Optimal feedback control and the neural basis of volitional motor control

Scott, Stephen H.

doi:10.1038/nrn1427

Cited by 863 publications

(776 citation statements)

References 163 publications

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“…A sharpening in the distribution of the fluctuations in the COP is also seen for postural sway during quiet standing when the Achilles' tendons are subjected to low frequency, low amplitude periodic vibration (Figures 3b and d). These observations support the concept that human balance control is maintained by a simple "drift and act" mechanism [21,35,36,37,38,53]. This mechanism proposes that the basin of attraction for the stabilized upright position is small enough so that escapes ("falls") are possible [54,63].…”

Section: Research Projectssupporting

confidence: 68%

A Team Approach to Undergraduate Research in Biomathematics: Balance Control

Milton

Radunskaya

et al. 2011

Math. Model. Nat. Phenom.

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Abstract. The question, how does an organism maintain balance? provides a unifying theme to introduce undergraduate students to the use of mathematics and modeling techniques in biological research. The availability of inexpensive high speed motion capture cameras makes it possible to collect the precise and reliable data that facilitates the development of relevant mathematical models. An in-house laboratory component ensures that students have the opportunity to directly compare prediction to observation and motivates the development of projects that push the boundaries of the subject. The projects, by their nature, readily lend themselves to the formation of inter-disciplinary student research teams. Thus students have the opportunity to learn skills essential for success in today's workplace including productive team work, critical thinking, problem solving, project management, and effective communication.

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Section: Research Projectssupporting

confidence: 68%

A Team Approach to Undergraduate Research in Biomathematics: Balance Control

Milton

Radunskaya

et al. 2011

Math. Model. Nat. Phenom.

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“…In several studies, the late phase, but not the early, was accompanied by changes in primary motor cortex (MI): imaging techniques revealed increased activity when humans learned new sequential finger movements (Ungerleider et al, 2002), and motor map reorganization and synapse formation have been observed when rats learned a novel multijoint reachand-grasp task (Kleim et al, 2004). These findings, together with a diversity of findings showing learning-dependant plasticity in MI (Sanes and Donoghue, 2000), suggest that a representation of the newly acquired skill is formed in MI during the late stages of learning, hence allowing for efficient generation and control of well trained movements (Porter and Lemon, 1993;Scott, 2004). Lately, several studies have reported changes in MI within a time scale of one session, i.e., dozens of trials (Laubach et al, 2000;Li et al, 2001;Cohen and Nicolelis, 2004).…”

Section: Introductionmentioning

confidence: 83%

Emerging Patterns of Neuronal Responses in Supplementary and Primary Motor Areas during Sensorimotor Adaptation

Paz¹,

Natan²,

Boraud³

et al. 2005

J. Neurosci.

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Acquisition and retention of sensorimotor skills have been extensively investigated psychophysically, but little is known about the underlying neuronal mechanisms. Here we examine the evolution of neural activity associated with adaptation to new kinematic tasks in two cortical areas: the caudal supplementary motor area (SMA proper), and the primary motor cortex (MI). We investigate the hypothesis that adaptation starts at premotor areas, i.e., higher in the hierarchy of computation, until a stable representation is formed in primary areas. In accordance with previous studies, we found that adaptation can be characterized by two phases: an early phase that is accompanied by fast and substantial reduction of errors, followed by a late phase with slower and more moderate improvements in behavior. We used unsupervised clustering to separate the activity of the single cells into groups of cells with similar response patterns, under the assumption that each such subpopulation forms a functional unit. We specifically observed the number of clusters in each cortical area during early and late phases of the adaptation and found that the number of clusters is higher in the SMA during early phases of adaptation. In contrast, a higher number of clusters was observed in MI only during late phases. Our results suggest a new approach to analyze responses of large populations of neurons and use it to show a hierarchy of dynamic reorganization of functional groups during adaptation.

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“…This suggestion has reignited interest in the long-latency reflex, a natural candidate to mediate an intelligent feedback signal because it occurs very quickly in response to a mechanical perturbation and exhibits a wide range of sophistication (Diedrichsen et al 2010;Scott 2004).…”

mentioning

confidence: 99%

The long-latency reflex is composed of at least two functionally independent processes

Pruszynski

Kurtzer

Scott

2011

Journal of Neurophysiology

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113

116

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Pruszynski JA, Kurtzer I, Scott SH. The long-latency reflex is composed of at least two functionally independent processes. J Neurophysiol 106: 449 -459, 2011. First published May 4, 2011 doi:10.1152/jn.01052.2010.-The nervous system counters mechanical perturbations applied to the arm with a stereotypical sequence of muscle activity, starting with the short-latency stretch reflex and ending with a voluntary response. Occurring between these two events is the enigmatic long-latency reflex. Although researchers have been fascinated by the long-latency reflex for over 60 years, some of the most basic questions about this response remain unresolved and often debated. In the present study we help resolve one such question by providing clear evidence that the human long-latency reflex during a naturalistic motor task is not a single functional response; rather, it appears to reflect the output of (at least) two functionally independent processes that overlap in time and sum linearly. One of these functional components shares an important attribute of the short-latency reflex (i.e., automatic gain scaling, sensitivity to background load), and the other shares a defining feature of voluntary control (i.e., task dependency, sensitivity to goal target position). We further show that the task-dependent component of long-latency activity reflects a feedback control process rather than the simplest triggered reaction to a mechanical stimulus. upper limb; feedback; background load; intent; spatial target

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Optimal feedback control and the neural basis of volitional motor control

Cited by 863 publications

References 163 publications

A Team Approach to Undergraduate Research in Biomathematics: Balance Control

A Team Approach to Undergraduate Research in Biomathematics: Balance Control

Emerging Patterns of Neuronal Responses in Supplementary and Primary Motor Areas during Sensorimotor Adaptation

The long-latency reflex is composed of at least two functionally independent processes

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