Two views on the cognitive brain.

Cognition can be defined as computation over meaningful representations in the brain to produce adaptive behaviour. There are two views on the relationship between cognition and the brain that are largely implicit in the literature. The Sherringtonian view seeks to explain cognition as the result of operations on signals performed at nodes in a network and passed between them that are implemented by specific neurons and their connections in circuits in the brain. The contrasting Hopfieldian view explains cognition as the result of transformations between or movement within representational spaces that are implemented by neural populations. Thus, the Hopfieldian view relegates details regarding the identity of and connections between specific neurons to the status of secondary explainers. Only the Hopfieldian approach has the representational and computational resources needed to develop novel neurofunctional objects that can serve as primary explainers of cognition.

Modular Brain, Entangled Argument.

It has become a truism that the brain is a complex structure. One idea associated with complex systems is that of emergence, which is often characterized as the occurrence of a novel collective property that results from the interactions of individual parts, each of which alone do not have that property. Pessoa in his book argues, plausibly, that given that cognition is the most complex thing the brain does then it will need a new emergence-inflected science to understand it. His subsequent argument, however, does not follow, namely that this will take the form of distributed networks with identity-switching nodes that morph pluripotently from one computation to another. This is not true for whole organisms, which became more complex through compartmentalization and specialization. The brain did the same with hierarchically organized specialized areas.

Investigating and acquiring motor expertise using virtual reality.

After just months of simulated training, on January 19, 2019 a 23-year-old E-sports pro-gamer, Enzo Bonito, took to the racetrack and beat Lucas di Grassi, a Formula E and ex-Formula 1 driver with decades of real-world racing experience. This event raised the possibility that practicing in virtual reality can be surprisingly effective for acquiring motor expertise in real-world tasks. Here, we evaluate the potential of virtual reality to serve as a space for training to expert levels in highly complex real-world tasks in time windows much shorter than those required in the real world and at much lower financial cost without the hazards of the real world. We also discuss how VR can also serve as an experimental platform for exploring the science of expertise more generally.

Did We Get Sensorimotor Adaptation Wrong? Implicit Adaptation as Direct Policy Updating Rather than Forward-Model-Based Learning.

The human motor system can rapidly adapt its motor output in response to errors. The prevailing theory of this process posits that the motor system adapts an internal forward model that predicts the consequences of outgoing motor commands and uses this forward model to plan future movements. However, despite clear evidence that adaptive forward models exist and are used to help track the state of the body, there is no definitive evidence that such models are used in movement planning. An alternative to the forward-model-based theory of adaptation is that movements are generated based on a learned policy that is adjusted over time by movement errors directly ("direct policy learning"). This learning mechanism could act in parallel with, but independent of, any updates to a predictive forward model. Forward-model-based learning and direct policy learning generate very similar predictions about behavior in conventional adaptation paradigms. However, across three experiments with human participants (N = 47, 26 female), we show that these mechanisms can be dissociated based on the properties of implicit adaptation under mirror-reversed visual feedback. Although mirror reversal is an extreme perturbation, it still elicits implicit adaptation; however, this adaptation acts to amplify rather than to reduce errors. We show that the pattern of this adaptation over time and across targets is consistent with direct policy learning but not forward-model-based learning. Our findings suggest that the forward-model-based theory of adaptation needs to be re-examined and that direct policy learning provides a more plausible explanation of implicit adaptation.SIGNIFICANCE STATEMENT The ability of our brain to adapt movements in response to error is one of the most widely studied phenomena in motor learning. Yet, we still do not know the process by which errors eventually result in adaptation. It is known that the brain maintains and updates an internal forward model, which predicts the consequences of motor commands, and the prevailing theory of motor adaptation posits that this updated forward model is responsible for trial-by-trial adaptive changes. Here, we question this view and show instead that adaptation is better explained by a simpler process whereby motor output is directly adjusted by task errors. Our findings cast doubt on long-held beliefs about adaptation.

Dissociation between abnormal motor synergies and impaired reaching dexterity after stroke.

Most patients with stroke experience motor deficits, usually referred to collectively as hemiparesis. Although hemiparesis is one of the most common and clinically recognizable motor abnormalities, it remains undercharacterized in terms of its behavioral subcomponents and their interactions. Hemiparesis comprises both negative and positive motor signs. Negative signs consist of weakness and loss of motor control (dexterity), whereas positive signs consist of spasticity, abnormal resting posture, and intrusive movement synergies (abnormal muscle co-activations during voluntary movement). How positive and negative signs interact, and whether a common mechanism generates them, remains poorly understood. Here, we used a planar, arm-supported reaching task to assess poststroke arm dexterity loss, which we compared with the Fugl-Meyer stroke scale; a measure primarily reflecting abnormal synergies. We examined 53 patients with hemiparesis after a first-time ischemic stroke. Reaching kinematics were markedly more impaired in patients with subacute (<3 mo) compared to chronic (>6 mo) stroke even for similar Fugl-Meyer scores. This suggests a dissociation between abnormal synergies (reflected in the Fugl-Meyer scale) and loss of dexterity, which in turn suggests different underlying mechanisms. Moreover, dynamometry suggested that Fugl-Meyer scores capture weakness as well as abnormal synergies, in line with these two deficits sharing a neural substrate. These findings have two important implications: First, clinical studies that test for efficacy of rehabilitation interventions should specify which component of hemiparesis they are targeting and how they propose to measure it. Metrics used widely for this purpose may not always be chosen appropriately. For example, as we show here, the Fugl-Meyer score may capture some hemiparesis components (abnormal synergies and weakness) but not others (loss of dexterity). Second, there may be an opportunity to design rehabilitation interventions to address specific subcomponents of hemiparesis.NEW & NOTEWORTHY Motor impairment is common after stroke and comprises reduced dexterity, weakness, and abnormal muscle synergies. Here we report that, when matched on an established synergy and weakness scale (Fugl-Meyer), patients with subacute stroke have worse reaching dexterity than chronic ones. This result suggests that the components of hemiparesis are dissociable and have separable mechanisms and, thus, may require distinct assessments and treatments.

No evidence for motor-recovery-related cortical connectivity changes after stroke using resting-state fMRI.

It has been proposed that a form of cortical reorganization (changes in functional connectivity between brain areas) can be assessed with resting-state (rs) functional MRI (fMRI). Here, we report a longitudinal data set collected from 19 patients with subcortical stroke and 11 controls. Patients were imaged up to five times over 1 year. We found no evidence, using rs-fMRI, for longitudinal poststroke cortical connectivity changes despite substantial behavioral recovery. These results could be construed as questioning the value of resting-state imaging. Here, we argue instead that they are consistent with other emerging reasons to challenge the idea of motor-recovery-related cortical reorganization poststroke when conceived of as changes in connectivity between cortical areas.NEW & NOTEWORTHY We investigated longitudinal changes in functional connectivity after stroke. Despite substantial motor recovery, we found no differences in functional connectivity patterns between patients and controls, nor any changes over time. Assuming that rs-fMRI is an adequate method to capture connectivity changes between cortical regions after brain injury, these results provide reason to doubt that changes in cortico-cortical connectivity are the relevant mechanism for promoting motor recovery.

Novel Planar Strain Sensor Design for Capturing 3-Dimensional Fingertip Forces from Patients Affected by Hand Paralysis.

Assessment and therapy for individuals who have hand paresis requires force sensing approaches that can measure a wide range of finger forces in multiple dimensions. Here we present a novel strain-gauge force sensor with 3 degrees of freedom (DOF) designed for use in a hand assessment and rehabilitation device. The sensor features a fiberglass printed circuit board substrate to which eight strain gauges are bonded. All circuity for the sensor is routed directly through the board, which is secured to a larger rehabilitative device via an aluminum frame. After design, the sensing package was characterized for weight, capacity, and resolution requirements. Furthermore, a test sensor was calibrated in a three-axis configuration and validated in the larger spherical workspace to understand how accurate and precise the sensor is, while the sensor has slight shortcomings with validation error, it does satisfy the precision, calibration accuracy, and fine sensing requirements in orthogonal loading, and all structural specifications are met. The sensor is therefore a great candidate for sensing technology in rehabilitation devices that assess dexterity in patients with impaired hand function.

Movement Imitation via an Abstract Trajectory Representation in Dorsal Premotor Cortex.

Humans are particularly good at copying novel and meaningless gestures. The mechanistic and anatomical basis for this specialized imitation ability remains largely unknown. One idea is that imitation occurs by matching body configurations. Here we propose an alternative route to imitation that depends on a body-independent representation of the trajectory path of the end-effector. We studied a group of patients with strokes in the left frontoparietal cortices. We found that they were equally impaired at imitating movement trajectories using the ipsilesional limb (i.e., the nonparetic side) that were cued either by an actor using their whole arm or just by a cursor, suggesting that body configuration information is not always critical for imitation and that a representation of abstract trajectory shape may suffice. In addition, imitation ability was uncorrelated to the ability to identify the trajectory shape, suggesting that imitation deficits were unlikely to arise from perceptual impairments. Finally, a lesion-symptom mapping analysis found that imitation deficits were associated with lesions in left dorsal premotor but not parietal cortex. Together, these findings suggest a novel body-independent route to imitation that relies on the ability to plan abstract movement trajectories within dorsal premotor cortex.SIGNIFICANCE STATEMENT The ability to imitate is critical for rapidly learning to produce new gestures and actions, but how the brain translates observed movements into motor commands is poorly understood. Examining the ability of patients with strokes affecting the left hemisphere revealed that meaningless gestures can be imitated by succinctly representing only the motion of the hand in space, rather than the posture of the entire arm. Moreover, performance deficits correlated with lesions in dorsal premotor cortex, an area not previously associated with impaired imitation of arm postures. These findings thus describe a novel route to imitation that may also be impaired in some patients with apraxia.

Rethinking interhemispheric imbalance as a target for stroke neurorehabilitation.

OBJECTIVE: Patients with chronic stroke have been shown to have failure to release interhemispheric inhibition (IHI) from the intact to the damaged hemisphere before movement execution (premovement IHI). This inhibitory imbalance was found to correlate with poor motor performance in the chronic stage after stroke and has since become a target for therapeutic interventions. The logic of this approach, however, implies that abnormal premovement IHI is causal to poor behavioral outcome and should therefore be present early after stroke when motor impairment is at its worst. To test this idea, in a longitudinal study, we investigated interhemispheric interactions by tracking patients' premovement IHI for one year following stroke. METHODS: We assessed premovement IHI and motor behavior five times over a 1-year period after ischemic stroke in 22 patients and 11 healthy participants. RESULTS: We found that premovement IHI was normal during the acute/subacute period and only became abnormal at the chronic stage; specifically, release of IHI in movement preparation worsened as motor behavior improved. In addition, premovement IHI did not correlate with behavioral measures cross-sectionally, whereas the longitudinal emergence of abnormal premovement IHI from the acute to the chronic stage was inversely correlated with recovery of finger individuation. INTERPRETATION: These results suggest that interhemispheric imbalance is not a cause of poor motor recovery, but instead might be the consequence of underlying recovery processes. These findings call into question the rehabilitation strategy of attempting to rebalance interhemispheric interactions in order to improve motor recovery after stroke. Ann Neurol 2019;85:502-513.

The continued need for scientific monographs: an appreciation of John Rothwell's "Control of human voluntary movement".

Here I write a personal assessment of Professor John Rothwell's seminal book, "Control of Human Voluntary Movement". I focus on the second edition published in 1994, reflecting on its importance over the last 25 years and explaining why it remains highly relevant for the motor control field to this day. It is to be hoped that a third edition will be written that updates the physiology and unifies it with computational motor control. The book attests to the continuing importance of monographs in science, as they uniquely allow for long-form narrative and coherent synthesis.

Can patients with cerebellar disease switch learning mechanisms to reduce their adaptation deficits?

Systematic perturbations in motor adaptation tasks are primarily countered by learning from sensory-prediction errors, with secondary contributions from other learning processes. Despite the availability of these additional processes, particularly the use of explicit re-aiming to counteract observed target errors, patients with cerebellar degeneration are surprisingly unable to compensate for their sensory-prediction error deficits by spontaneously switching to another learning mechanism. We hypothesized that if the nature of the task was changed-by allowing vision of the hand, which eliminates sensory-prediction errors-patients could be induced to preferentially adopt aiming strategies to solve visuomotor rotations. To test this, we first developed a novel visuomotor rotation paradigm that provides participants with vision of their hand in addition to the cursor, effectively setting the sensory-prediction error signal to zero. We demonstrated in younger healthy control subjects that this promotes a switch to strategic re-aiming based on target errors. We then showed that with vision of the hand, patients with cerebellar degeneration could also switch to an aiming strategy in response to visuomotor rotations, performing similarly to age-matched participants (older controls). Moreover, patients could retrieve their learned aiming solution after vision of the hand was removed (although they could not improve beyond what they retrieved), and retain it for at least 1 year. Both patients and older controls, however, exhibited impaired overall adaptation performance compared to younger healthy controls (age 18-33 years), likely due to age-related reductions in spatial and working memory. Patients also failed to generalize, i.e. they were unable to adopt analogous aiming strategies in response to novel rotations. Hence, there appears to be an inescapable obligatory dependence on sensory-prediction error-based learning-even when this system is impaired in patients with cerebellar disease. The persistence of sensory-prediction error-based learning effectively suppresses a switch to target error-based learning, which perhaps explains the unexpectedly poor performance by patients with cerebellar degeneration in visuomotor adaptation tasks.

Practice induces a qualitative change in the memory representation for visuomotor learning.

Adaptation of our movements to changes in the environment is known to be supported by multiple learning processes that operate in parallel. One is an implicit recalibration process driven by sensory-prediction errors; the other process counters the perturbation through more deliberate compensation. Prior experience is known to enable adaptation to occur more rapidly, a phenomenon known as "savings," but exactly how experience alters each underlying learning process remains unclear. We measured the relative contributions of implicit recalibration and deliberate compensation to savings across 2 days of practice adapting to a visuomotor rotation. The rate of implicit recalibration showed no improvement with repeated practice. Instead, practice led to deliberate compensation being expressed even when preparation time was very limited. This qualitative change is consistent with the proposal that practice establishes a cached association linking target locations to appropriate motor output, facilitating a transition from deliberate to automatic action selection.NEW & NOTEWORTHY Recent research has shown that savings for visuomotor adaptation is attributable to retrieval of intentional, strategic compensation. This does not seem consistent with the implicit nature of memory for motor skills and calls into question the validity of visuomotor adaptation of reaching movements as a model for motor skill learning. Our findings suggest a solution: that additional practice adapting to a visuomotor perturbation leads to the caching of the initially explicit strategy for countering it.

Evidence for a subcortical origin of mirror movements after stroke: a longitudinal study.

Following a stroke, mirror movements are unintended movements that appear in the non-paretic hand when the paretic hand voluntarily moves. Mirror movements have previously been linked to overactivation of sensorimotor areas in the non-lesioned hemisphere. In this study, we hypothesized that mirror movements might instead have a subcortical origin, and are the by-product of subcortical motor pathways upregulating their contributions to the paretic hand. To test this idea, we first characterized the time course of mirroring in 53 first-time stroke patients, and compared it to the time course of activities in sensorimotor areas of the lesioned and non-lesioned hemispheres (measured using functional MRI). Mirroring in the non-paretic hand was exaggerated early after stroke (Week 2), but progressively diminished over the year with a time course that parallelled individuation deficits in the paretic hand. We found no evidence of cortical overactivation that could explain the time course changes in behaviour, contrary to the cortical model of mirroring. Consistent with a subcortical origin of mirroring, we predicted that subcortical contributions should broadly recruit fingers in the non-paretic hand, reflecting the limited capacity of subcortical pathways in providing individuated finger control. We therefore characterized finger recruitment patterns in the non-paretic hand during mirroring. During mirroring, non-paretic fingers were broadly recruited, with mirrored forces in homologous fingers being only slightly larger (1.76 times) than those in non-homologous fingers. Throughout recovery, the pattern of finger recruitment during mirroring for patients looked like a scaled version of the corresponding control mirroring pattern, suggesting that the system that is responsible for mirroring in controls is upregulated after stroke. Together, our results suggest that post-stroke mirror movements in the non-paretic hand, like enslaved movements in the paretic hand, are caused by the upregulation of a bilaterally organized subcortical system.

Error correction, sensory prediction, and adaptation in motor control.

Motor control is the study of how organisms make accurate goal-directed movements. Here we consider two problems that the motor system must solve in order to achieve such control. The first problem is that sensory feedback is noisy and delayed, which can make movements inaccurate and unstable. The second problem is that the relationship between a motor command and the movement it produces is variable, as the body and the environment can both change. A solution is to build adaptive internal models of the body and the world. The predictions of these internal models, called forward models because they transform motor commands into sensory consequences, can be used to both produce a lifetime of calibrated movements, and to improve the ability of the sensory system to estimate the state of the body and the world around it. Forward models are only useful if they produce unbiased predictions. Evidence shows that forward models remain calibrated through motor adaptation: learning driven by sensory prediction errors.

Independence of Movement Preparation and Movement Initiation.

Initiating a movement in response to a visual stimulus takes significantly longer than might be expected on the basis of neural transmission delays, but it is unclear why. In a visually guided reaching task, we forced human participants to move at lower-than-normal reaction times to test whether normal reaction times are strictly necessary for accurate movement. We found that participants were, in fact, capable of moving accurately ∼80 ms earlier than their reaction times would suggest. Reaction times thus include a seemingly unnecessary delay that accounts for approximately one-third of their duration. Close examination of participants' behavior in conventional reaction-time conditions revealed that they generated occasional, spontaneous errors in trials in which their reaction time was unusually short. The pattern of these errors could be well accounted for by a simple model in which the timing of movement initiation is independent of the timing of movement preparation. This independence provides an explanation for why reaction times are usually so sluggish: delaying the mean time of movement initiation relative to preparation reduces the risk that a movement will be initiated before it has been appropriately prepared. Our results suggest that preparation and initiation of movement are mechanistically independent and may have a distinct neural basis. The results also demonstrate that, even in strongly stimulus-driven tasks, presentation of a stimulus does not directly trigger a movement. Rather, the stimulus appears to trigger an internal decision whether to make a movement, reflecting a volitional rather than reactive mode of control.

The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly (experiment 1) or gradually (experiment 2). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability (experiment 3). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials.NEW & NOTEWORTHY Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory prediction errors to update an internal model. Here we show that these individuals also have difficulty in discovering an aiming solution to overcome their adaptation deficit, suggesting a new role for the cerebellum in sensorimotor adaptation tasks.

Separable systems for recovery of finger strength and control after stroke.

Impaired hand function after stroke is a major cause of long-term disability. We developed a novel paradigm that quantifies two critical aspects of hand function, strength, and independent control of fingers (individuation), and also removes any obligatory dependence between them. Hand recovery was tracked in 54 patients with hemiparesis over the first year after stroke. Most recovery of strength and individuation occurred within the first 3 mo. A novel time-invariant recovery function was identified: recovery of strength and individuation were tightly correlated up to a strength level of ~60% of estimated premorbid strength; beyond this threshold, strength improvement was not accompanied by further improvement in individuation. Any additional improvement in individuation was attributable instead to a second process that superimposed on the recovery function. We conclude that two separate systems are responsible for poststroke hand recovery: one contributes almost all of strength and some individuation; the other contributes additional individuation.NEW & NOTEWORTHY We tracked recovery of the hand over a 1-yr period after stroke in a large cohort of patients, using a novel paradigm that enabled independent measurement of finger strength and control. Most recovery of strength and control occurs in the first 3 mo after stroke. We found that two separable systems are responsible for motor recovery of hand: one contributes strength and some dexterity, whereas a second contributes additional dexterity.

The influence of movement preparation time on the expression of visuomotor learning and savings.

Following a change in the environment or motor apparatus, human subjects are able to rapidly compensate their movements to recover accurate performance. This ability to adapt is thought to be achieved through multiple, qualitatively distinct learning processes acting in parallel. It is unclear, however, what the relative contributions of these multiple processes are during learning. In particular, long-term memories in such paradigms have been extensively studied through the phenomenon of savings-faster adaptation to a given perturbation the second time it is experienced-but it is unclear which components of learning contribute to this effect. Here we show that distinct components of learning in an adaptation task can be dissociated based on the amount of preparation time they require. During adaptation, we occasionally forced subjects to generate movements at very low preparation times. Early in learning, subjects expressed only a limited amount of their prior learning in these trials, though performance improved gradually with further practice. Following washout, subjects exhibited a strong and persistent aftereffect in trials in which preparation time was limited. When subjects were exposed to the same perturbation twice in successive days, they adapted faster the second time. This savings effect was, however, not seen in movements generated at low preparation times. These results demonstrate that preparation time plays a critical role in the expression of some components of learning but not others. Savings is restricted to those components that require prolonged preparation to be expressed and might therefore reflect a declarative rather than procedural form of memory.

Persistent residual errors in motor adaptation tasks: reversion to baseline and exploratory escape.

When movements are perturbed in adaptation tasks, humans and other animals show incomplete compensation, tolerating small but sustained residual errors that persist despite repeated trials. State-space models explain this residual asymptotic error as interplay between learning from error and reversion to baseline, a form of forgetting. Previous work using zero-error-clamp trials has shown that reversion to baseline is not obligatory and can be overcome by manipulating feedback. We posited that novel error-clamp trials, in which feedback is constrained but has nonzero error and variance, might serve as a contextual cue for recruitment of other learning mechanisms that would then close the residual error. When error clamps were nonzero and had zero variance, human subjects changed their learning policy, using exploration in response to the residual error, despite their willingness to sustain such an error during the training block. In contrast, when the distribution of feedback in clamp trials was naturalistic, with persistent mean error but also with variance, a state-space model accounted for behavior in clamps, even in the absence of task success. Therefore, when the distribution of errors matched those during training, state-space models captured behavior during both adaptation and error-clamp trials because error-based learning dominated; when the distribution of feedback was altered, other forms of learning were triggered that did not follow the state-space model dynamics exhibited during training. The residual error during adaptation appears attributable to an error-dependent learning process that has the property of reversion toward baseline and that can suppress other forms of learning.