Showing papers by "John W. Krakauer published in 2021"

Two views on the cognitive brain.

Abstract: 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.

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

Abstract: 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.

Comparing a Novel Neuroanimation Experience to Conventional Therapy for High-Dose Intensive Upper-Limb Training in Subacute Stroke: The SMARTS2 Randomized Trial

Abstract: BackgroundEvidence from animal studies suggests that greater reductions in poststroke motor impairment can be attained with significantly higher doses and intensities of therapy focused on movement...

The explicit/implicit distinction in studies of visuomotor learning: Conceptual and methodological pitfalls.

Abstract: A ubiquitous problem in science - from a physicist estimating the position of an electron (Heisenberg, 1927) to a social scientist conducting opinion polling (Bishop, 2004) - is that the measurement process can change the measured quantity itself. In addition, variation in measurement methodology may inadvertently favor one component of the measured quantity over another, leading to different results even though the measured quantity has not changed - for example, both gross domestic product and gross national product assess the economic activity of a country, but focus on different components.

The strength of the corticospinal tract not the reticulospinal tract determines upper-limb impairment level and capacity for skill-acquisition in the sub-acute post-stroke period

Abstract: Background. Upper-limb impairment in patients with chronic stroke appears to be partly attributable to an upregulated reticulospinal tract (RST). Here, we assessed whether the impact of corticospin...

The proportional recovery rule redux: Arguments for its biological and predictive relevance

Abstract: The proportional recovery rule (PRR) posits that most stroke survivors can expect to reverse a fixed proportion of motor impairment. As a statistical model, the PRR explicitly relates change scores to baseline values -- an approach that has the potential to introduce artifacts and flawed conclusions. We describe approaches that can assess associations between baseline and changes from baseline while avoiding artifacts either due to mathematical coupling or regression to the mean due to measurement error. We also describe methods that can compare different biological models of recovery. Across several real datasets, we find evidence for non-artifactual associations between baseline and change, and support for the PRR compared to alternative models. We conclude that the PRR remains a biologically-relevant model of recovery, and also introduce a statistical perspective that can be used to assess future models.

Black-box testing in motor sequence learning

Abstract: During learning of novel motor sequences, practice leads to the consolidation of hierarchical structures, namely motor chunks, facilitating the accurate execution of sequences at increasing speeds. Recent studies show that such hierarchical structures are largely represented upstream of the primary motor cortex in the motor network, suggesting their function to be more related to the encoding, storage, and retrieval of sequences rather than their sole execution. We isolated different components of motor skill acquisition related to the consolidation of spatiotemporal features and followed their evolution over training. We found that optimal motor skill acquisition relies on the storage of the spatial features of the sequence in memory, followed by the optimization of its execution and increased execution speeds (i.e., a shift in the speed-accuracy trade-off) early in training, supporting the model proposed by Hikosaka in 1999. Contrasting the dynamics of these components during ageing, we identified less-than-optimal mechanisms in older adults explaining the observed differences in performance. We applied noninvasive brain stimulation in an attempt to support the aging brain to compensate for these deficits. The present study found that anodal direct current stimulation applied over the motor cortex restored the mechanisms involved in the consolidation of spatial features, without directly affecting the speed of execution of the sequence. This led older adults to sharply improve their accuracy, resulting in an earlier yet gradual emergence of motor chunks. The results suggest the early storage of the sequence in memory, largely independent of motor practice, is crucial for an optimal motor acquisition and retrieval of this motor behavior. Nevertheless, the consolidation of optimal temporal patterns, detected as motor chunks at a behavioral level, is not a direct consequence of storing the sequence elements, but rather of motor practice.

Positive and negative stroke signs revisited: dissociations between synergies, weakness, and impaired reaching dexterity

Abstract: Stroke affects more than ten million individuals in the world each year, with most victims experiencing motor deficits usually referred to collectively as hemiparesis. While hemiparesis is one of the most common and clinically recognizable abnormalities, it remains under-characterized in terms of its behavioral subcomponents and how they combine to produce the overall post-stroke motor deficit. Hemiparesis is comprised of 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 whereby multiple muscles or joints become co-activated during voluntary movement. How positive and negative signs interact, and whether a common mechanism generates them, remains poorly understood. Here we employed a planar reaching task to assess post-stroke arm dexterity loss, which we compared to 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 ( 6 months) stroke even when matched for Fugl-Meyer score. While our reaching dexterity task mitigated the effect of weakness on synergies through the use of arm-weight support, we found that the Fugl-Meyer scale was a poor predictor of arm dexterity. This suggests a dissociation between abnormal synergies (reflected in the Fugl-Meyer scale) and loss of dexterity, which in turns suggests that different mechanisms may generate these particular positive and negative signs. At the same time, dynamometry suggested that Fugl-Meyer scores may 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. Second, there may be an opportunity to design specific rehabilitation interventions to address specific subcomponents of the hemiparesis syndrome.