Showing papers by "John W. Krakauer published in 2007"

Sensory Prediction Errors Drive Cerebellum-Dependent Adaptation of Reaching

Abstract: The cerebellum is an essential part of the neural network involved in adapting goal-directed arm movements. This adaptation might rely on two distinct signals: a sensory prediction error or a motor correction. Sensory prediction errors occur when an initial motor command is generated but the predicted sensory consequences do not match the observed values. In some tasks, these sensory errors are monitored and result in on-line corrective motor output as the movement progresses. Here we asked whether cerebellum-dependent adaptation of reaching relies on sensory or on-line motor corrections. Healthy controls and people with hereditary cerebellar ataxia reached during a visuomotor perturbation in two conditions: "shooting" movements without on-line corrections and "pointing" movements that allowed for on-line corrections. Sensory (i.e., visual) errors were available in both conditions. Results showed that the addition of motor corrections did not influence adaptation in control subjects, suggesting that only sensory errors were needed for learning. Cerebellar subjects were comparably impaired in both adaptation conditions relative to controls, despite abnormal and inconsistent on-line motor correction. Specifically, poor on-line motor corrections were unrelated to cerebellar subjects' adaptation deficit (i.e., adaptation did not worsen), further suggesting that only sensory prediction errors influence this process. Therefore adaptation to visuomotor perturbations depends on the cerebellum and is driven by the mismatch between predicted and actual sensory outcome of motor commands.

Why Don't We Move Faster? Parkinson's Disease, Movement Vigor, and Implicit Motivation

Abstract: People generally select a similar speed for a given motor task, such as reaching for a cup. One well established determinant of movement time is the speed-accuracy trade-off: movement time increases with the accuracy requirement. A second possible determinant is the energetic cost of making a movement. Parkinson's disease (PD), a condition characterized by generalized movement slowing (bradykinesia), provides the opportunity to directly explore this second possibility. We compared reaching movements of patients with PD with those of control subjects in a speed-accuracy trade-off task comprising conditions of increasing difficulty. Subjects completed as many trials as necessary to make 20 movements within a required speed range (trials to criterion, N(c)). Difficulty was reflected in endpoint accuracy and N(c). Patients were as accurate as control subjects in all conditions (i.e., PD did not affect the speed-accuracy trade-off). However, N(c) was consistently higher in patients, indicating reluctance to move fast although accuracy was not compromised. Specifically, the dependence of N(c) on movement energy cost (slope S(N)) was steeper in patients than in control subjects. This difference in S(N) suggests that bradykinesia represents an implicit decision not to move fast because of a shift in the cost/benefit ratio of the energy expenditure needed to move at normal speed. S(N) was less steep, but statistically significant, in control subjects, which demonstrates a role for energetic cost in the normal control of movement speed. We propose that, analogous to the established role of dopamine in explicit reward-seeking behavior, the dopaminergic projection to the striatum provides a signal for implicit "motor motivation."

Towards a computational neuropsychology of action.

Abstract: From a computational perspective, the act of using a tool and making a movement involves solving three kinds of problems: we need to learn the costs that are associated with our actions as well as the rewards that we may experience at various sensory states. We need to learn how our motor commands produce changes in things that we can sense. Finally, we must learn how to actually produce the motor commands that are needed so that we minimize the costs and maximize the rewards. The various computational problems appear to require different kinds of error signals that guide their learning, and might rely on different kinds of contextual cues that allow their recall. Indeed, there may be different neural structures that compute these functions. Here we use this computational framework to review the motor control capabilities of two important patients who have been studied extensively from the neuropsychological perspective: HM, who suffered from severe amnesia; and BG, who suffered from apraxia. When viewed from a computational perspective, the capabilities and deficits of these patients provide insights into the neural basis of our ability to willfully move our limbs and interact with the objects around us.

The complex dynamics of stroke onset and progression.

Abstract: PURPOSE OF REVIEW The aim of this article is to discuss the dynamic nature of cerebrovascular ischemia. RECENT FINDINGS Acute risk factors are superimposed on chronic risk factors to precipitate plaque rupture in myocardial infarction. The interaction between external triggers, such as stress, with internal triggers, such as vasoconstriction, is mediated to a large part by the autonomic nervous system. Numerous algorithms have been developed to describe physiological time-series data, for example heartbeat variability, and reveal complex structure that has diagnostic and prognostic significance. Much of this structure is mediated by the autonomic nervous system. Recent data on stroke triggers, carotid stenosis, transient ischemic attack, and infarct expansion suggest a similar need for detailed physiological measurement and non-linear dynamics in order to understand stroke onset and progression. SUMMARY The picture emerging is that stroke arises as a result of multiple processes with different time constants. The nature and timing of interventions should be tailored to these complex interacting processes. This will require more frequent and varied physiological measurement accompanied by non-linear analytical methods. This new approach, which stresses complex within-subject measurements, will likely make 'one size fits all' solutions to stroke care untenable.