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John W. Krakauer

Bio: John W. Krakauer is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Motor learning & Stroke. The author has an hindex of 66, co-authored 169 publications receiving 21008 citations. Previous affiliations of John W. Krakauer include Columbia University Medical Center & Johns Hopkins University School of Medicine.


Papers
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Journal ArticleDOI
TL;DR: Evidence shows that forward models remain calibrated through motor adaptation: learning driven by sensory prediction errors, and is used to produce a lifetime of calibrated movements.
Abstract: 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.

1,470 citations

Journal ArticleDOI
TL;DR: Findings support the existence of a consolidation mechanism, susceptible to anodal tDCS, which contributes to offline effects but not to online effects or long-term retention, and may hold promise for the rehabilitation of brain injury.
Abstract: Motor skills can take weeks to months to acquire and can diminish over time in the absence of continued practice. Thus, strategies that enhance skill acquisition or retention are of great scientific and practical interest. Here we investigated the effect of noninvasive cortical stimulation on the extended time course of learning a novel and challenging motor skill task. A skill measure was chosen to reflect shifts in the task's speed–accuracy tradeoff function (SAF), which prevented us from falsely interpreting variations in position along an unchanged SAF as a change in skill. Subjects practiced over 5 consecutive days while receiving transcranial direct current stimulation (tDCS) over the primary motor cortex (M1). Using the skill measure, we assessed the impact of anodal (relative to sham) tDCS on both within-day (online) and between-day (offline) effects and on the rate of forgetting during a 3-month follow-up (long-term retention). There was greater total (online plus offline) skill acquisition with anodal tDCS compared to sham, which was mediated through a selective enhancement of offline effects. Anodal tDCS did not change the rate of forgetting relative to sham across the 3-month follow-up period, and consequently the skill measure remained greater with anodal tDCS at 3 months. This prolonged enhancement may hold promise for the rehabilitation of brain injury. Furthermore, these findings support the existence of a consolidation mechanism, susceptible to anodal tDCS, which contributes to offline effects but not to online effects or long-term retention.

1,239 citations

Journal ArticleDOI
TL;DR: This review will focus on arm movements and address the following questions: What is motor learning, do patients with hemiparesis have a learning deficit, and are approaches based on motor learning principles useful for rehabilitation?
Abstract: Purpose of reviewMuch of neurorehabilitation rests on the assumption that patients can improve with practice. This review will focus on arm movements and address the following questions: (i) What is motor learning? (ii) Do patients with hemiparesis have a learning deficit? (iii) Is recovery after in

1,113 citations

Journal ArticleDOI
TL;DR: It is argued that the lesion approach and theoretical motor control can mutually inform each other and one may identify distinct motor control processes from computational models and map them onto specific deficits in patients.
Abstract: The study of patients to infer normal brain function has a long tradition in neurology and psychology. More recently, the motor system has been subject to quantitative and computational characterization. The pur- pose of this review is to argue that the lesion approach and theoretical motor control can mutually inform each other. Specifically, one may identify distinct motor control pro- cesses from computational models and map them onto specific deficits in patients. Here we review some of the impairments in motor control, motor learning and higher- order motor control in patients with lesions of the corti- cospinal tract, the cerebellum, parietal cortex, the basal ganglia, and the medial temporal lobe. We attempt to explain some of these impairments in terms of computa- tional ideas such as state estimation, optimization, prediction, cost, and reward. We suggest that a function of the cerebellum is system identification: to build internal models that predict sensory outcome of motor commands and correct motor commands through internal feedback. A function of the parietal cortex is state estimation: to inte- grate the predicted proprioceptive and visual outcomes with sensory feedback to form a belief about how the commands affected the states of the body and the envi- ronment. A function of basal ganglia is related to optimal control: learning costs and rewards associated with sensory states and estimating the ''cost-to-go'' during execution of a motor task. Finally, functions of the primary and the premotor cortices are related to implementing the optimal control policy by transforming beliefs about proprioceptive and visual states, respectively, into motor commands.

1,026 citations

Journal ArticleDOI
08 Feb 2017-Neuron
TL;DR: A more pluralistic notion of neuroscience is advocated when it comes to the brain-behavior relationship: behavioral work provides understanding, whereas neural interventions test causality.

920 citations


Cited by
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Journal ArticleDOI
06 Jun 1986-JAMA
TL;DR: The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or her own research.
Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

7,563 citations

Book ChapterDOI
01 Jan 2010

5,842 citations

Journal ArticleDOI
08 Sep 1978-Science

5,182 citations

Journal ArticleDOI
TL;DR: This Review looks at some key brain theories in the biological and physical sciences from the free-energy perspective, suggesting that several global brain theories might be unified within a free- energy framework.
Abstract: A free-energy principle has been proposed recently that accounts for action, perception and learning. This Review looks at some key brain theories in the biological (for example, neural Darwinism) and physical (for example, information theory and optimal control theory) sciences from the free-energy perspective. Crucially, one key theme runs through each of these theories — optimization. Furthermore, if we look closely at what is optimized, the same quantity keeps emerging, namely value (expected reward, expected utility) or its complement, surprise (prediction error, expected cost). This is the quantity that is optimized under the free-energy principle, which suggests that several global brain theories might be unified within a free-energy framework.

4,866 citations