistic networks of spiking neurons embodied in a biomechanically accurate musculoskeletal system that interacts with a physically realistic virtual environment. We deploy this framework on the high performance computing resources of the EBRAINS research infrastructure and we investigate the scaling performance by distributing computation across an increasing number of interconnected compute nodes. Our architecture is based on requested compute nodes as well as persistent virtual machines; this provides a high-performance simulation environment that is accessible to multi-domain users without expert knowledge, with a view to enable users to instantiate and control simulations at custom scale via a web-based graphical user interface. Our simulation environment, entirely open source, is based on the Neurorobotics Platform developed in the context of the Human Brain Project, and the NEST simulator. We characterize the capabilities of our parallelized architecture for large-scale embodied brain simulations through two benchmark experiments, by investigating the effects of scaling compute resources on performance defined in terms of experiment runtime, brain instantiation and simulation time. The first benchmark is based on a large-scale balanced network, while the second one is a multi-region embodied brain simulation consisting of more than a million neurons and a billion synapses. Both benchmarks clearly show how scaling compute resources improves the aforementioned performance metrics in a near-linear fashion. The second benchmark in particular is indicative of both the potential and limitations of a highly distributed simulation in terms of a trade-off between computation speed and resource cost. Our simulation architecture is being prepared to be accessible for everyone as an EBRAINS service, thereby offering a community-wide tool with a unique workflow that should provide momentum to the investigation of closed-loop embodiment within the computational neuroscience community.

Post-Stroke Hemiplegic Rodent Evaluation: A Framework for Assessing Forelimb Movement Quality Using Kinematics

Kinematics is the gold-standard method for measuring detailed joint motions. Recent research demonstrates that post-stroke kinematic analysis in rats reveals reaching abnormalities similar to those seen in humans after stroke. Nonetheless, behavioral neuroscientists have failed to incorporate kinematic methods for assessing movement quality in stroke models. The availability of a user-friendly method to assess multi-segment forelimb kinematics models should greatly increase uptake of this approach. Here, we present a framework for multi-segment forelimb analysis in rodents after stroke. This method greatly enhances the understanding of post-stroke forelimb motor recovery by including several movement quality metrics often used in human clinical work, such as upper-limb linear and angular kinematics, movement smoothness and kinetics, abnormal synergies, and compensations. These metrics may constitute a preclinical surrogate for the Fugl-Meyer assessment of hemiplegic patients. The data obtained using this method are 83 outputs of linear and angular kinematics and kinetics. The outputs also include 24 time series of continuous data, which afford a graphical representation of the kinematics and kinetics of the reaching cycle. We show that post-stroke rodents displayed many features resembling those seen in humans after stroke that are evident only when multi-segment kinematics models are considered. This method expands the knowledge derived from methods constrained to paw movements to a multi-segment forelimb movement quality framework. Moreover, it highlights the need for preclinical work to consider more sensitive measures of sensorimotor impairment and recovery as a means to enhance the interpretation of true recovery and compensation. © 2022 Wiley Periodicals LLC. Basic Protocol: Recording and data analysis of rodents performing the Montoya staircase task.

The primary motor cortex: the hub of motor learning in rodents

The primary motor cortex, a dynamic center for overall motion control and decision making, undergoes significant alterations upon neural stimulation. Over the last few decades, data from numerous studies using rodent models have improved our understanding of the morphological and functional plasticity of the primary motor cortex. In particular, spatially specific formation of dendritic spines and their maintenance during distinct behaviors is considered crucial for motor learning. However, whether the modifications of specific synapses are associated with motor learning should be studied further. In this review, we summarized the findings of prior studies on the features and dynamics of the primary motor cortex in rodents.

Sensory Circuit Remodeling and Movement Recovery After Spinal Cord Injury

Restoring sensory circuit function after spinal cord injury (SCI) is essential for recovery of movement, yet current interventions predominantly target motor pathways. Integrated cortical sensorimotor networks, disrupted by SCI, are critical for perceiving, shaping, and executing movement. Corticocortical connections between primary sensory (S1) and motor (M1) cortices are critical loci of functional plasticity in response to learning and injury. Following SCI, in the motor cortex, corticocortical circuits undergo dynamic remodeling; however, it remains unknown how rehabilitation shapes the plasticity of S1-M1 networks or how these changes may impact recovery of movement.

Three Water Restriction Schedules Used in Rodent Behavioral Tasks Transiently Impair Growth and Differentially Evoke a Stress Hormone Response without Causing Dehydration

Water restriction is commonly used to motivate rodents to perform behavioral tasks; however, its effects on hydration and stress hormone levels are unknown. Here, we report daily body weight and bi-weekly packed red blood cell volume and corticosterone (CORT) in adult male rats across 80 days for three commonly used water restriction schedules. We also assessed renal adaptation to water restriction using postmortem histologic evaluation of renal medulla. A control group received ad libitum water. After one week of water restriction, rats on all restriction schedules resumed similar levels of growth relative to the control group. Normal hydration was observed, and water restriction did not drive renal adaptation. An intermittent restriction schedule was associated with an increase in CORT relative to the control group. However, intermittent restriction evokes a stress response which could affect behavioral and neurobiological results. Our results also suggest that stable motivation in behavioral tasks may only be achieved after one week of restriction.

Contralateral S1 function is involved in electroacupuncture treatment-mediated recovery after focal unilateral M1 infarction

Acupuncture at acupoints Baihui (GV20) and Dazhui (GV14) has been shown to promote functional recovery after stroke. However, the contribution of the contralateral primary sensory cortex (S1) to recovery remains unclear. In this study, unilateral local ischemic infarction of the primary motor cortex (M1) was induced by photothrombosis in a mouse model. Electroacupuncture (EA) was subsequently performed at acupoints GV20 and GV14 and neuronal activity and functional connectivity of contralateral S1 and M1 were detected using in vivo and in vitro electrophysiological recording techniques. Our results showed that blood perfusion and neuronal interaction between contralateral M1 and S1 is impaired after unilateral M1 infarction. Intrinsic neuronal excitability and activity were also disturbed, which was rescued by EA. Furthermore, the effectiveness of EA treatment was inhibited after virus-mediated neuronal ablation of the contralateral S1. We conclude that neuronal activity of the contralateral S1 is important for EA-mediated recovery after focal M1 infarction. Our study provides insight into how the S1–M1 circuit might be involved in the mechanism of EA treatment of unilateral cerebral infarction. The animal experiments were approved by the Committee for Care and Use of Research Animals of Guangzhou University of Chinese Medicine (approval No. 20200407009) April 7, 2020.

Intersectional genetic tools to study skilled reaching in mice

Reaching to grasp is an evolutionarily conserved behavior and a crucial part of the motor repertoire in mammals. As it is studied in the laboratory, reaching has become the prototypical example of dexterous forelimb movements, illuminating key principles of motor control throughout the spinal cord, brain, and peripheral nervous system. Here, we (1) review the motor elements or phases that comprise the reach, grasp, and retract movements of reaching behavior, (2) highlight the role of intersectional genetic tools in linking these movements to their neuronal substrates, (3) describe spinal cord cell types and their roles in skilled reaching, and (4) how descending pathways from the brain and the sensory systems contribute to skilled reaching. We emphasize that genetic perturbation experiments can pin-point the neuronal substrates of specific phases of reaching behavior.

Does proprioceptive acuity influence the extent of implicit sensorimotor adaptation in young and older adults?

The ability to adjust movements to changes in the environment declines with aging. This age-related decline is caused by the decline of explicit adjustments. However, implicit adaptation remains intact and might even be increased with aging. Since proprioceptive information has been linked to implicit adaptation, it might well be that an age-related decline in proprioceptive acuity might be linked to the performance of older adults in implicit adaptation tasks. Indeed, age-related proprioceptive deficits could lead to altered sensory integration with an increased weighting of the visual sensory-prediction error. Another possibility is that reduced proprioceptive acuity results in an increased reliance on predicted sensory consequences of the movement. Both these explanations led to our preregistered hypothesis: we expected a relation between the decline of proprioception and the amount of implicit adaptation across ages. However, we failed to support this hypothesis. Our results question the existence of reliability-based integration of visual and proprioceptive signals during motor adaptation.

Measuring and modeling the motor system with machine learning

The utility of machine learning in understanding the motor system is promising a revolution in how to collect, measure, and analyze data. The field of movement science already elegantly incorporates theory and engineering principles to guide experimental work, and in this review we discuss the growing use of machine learning: from pose estimation, kinematic analyses, dimensionality reduction, and closed-loop feedback, to its use in understanding neural correlates and untangling sensorimotor systems. We also give our perspective on new avenues, where markerless motion capture combined with biomechanical modeling and neural networks could be a new platform for hypothesis-driven research.

Chronic Primary Headache Subjects Have Greater Forward Head Posture than Asymptomatic and Episodic Primary Headache Sufferers: Systematic Review and Meta-analysis

OBJECTIVE

To summarize the cervical physical examination characteristics in subjects with chronic primary headache and compare those with a healthy population and a population with episodic primary headache.

DESIGN

Systematic review and meta-analysis.

SUBJECTS

Humans ≥18 years old. At least one of the study groups should be constituted by subjects diagnosed with one of the chronic primary headache subtypes according to the International Classification of Headache Disorders, 3rd Edition.

COMPARISON

Neck physical examination outcomes of subjects with chronic primary headache compared with a healthy population or subjects with episodic primary headache.

OUTCOMES

Forward head posture (FHP), cervical range of movement, motor control, neck muscle activity, and reproduction and resolution of symptoms.

METHODS

Two reviewers assessed independently the MEDLINE, EMBASE, WOS, MEDES, PEDro, and CINAHL databases to select observational studies. First, both implemented an agreement for a search strategy. Then, they screened independently for duplicates, titles, abstracts, and full-text information. A meta-analysis was conducted to compare measures between groups.

RESULTS

Twelve studies (N = 1,083) with moderate quality (mean ± SD = 7.75 ± 1.48 on the Newcastle Ottawa Scale) were selected for the qualitative analysis. The meta-analysis showed that patients with chronic primary headache presented greater forward head posture than asymptomatic participants (N = 275, Hg = 0.68, 95% CI = 0.25-1.1, Z = 3.14, P < 0.01) and patients with episodic primary headache (N = 268, Hg = 0.39, 95% CI = 0.13-0.65, Z = 2.98, P < 0.01).

CONCLUSIONS

There is moderate to strong evidence that patients with chronic primary headache present greater FHP than asymptomatic individuals and moderate evidence that patients with chronic primary headache present greater forward head posture than those with episodic primary headache.

New roles for dopamine in motor skill acquisition: lessons from primates, rodents, and songbirds

Motor learning is a core aspect of human life and appears to be ubiquitous throughout the animal kingdom. Dopamine, a neuromodulator with a multifaceted role in synaptic plasticity, may be a key signaling molecule for motor skill learning. Though typically studied in the context of reward-based associative learning, dopamine appears to be necessary for some types of motor learning. Mesencephalic dopamine structures are highly conserved among vertebrates, as are some of their primary targets within the basal ganglia, a subcortical circuit important for motor learning and motor control. With a focus on the benefits of cross-species comparisons, this review examines how "model-free" and "model-based" computational frameworks for understanding dopamine's role in associative learning may be applied to motor learning. The hypotheses that dopamine could drive motor learning either by functioning as a reward prediction error, through passive facilitating of normal basal ganglia activity, or through other mechanisms are examined in light of new studies using humans, rodents, and songbirds. Additionally, new paradigms that could enhance our understanding of dopamine's role in motor learning by bridging the gap between the theoretical literature on motor learning in humans and other species are discussed.

Parallel and Serial Sensory Processing in Developing Primary Somatosensory and Motor Cortex

It is generally supposed that primary motor cortex (M1) receives somatosensory input predominantly via primary somatosensory cortex (S1). However, a growing body of evidence indicates that M1 also receives direct sensory input from the thalamus, independent of S1; such direct input is particularly evident at early ages before M1 contributes to motor control. Here, recording extracellularly from the forelimb regions of S1 and M1 in unanesthetized rats at postnatal day (P)8 and P12, we compared S1 and M1 responses to self-generated (i.e., reafferent) forelimb movements during active sleep and wake, and to other-generated (i.e., exafferent) forelimb movements. At both ages, reafferent responses were processed in parallel by S1 and M1; in contrast, exafferent responses were processed in parallel at P8 but serially, from S1 to M1, at P12. To further assess this developmental difference in processing, we compared exafferent responses to proprioceptive and tactile stimulation. At both P8 and P12, proprioceptive stimulation evoked parallel responses in S1 and M1, whereas tactile stimulation evoked parallel responses at P8 and serial responses at P12. Independent of the submodality of exafferent stimulation, pairs of S1-M1 units exhibited greater coactivation during active sleep than wake. These results indicate that S1 and M1 independently develop somatotopy before establishing the interactive relationship that typifies their functionality in adults.SIGNIFICANCE STATEMENT Learning any new motor task depends on the ability to use sensory information to update motor outflow. Thus, to understand motor learning, we must also understand how animals process sensory input. Primary somatosensory cortex (S1) and primary motor cortex (M1) are two interdependent structures that process sensory input throughout life. In adults, the functional relationship between S1 and M1 is well established; however, little is known about how S1 and M1 begin to transmit or process sensory information in early life. In this study, we investigate the early development of S1 and M1 as a sensory processing unit. Our findings provide new insights into the fundamental principles of sensory processing and the development of functional connectivity between these important sensorimotor structures.

Motor control: Neural correlates of optimal feedback control theory

Recent work is revealing neural correlates of a leading theory of motor control. By linking an elegant series of behavioral experiments with neural inactivation in macaques with computational models, a new study shows that premotor and parietal areas can be mapped onto a model for optimal feedback control.

Effects of Optogenetic Stimulation of Primary Somatosensory Cortex and Its Projections to Striatum on Vibrotactile Perception in Freely Moving Rats

Tactile sensation is one of our primary means to collect information about the nearby environment and thus crucial for daily activities and survival. Therefore, it is of high importance to restore sensory feedback after sensory loss. Optogenetic manipulation allows local or pathway-specific write-in of information. However, it remains elusive whether optogenetic stimulation can be interpreted as tactile sensation to guide operant behavior and how it is integrated with tactile stimuli. To address these questions, we employed a vibrotactile detection task combined with optogenetic neuromodulation in freely moving rats. By bidirectionally manipulating the activity of neurons in primary somatosensory cortex (S1), we demonstrated that optical activation as well as inhibition of S1 reduced the detection rate for vibrotactile stimuli. Interestingly, activation of corticostriatal terminals improved the detection of tactile stimuli, while inhibition of corticostriatal terminals did not affect the performance. To manipulate the corticostriatal pathway more specifically, we employed a dual viral system. Activation of corticostriatal cell bodies disturbed the tactile perception while activation of corticostriatal terminals slightly facilitated the detection of vibrotactile stimuli. In the absence of tactile stimuli, both corticostriatal cell bodies as well as terminals caused a reaction. Taken together, our data confirmed the possibility to restore sensation using optogenetics and demonstrated that S1 and its descending projections to striatum play differential roles in the neural processing underlying vibrotactile detection.

Cuneate nucleus: The somatosensory gateway to the brain

Much remains unknown about the transformation of proprioceptive afferent input from the periphery to the cortex. Until recently, the only recordings from neurons in the cuneate nucleus (CN) were from anesthetized animals. We are beginning to learn more about how the sense of proprioception is transformed as it propagates centrally. Recent recordings from microelectrode arrays chronically implanted in CN have revealed that CN neurons with muscle-like properties have a greater sensitivity to active reaching movements than to passive limb displacement, and we find that these neurons have receptive fields that resemble single muscles. In this review, we focus on the varied uses of proprioceptive input and the possible role of CN in processing this information.

Transient deactivation of dorsal premotor cortex or parietal area 5 impairs feedback control of the limb in macaques

We can generate goal-directed motor corrections with surprising speed, but their neural basis is poorly understood. Here, we show that temporary cooling of dorsal premotor cortex (PMd) impaired both spatial accuracy and the speed of corrective responses, whereas cooling parietal area 5 (A5) impaired only spatial accuracy. Simulations based on optimal feedback control (OFC) models demonstrated that "deactivation" of the control policy (reduction in feedback gain) and state estimation (reduction in Kalman gain) caused impairments similar to that observed for PMd and A5 cooling, respectively. Furthermore, combined deactivation of both cortical regions led to additive impairments of individual deactivations, whereas reducing the amount of cooling to PMd led to impairments in response speed but not spatial accuracy, both also predicted by OFC models. These results provide causal support that frontoparietal circuits beyond primary somatosensory and motor cortices are involved in generating goal-directed motor corrections.