Journal of Neurophysiology

Patients with cerebellar damage experience various motor impairments, but the specific sequence of primary and compensatory processes that contribute to these deficits remains unclear. To clarify this, we reversibly blocked cerebellar outflow in monkeys engaged in planar reaching tasks. This intervention led to a spatially selective reduction in hand velocity, primarily due to decreased muscle torque, especially in movements requiring high inter-joint torque coupling. When examining repeated reaches to the same target, we found that the reduced velocity resulted from both an immediate deficit and a gradually developing compensatory slowing to reduce passive inter-joint interactions. However, the slowed hand velocity did not account for the fragmented and variable movement trajectories observed during the cerebellar block. Our findings indicate that cerebellar impairment results in motor deficits due to both inadequate muscle torque and an altered motor control strategy for managing impaired limb dynamics. Additionally, impaired motor control elevates noise, which cannot be entirely mitigated through compensatory strategies.

Motor adaptation is essential for maintaining coordination and precision in daily activities. Implicit motor adaptation--adaptation that occurs without conscious awareness--is thought to be primarily driven by sensory prediction errors. Here, we investigated how rapidly these unconscious changes in reaching behavior emerge as a function of error magnitude and the availability of task error signals. To this end, we employed a single-trial learning (STL) paradigm within a classical visuomotor rotation task. Participants made center-out reaching movements to either small (dot) or large (arc) targets while experiencing single perturbation trials with cursor rotations ranging from 1{degrees} to 90{degrees}, each followed by an aligned washout trial. By manipulating target size, we systematically modulated the presence of task error while holding sensory prediction error constant. We further compared these early implicit changes with those observed during standard prolonged adaptation to a fixed 20{degrees} rotation across >100 trials. Our results show that implicit adaptation emerges rapidly, even after a single exposure to small perturbations, and follows a saturating, fixed-rate response profile. Importantly, the magnitude of single-trial adaptation was greater when task error was present (small targets) compared with conditions in which only sensory prediction error was available (large targets). Moreover, STL-derived parameters moderately predicted the initial phase of adaptation during prolonged learning, suggesting that STL captures core dynamics of early implicit processes. These findings provide new insight into the mechanistic principles governing implicit motor adaptation. By identifying the parameters that drive early-stage error-based learning, this work refines current models of sensorimotor learning and highlights potential strategies for designing targeted training or rehabilitation protocols that leverage rapid adaptation processes to enhance motor performance and recovery.

Attention plays a crucial role in maintaining precision and effectiveness in goal-directed actions. Although there is evidence that dividing attention across tasks impairs performance in various domains, the impact of attention on sensorimotor adaptation remains inconclusive, with some studies reporting deficits and others showing no effects. Because sensorimotor adaptation arises from the interaction of explicit and implicit processes, this discrepancy may reflect differential effects of attention on each process. Here, we investigate how divided attention influences implicit sensorimotor adaptation using an error-clamp paradigm, coupled with a random dot kinematogram (RDK) motion coherence discrimination task. We also assessed whether the timing of the secondary task affects error processing during sensorimotor adaptation by presenting the RDK either during the outward movement (coinciding with error feedback), or the inward movement (following error feedback). We observed that attentional manipulation influenced implicit sensorimotor adaptation only when the RDK was presented on the outward movement, not the inward movement. Remarkably, implicit sensorimotor adaptation was enhanced when attention was divided, compared to when attention was focused entirely on the adaptation task. This suggests that implicit sensorimotor adaptation is sensitive to attentional demand, particularly during the time window where error feedback is received.

The locus coeruleus-norepinephrine (LC-NE) system plays multiple roles in higher brain function that are thought to depend on its mode of activation, which reflects relationships between baseline and evoked activation levels. These relationships are evident in both single-unit LC activity and proposed physiological proxies of LC-NE activity, such as pupil size. Here we used measurements in awake monkeys to show that the baseline-evoked relationships evident within these two different measures are unreliably coupled between them: baseline-evoked relationships of the pupil are not predictive of those in the LC, and vice versa. These results imply that pupil modulations, which can reflect LC-NE activity, should be used with caution to make inferences about "phasic" (moderate baseline, high evoked) and "tonic" (high baseline, low evoked) LC-NE activity modes that are thought to support different forms of information processing in the brain.

During deliberation, as the brain considers its options, the neural activity representing the goodness of each option rises toward a threshold, and the choice is often dictated by the option for which the rise is fastest. Here we report a surprising correlate of these activities: saccade vigor. We engaged human subjects in a decision-making task in which they considered effortful options, each requiring walking various durations and inclines. As they deliberated, they made saccades between the symbolic representations of those options. These saccades had no bearing on the effort that they would later expend, yet as they deliberated, saccade velocities increased. The rate of rise in vigor was faster for saccades toward the option that they later indicated as their choice, and encoded the difference in the subjective value of the two effortful options. Once deliberation ended, following a brief delay the subjects indicated their choice by making another saccade. Remarkably, vigor for this saccade dropped to baseline and no longer encoded subjective value. These results are consistent with an urgency model of decision-making in which a global signal in the brain drives both the neural circuits that make decisions, and the neural circuits that make movements. Paradoxically, this common drive is shared between the oculomotor circuits and the decision-making circuits, even when the decision involves effortful expenditure during a future event. SignificanceThere is a link between the decisions we make and the movements that follow. Not only do we prefer options of greater value, but we also move faster to acquire them. When deliberating between options, neural activity rises to a threshold and the option that wins this race is the one chosen. We report a potential correlate of this in the motor control circuits; during deliberation, saccade vigor to both options rise, but faster for the option ultimately chosen. Thus, our movements appear to mirror the neural activity conducting the decision-making process. Paradoxically, this is true even when the movements have no direct bearing on the decision at hand.

When reaching to a foveated target, peripheral vision of the hand can be used to make rapid, automatic adjustments to the ongoing reach movement, with the feedback gain being sensitive to features of the task and environment. These rapid corrective responses are also observed when gaze is directed to a stationary gaze target located away from the reach target. In everyday contexts, reaching often occurs concurrently with other visual or visuomotor tasks, such as tracking a moving target. Yet it remains unclear whether engaging in such tasks affects the use of peripheral vision for hand guidance. Here, we compare rapid visuomotor corrective responses to visual perturbations during fixation and smooth pursuit, and test whether pursuit-related and reach-related visuomotor processes operate independently or compete for shared visual resources. Participants either fixated a stationary target or tracked a moving target while reaching toward a spatially dissociated reach target. During the reach, the visual representation of the hand was perturbed, requiring rapid corrective responses. We found that neither the onset nor the gain of reach corrections was modulated by gaze-task demands. Moreover, response gains were strongly correlated across tasks, indicating consistent individual response profiles that were independent of the gaze condition. Despite modest increases in position error and decreases in gain, participants largely sustained engagement with the visual tasks during target reaching. These findings demonstrate that smooth pursuit and reach-related visuomotor processing can operate in parallel without mutual interference, suggesting a functional independence between them. NEW & NOTEWORTHYIn everyday life, reaching to an object can occur while the eyes are engaged in competing visual tasks. We show that engaging in smooth pursuit eye movements does not disrupt rapid visuomotor corrections during reaching. The onset and gain of corrective responses following perturbation were unchanged by gaze-task demands and were consistent across individuals. These findings demonstrate that pursuit and reach-related visuomotor processes can operate in parallel, supporting functional independence between these systems.

We investigated the dimensions of output zones affecting specific combinations of forelimb muscles in the precentral "motor" cortex of macaque monkeys. Single-pulse intracortical microstimulation (S-ICMS) was used to evoke subthreshold effects in multiple wrist and finger muscles. Results indicate that each motor cortex site represents a different combination of muscles. The effects evoked from cortical sites separated by several hundred microns invariably involved different profiles of muscle activity. The muscle fields of remote CM cells were rarely identical, while the fields of neighboring CM cells were often similar. Given the number of unrecorded muscles, we conclude that primate motor cortex is a mosaic of output sites representing forelimb muscles in different combinations.

Sensorimotor adaptation is essential for keeping our movements well-calibrated in response to changes in the body and environment. For over a century, we have studied sensorimotor adaptation in highly controlled laboratory settings that typically involve small sample sizes. While this approach has proven useful to characterize different learning processes, laboratory studies are typically very underpowered to generate data suited for exploring the myriad of factors that may modulate motor performance. Here, using a citizen science website (testmybrain.org), we collected over 2000 sessions on a visuomotor rotation task. This unique dataset has allowed us to replicate classic motor findings, reconcile controversial findings in the learning and memory literature, and discover novel constraints underlying dissociable implicit and explicit learning processes supporting sensorimotor adaptation. Taken together, this study suggests that large-scale motor learning studies hold enormous potential to advance sensorimotor neuroscience.

Human motor adaptation relies on both explicit conscious strategies and implicit unconscious updating of internal models to correct motor errors. Implicit adaptation is powerful, requiring less preparation time before executing adapted movements, but recent work suggests it is limited to some absolute magnitude regardless of the size of a visuomotor perturbation when the perturbation is introduced abruptly. It is commonly assumed that gradually introducing a perturbation should lead to improved implicit learning beyond this limit, but outcomes are conflicting. We tested whether introducing a perturbation in two distinct gradual methods can overcome the apparent limit and explain past conflicting findings. We found that gradually introducing a perturbation in a stepped manner, where participants were given time to adapt to each partial step before being introduced to a larger partial step, led to [~]80% higher implicit aftereffects of learning, but introducing it in a ramped manner, where participants adapted larger rotations on each subsequent reach, did not. Our results clearly show that gradual introduction of a perturbation can lead to substantially larger implicit adaptation, as well as identify the type of introduction that is necessary to do so.

The role of sensory feedback is well established in current models of motor control, evidenced by deficits in movement coordination resulting from impaired sensory function. When vision and touch are both available for object-oriented manual behaviors, these senses can be distinctly leveraged; vision guides movement planning while touch provides feedback on hand-object interactions. How eye-hand coordination changes with the loss of somatosensory feedback has not been well studied. Conceivably, vision is recruited to compensate for the feedback lost when touch is abolished. We tested healthy participants on a manual dexterity task, consisting of moving small metal pegs. The task was performed before and after administration of digital anesthesia that abolished cutaneous sensations while preserving motor function with the acting hand. During peg collection, transport, and placement epochs, we tracked gaze direction and hand positions while also recording forces applied to the pegboard. We hypothesized that the nervous system selectively adapts eye-hand coordination according to the dexterity demands of the task epochs. We found that participants maintained the ability to perform the pegboard task following the loss of cutaneous feedback, albeit with longer trial times and altered force profiles. Notably, somatosensory loss was accompanied by a shift in visual behavior marked by a closer alignment between gaze and hand positions during all task epochs, even those that did not involve object manipulation. Together, these data affirm the contributions of sensory feedback to force control in service of dexterous object manipulation and reveal the non-selective nature of compensatory eye-hand coordination processes. Significance StatementTouch and vision typically support distinct, but coordinated aspects of dexterous manual behaviors. Here, we evaluated how acute removal of tactile feedback using digital anesthesia affected performance and eye-hand coordination in a manual dexterity task. With insensate fingers and intact vision, participants continued to perform the task successfully, albeit with longer trial times and altered force profiles. We also observed closer alignment between gaze and hand positions during all task epochs, even those that did not involve object manipulation. Our results reveal the consequences of acute somatosensory loss and the general nature of compensatory eye-hand coordination processes.

The nervous system has a tremendous ability to modify motoneuron excitability according to task demands through neuromodulatory synaptic input to motoneurons. Neuromodulatory inputs adjust the response of the motoneuron to excitatory and inhibitory ionotropic input and can facilitate the induction of persistent inward currents (PICs). PICs amplify and prolong the motoneuron response to synaptic inputs, and PIC impairment may play a major role in motor deficits observed in pathological conditions. Noninvasive estimation of the magnitude of neuromodulatory input and persistent inward currents in human motoneurons is achieved through a paired motor unit analysis ({Delta}F) that quantifies hysteresis in the firing rates at motor unit recruitment and derecruitment. While the {Delta}F technique is commonly used for estimating motoneuron excitability, computational parameters used for the technique vary across studies. In the present study, we assessed the sensitivity of the {Delta}F technique to several criteria commonly used in selecting motor unit pairs for analysis, as well as to methods used for smoothing the instantaneous motor unit firing rates. Using HD-sEMG and motor unit decomposition we obtained 5,409 motor unit pairs from the triceps brachii of ten healthy individuals during submaximal triangle contractions. The mean (SD) {Delta}F was 4.9 (1.08) pps, consistent with previous work using intramuscular recordings. There was an exponential plateau relationship between {Delta}F and the recruitment time difference between the motor unit pairs, with the plateau occurring at approximately 1 s. There was an exponential decay relationship between {Delta}F and the derecruitment time difference between the motor unit pairs, with the decay stabilizing at approximately 1.5 s. We found that reducing or removing the minimum threshold for the correlation of the rate-rate slope for the two units did not affect {Delta}F values or variance. Additionally, we found that removing motor unit pairs in which the control unit was saturated had no significant effect on {Delta}F. Smoothing filter selection had no substantial effect on {Delta}F values and {Delta}F variance; however, the length and type of smoothing filter affected the minimum recruitment and derecruitment time differences. Our results facilitate interpretation of findings from studies that implement the {Delta}F approach but use different computational parameters.

Motor learning involves plasticity in a network of brain areas across the cortex and cerebellum. Such traces of learning have the potential to affect subsequent learning of other tasks. In some cases, prior learning can interfere with subsequent learning, but it may be possible to potentiate learning of one task with a prior task if they are sufficiently different. Because prism adaptation involves extensive neuroplasticity, we reasoned that the elevated excitability of neurons could increase their readiness to undergo structural changes, and in turn, create an optimal state for learning a subsequent task. We tested this idea, selecting two different forms of learning tasks, asking whether exposure to a sensorimotor adaptation task can improve subsequent de novo motor skill learning. Participants first learned a new visuomotor mapping induced by prism glasses in which prism strength varied trial-to-trial. Immediately after and the next day, we tested participants on a mirror tracing task, a form of de novo skill learning. Prism-trained and control participants both learned the mirror tracing task, with similar reductions in error and increases in distance traced. Both groups also showed evidence of offline performance gains between the end of day 1 and the start of day 2. However, we did not detect differences between groups. Overall, our results do not support the idea that prism adaptation learning can potentiate subsequent de novo learning. We discuss factors that may have contributed to this result.

Anticipatory postural adjustments (APAs) scale with velocity of approaching objects, with scaling magnitude depending on whether the moving object is actively foveated and tracked, processed through fixated peripheral vision, or processed through fixated central vision. Aging preferentially degrades the magnocellular pathway underlying peripheral motion processing while sparing the extraretinal signals available during smooth pursuit. We therefore asked whether the effect of aging on velocity-dependent APA scaling differs across these three visual pathways. Eighteen young and eighteen older adults stopped a virtual object approaching at four velocities (15-33 cm/s) under three gaze conditions: active foveation via smooth pursuit, central fixation, and peripheral fixation. We measured peak anticipatory force, rate of force development, and time to contact at force onset. Despite reduced smooth pursuit gain in older adults, velocity-dependent scaling was equivalent between age groups during active foveation, and minimal in both groups during central fixation. Critically, young adults scaled force rate during peripheral fixation nearly as steeply as during active foveation, whereas older adults slope was significantly lower -- a difference not observed during the other gaze conditions. Older adults achieved comparable peak force by initiating responses earlier. These results establish that age-related decline in anticipatory motor control is pathway-specific: aging selectively impairs peripheral motion processing for APAs, while extraretinal mechanisms remain capable of sustaining velocity-dependent scaling. More broadly, peripheral motion processing emerges as a candidate physiological locus of age-related postural vulnerability, raising the question of whether magnocellular-targeted training can restore APA scaling in older adults. Key PointsO_LIYoung and older adults stopped virtual objects under three visual conditions: active foveation via smooth pursuit eye movements, and stationary gaze with the object moving through either central or peripheral vision. C_LIO_LIVelocity-dependent force rate scaling was preserved during active foveation in both age groups, minimal during fixated central vision in both age groups, and selectively impaired in older adults during fixated peripheral vision. C_LIO_LIWe found an age-induced vulnerability in peripheral visual motion processing for anticipatory posture stabilization. C_LI

During goal-directed movements, the magnitude of error correction by a person on a subsequent movement provides important insight into a persons motor learning dynamics. Observed differences in trial-by-trial adaptation rates might indicate different relative weighting placed on the various sources of information that inform a movement, e.g. sensory feedback, control predictions, or internal model expectations. Measuring this trial-by-trial adaptation rate is not straightforward, however, since externally observed data are masked by noise from several sources and influenced by inaccessible internal processes. Adaptation to perturbation has been used to measure error adaptation as the introduced external disturbance is sufficiently large to overshadow other noise sources. However, perturbation analysis is difficult to implement in real-world scenarios, requires a large number of movement trials to accommodate infrequent perturbations, and the paradigm itself might affect the movement dynamics being observed. Here we focus on error adaptation during unperturbed and naturalistic movements. With increasing motor noise, the conventional estimation of trial-by-trial adaptation increases, a counterintuitive finding that is the consequence of systematic bias in the estimate due to noise masking the learners intention. We present an analytic solution relying on stochastic signal processing to reduce this effect of noise, producing an estimate of motor adaptation with reduced bias. The result is an improved estimate of trial-by-trial adaptation in a human learner compared to conventional methods. We demonstrate the effectiveness of the new method in analyzing simulated and empirical movement data under different noise conditions. The analytic approach is applicable across different types of movements in varied contexts and should replace the regression analysis method in future motor analysis studies. Author SummaryWhen a person makes a movement, a motor error is typically observed that then drives motor planning corrections on subsequent movements. This error correction provides insight into how the nervous system is operating, particularly in regard to how much confidence a person places in different sources of information such as sensory feedback or motor command reproducibility. Traditional analysis of movement has required carefully controlled laboratory conditions, limiting the usefulness of motor analysis in clinical and everyday environments. Here we present a new computational method that can be accurately applied to typical movements. Counterintuitive findings of the established approach are corrected by the proposed method. This method will provide a common framework for researchers to analyze movements while extending dynamic motor adaptation analysis capabilities to clinical and non-laboratory settings.

Learned movements are thought to be represented in both extrinsic and intrinsic coordinate systems. Intrinsic representations have traditionally been characterized using joint-based coordinates, although the relationship between joint movements and muscle activation depends strongly on limb configuration. Consequently, movement directions aligned in joint space may not be aligned in muscle space, but the implications of this mismatch for motor learning have remained largely unexplored. We addressed this question by combining electromyographic (EMG) analysis with a visuomotor adaptation experiment. In Experiment 1, participants performed planar reaching movements in two workspaces separated by a 45{degrees} shoulder rotation while EMG activity was recorded from nine upper-limb muscles. Muscle-pattern similarity analysis revealed that movement directions aligned in joint space were not always aligned in muscle space and that the degree of misalignment varied systematically across movement directions. Based on these results, we predicted that visuomotor adaptation to clockwise (CW) and counterclockwise (CCW) rotations would produce different patterns of motor generalization, contrary to the prediction of conventional joint-space accounts. Experiment 2 confirmed this prediction, revealing a systematic shift between the CW and CCW generalization patterns that was consistent with the muscle-space prediction. These findings suggest that intrinsic representations of learned movements are not fully captured by joint-based coordinates alone and that muscle-based coordinates contribute to motor learning and its generalization. Together, these findings highlight the importance of considering underlying biomechanics when interpreting motor representations using generalization paradigms.

Generating pure elbow rotation requires contracting muscles at both the shoulder and elbow joints to counter torques that arise at the shoulder when the forearm rotates (i.e., intersegmental dynamics). Previous work has shown that human participants learn to reduce their shoulder muscle activity if the same elbow movement is performed after the shoulder joint is mechanically locked, which is appropriate because locking the shoulder joint eliminates the torques that arise at the shoulder when the forearm rotates. However, this learning is slow (i.e., it unfolds over hundreds of trials) and incomplete (i.e., shoulder activity is not fully eliminated). Here we investigated whether and how the addition of explicit strategies and biofeedback modulate this type of learning. Three groups of human participants (N = 55) performed voluntary pure elbow rotations using a robotic exoskeleton that permits shoulder and elbow rotation in a horizontal plane. Participants did the task with the shoulder free to move (baseline), then with the shoulder joint locked by the robotic manipulandum (adaptation), and then with the shoulder free to move again (post-adaptation). The first group of participants performed this protocol and received no instructions about what to do after their shoulder was locked. The second group of participants received visual feedback about their shoulder muscle activity after each movement and was instructed to reduce their shoulder activity to zero. The third group of participants also received visual biofeedback, but it was removed part way through the experiment. We found that, although all groups learned, the rate and magnitude of learning was not reliably different across the groups. Taken together, our results suggest that learning new arm dynamics, unlike other motor learning paradigms, unfolds independent of explicit instructions, biofeedback and task instructions.

When a movement error occurs, the motor system updates its commands to improve performance on subsequent trials. A prominent feedback error learning hypothesis proposes that the feedback response that corrects movement within a trial serves as a teaching signal for the learning response, observed as changes in motor commands on the next trial. However, how the temporal pattern of the feedback response influences the learning response remains unclear. Here, we introduce an experimental paradigm that directly compares the temporal patterns of feedback and learning responses across different patterns of visual error. We show that although the feedback response closely tracks the temporal pattern of the visual error, this temporal pattern is not transferred to the learning response. Instead, the amplitude of the feedback response during the holding period, reflecting the temporal pattern of the visual error, primarily determines the magnitude of the learning response. These findings reveal how the motor learning system selectively extracts specific components of feedback responses to update future motor commands.

Accumulating evidence indicates that the humans proprioception map appears subject-specific. However, whether the idiosyncratic pattern persists across time with good within-subject consistency has not been quantitatively examined. Here we measured the proprioception by a hand visual-matching task in multiple sessions over two days. We found that people improved their proprioception when tested repetitively without performance feedback. Importantly, despite the reduction of average error, the spatial pattern of proprioception errors remained idiosyncratic. Based on individuals proprioceptive performance, a standard convolutional neural network classifier could identify people with good accuracy. We also found that subjects baseline proprioceptive performance could not predict their motor performance in a visual trajectory-matching task even though both tasks require accurate mapping of hand position to visual targets in the same workspace. Using a separate experiment, we not only replicated these findings but also ruled out the possibility that performance feedback during a few familiarization trials caused the observed improvement in proprioception. We conclude that the conventional proprioception test itself, even without feedback, can improve proprioception but leave the idiosyncrasy of proprioception unchanged.

Integrated multisensory feedback plays a crucial role in balance control. Minimal fingertip contact with a surface (light-touch), reduces center of pressure (CoP) by adding sensory information about postural orientation and balance state. Electrical vestibular stimulation (EVS) can increase sway by adding erroneous vestibular cues. This juxtaposition of conflicting sensory cues can be exploited to explore the dynamics of sensorimotor reweighting. We used continuous stochastic EVS (0-25Hz; {+/-}4mA; 200-300s) to evoke balance responses in CoP (Exp-1, Exp-2) and segment accelerations (Exp-2). Systems analyses (coherence, gain) quantified coupling and size of balance responses to EVS. We had participants either touch (TOUCH; <2N) or not touch (NO-TOUCH) a load cell during EVS (Exp-1, Exp-2), or we intermittently removed the touch surface (Exp-2) to measure the effects of light touch on vestibular-evoked balance responses. We hypothesized that coherence and gain between EVS and CoP would decrease, consistent with the CNS down-weighting vestibular cues that conflict with light touch. Light touch reduced CoP displacement, but increased variation in the CoP signal explained by EVS input. Significant coherence between EVS and CoP was observed up to [~]30Hz in both conditions but was significantly greater in the TOUCH condition from 12-28.5-Hz. Conversely, EVS-CoP gain was 63% lower in TOUCH, compared to NO-TOUCH. Our findings show that light touch can re-weight vestibular-evoked responses by reducing their size but also increasing high frequency vestibular contributions for sway. This suggests that the CNS can use novel sensory inputs to alter balance behavior but cannot completely ignore a salient balance cue. New and NoteworthyThis study reveals that minimal fingertip contact (light touch) during balance tasks not only diminishes the impact of electrical vestibular stimulation (EVS) on sway, but also enhances the central nervous systems ability to integrate high-frequency vestibular cues. Specifically, light touch decreases the magnitude of EVS-induced sway while increasing coherence with EVS at higher frequencies, illustrating the central nervous systems capacity to adaptively reweight sensory inputs for improved balance control without fully disregarding dominant cues.

Precision reaching tasks often require corrective submovements for successful completion. Most studies of reaching have focused on single initial movements, and the cortical encoding model was implied to be the same for all submovements. However, corrective submovements may show different encoding patterns from the initial submovement with distinct patterns of activation across the population. Two rhesus macaques performed a precision center-out-task with small targets. Neural activity from single units in primary motor cortex and associated behavioral data were recorded to evaluate movement characteristics. Neural population data and individual neuronal firing rates identified with a peak finding algorithm to identify peaks in hand speed were examined for encoding differences between initial and corrective submovements. Individual neurons were fitted with a regression model that included the reach vector, position, and speed to predict firing rate. For both initial and corrective submovements, the largest effect remained movement direction. We observed a large subset changed their preferred direction greater than 45{degrees} between initial and corrective submovements. Neuronal depth of modulation also showed considerable variation when adjusted for movement speed. By utilizing principal component analysis, neural trajectories of initial and corrective submovements progressed through different neural subspaces. These findings all suggest that different neural encoding patterns exist for initial and corrective submovements within the cortex. We hypothesize that this variation in how neurons change to encode small, corrective submovements might allow for a larger portion of the neural space being used to encode a greater range of movements with varying amplitudes and levels of precision. New and NoteworthyNeuronal recordings matched with kinematic behavior were collected in a precision center-out task that often required corrective movements. We reveal large differences in preferred direction and depth of modulation between initial and corrective submovements across the neural population. We then present a model of the neural population describing how these shifts in tuning create different subspaces for signaling initial and corrective movements likely to improve motor precision.