TIKL: Development of a Wearable Vibrotactile Feedback Suit for Improved Human Motor Learning

2007 ◽  
Vol 23 (5) ◽  
pp. 919-926 ◽  
Author(s):  
J.. Lieberman ◽  
C.. Breazeal
Keyword(s):  
Motor Learning ◽  
Vibrotactile Feedback ◽  
Human Motor

scholarly journals Vibrotactile feedback as a tool to improve motor learning and sports performance: a systematic review

2017 ◽  
Vol 3 (1) ◽  
pp. e000216 ◽  
Author(s):  
Eric van Breda ◽  
Stijn Verwulgen ◽  
Wim Saeys ◽  
Katja Wuyts ◽  
Thomas Peeters ◽  
...  
Keyword(s):  
Systematic Review ◽  
Motor Learning ◽  
Sports Performance ◽  
Vibrotactile Feedback

scholarly journals Somatosensory cortical excitability changes precede those in motor cortex during human motor learning

2019 ◽  
Vol 122 (4) ◽  
pp. 1397-1405 ◽  
Author(s):  
Hiroki Ohashi ◽  
Paul L. Gribble ◽  
David J. Ostry
Keyword(s):  
Motor Cortex ◽  
Motor Learning ◽  
Evoked Potentials ◽  
Somatosensory Cortex ◽  
Somatosensory Evoked Potentials ◽  
Motor Skill ◽  
Cortical Excitability ◽  
Motor Evoked Potentials ◽  
Human Motor ◽  
Motor Cortical

Motor learning is associated with plasticity in both motor and somatosensory cortex. It is known from animal studies that tetanic stimulation to each of these areas individually induces long-term potentiation in its counterpart. In this context it is possible that changes in motor cortex contribute to somatosensory change and that changes in somatosensory cortex are involved in changes in motor areas of the brain. It is also possible that learning-related plasticity occurs in these areas independently. To better understand the relative contribution to human motor learning of motor cortical and somatosensory plasticity, we assessed the time course of changes in primary somatosensory and motor cortex excitability during motor skill learning. Learning was assessed using a force production task in which a target force profile varied from one trial to the next. The excitability of primary somatosensory cortex was measured using somatosensory evoked potentials in response to median nerve stimulation. The excitability of primary motor cortex was measured using motor evoked potentials elicited by single-pulse transcranial magnetic stimulation. These two measures were interleaved with blocks of motor learning trials. We found that the earliest changes in cortical excitability during learning occurred in somatosensory cortical responses, and these changes preceded changes in motor cortical excitability. Changes in somatosensory evoked potentials were correlated with behavioral measures of learning. Changes in motor evoked potentials were not. These findings indicate that plasticity in somatosensory cortex occurs as a part of the earliest stages of motor learning, before changes in motor cortex are observed. NEW & NOTEWORTHY We tracked somatosensory and motor cortical excitability during motor skill acquisition. Changes in both motor cortical and somatosensory excitability were observed during learning; however, the earliest changes were in somatosensory cortex, not motor cortex. Moreover, the earliest changes in somatosensory cortical excitability predict the extent of subsequent learning; those in motor cortex do not. This is consistent with the idea that plasticity in somatosensory cortex coincides with the earliest stages of human motor learning.

Closing the Loop: From Motor Neuroscience to Neurorehabilitation

2018 ◽  
Vol 41 (1) ◽  
pp. 415-429 ◽  
Author(s):  
Ryan T. Roemmich ◽  
Amy J. Bastian
Keyword(s):  
Motor Learning ◽  
Neural Control ◽  
Behavioral Studies ◽  
Closing The Loop ◽  
Motor Learning And Control ◽  
Human Motor ◽  
Basic Studies ◽  
The Right ◽  
And Control ◽  
Neural Control Of Movement

The fields of human motor control, motor learning, and neurorehabilitation have long been linked by the intuition that understanding how we move (and learn to move) leads to better rehabilitation. In reality, these fields have remained largely separate. Our knowledge of the neural control of movement has expanded, but principles that can directly impact rehabilitation efficacy remain somewhat sparse. This raises two important questions: What can basic studies of motor learning really tell us about rehabilitation, and are we asking the right questions to improve the lives of patients? This review aims to contextualize recent advances in computational and behavioral studies of human motor learning within the framework of neurorehabilitation. We also discuss our views of the current challenges facing rehabilitation and outline potential clinical applications from recent theoretical and basic studies of motor learning and control.

scholarly journals Role of the somatosensory cortex in motor memory consolidation

2020 ◽  
Vol 124 (3) ◽  
pp. 648-651
Author(s):  
Manasi Wali
Keyword(s):  
Motor Learning ◽  
Somatosensory Cortex ◽  
Memory Consolidation ◽  
Motor Memory ◽  
Implicit Motor Learning ◽  
Implicit Motor ◽  
Human Motor ◽  
Plos Biol

Motor memories become resistant to interference by the process of consolidation, which leads to long-term retention. Studies have shown involvement of the somatosensory cortex in motor learning-related plasticity, but not directly in motor memory consolidation. This Neuro Forum article reviews evidence from a continuous theta-burst transcranial magnetic stimulation (cTBS) study by Kumar and colleagues (Kumar N, Manning TF, Ostry DJ. PLoS Biol 17: e3000469, 2019) that demonstrates the role of somatosensory, rather than motor, cortex in human motor memory consolidation during implicit motor learning.

Reconsideration of Measurement of Error in Human Motor Learning

1988 ◽  
Vol 67 (2) ◽  
pp. 568-570 ◽  
Author(s):  
Darryl A. Crabtree ◽  
Laura R. Antrim
Keyword(s):  
Motor Learning ◽  
Error Analysis ◽  
Constant Error ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Error Measurement ◽  
Variable Error ◽  
Human Motor ◽  
Parsimonious Model

Human motor learning is often measured by error scores. The convention of using mean absolute error, mean constant error, and variable error shows lack of desirable parsimony and interpretability. This paper provides the background of error measurement and states criticisms of conventional methodology. A parsimonious model of error analysis is provided, along with operationalized interpretations and implications for motor learning. Teaching, interpreting, and using error scores in research may be simplified and facilitated with the model.

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