Concurrent changes in shortening reaction latency and reaction time of forearm muscles in post-stroke patients

Miscio, Giacinta; Pisano, Fabrizio; Conte, Carmen Del; Colombo, Roberto; Schieppati, Marco

doi:10.1007/s10072-005-0523-0

Cited by 8 publications

(3 citation statements)

References 30 publications

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“…A better understanding of the brain areas activated during both training techniques in healthy subjects could prove useful to help choose which one to apply for people with different types of brain injury, such as a stroke. Indeed, individuals with a stroke can exhibit greater cognitive movement planning time than healthy individuals (Daly et al 2006 ) and because of the presence of motor impairments at the affected limb, their timing performance can be twice as long as the one of the unaffected limb (Bi and Wan 2013 ; Freitas et al 2011 ; Miscio et al 2006 ), jeopardizing the accomplishment of daily tasks. EA/HG robotic training has been used to help improve timing performance at the chronic phase of a stroke, whereas the side of the brain lesion was shown to influence the response to EA/HG robotic training (Bouchard et al 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Neural circuits activated by error amplification and haptic guidance training techniques during performance of a timing-based motor task by healthy individuals

et al. 2018

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To promote motor learning, robotic devices have been used to improve subjects’ performance by guiding desired movements (haptic guidance—HG) or by artificially increasing movement errors to foster a more rapid learning (error amplification—EA). To better understand the neurophysiological basis of motor learning, a few studies have evaluated brain regions activated during EA/HG, but none has compared both approaches. The goal of this study was to investigate using fMRI which brain networks were activated during a single training session of HG/EA in healthy adults learning to play a computerized pinball-like timing task. Subjects had to trigger a robotic device by flexing their wrist at the correct timing to activate a virtual flipper and hit a falling ball towards randomly positioned targets. During training with HG/EA, subjects’ timing errors were decreased/increased, respectively, by the robotic device to delay or accelerate their wrist movement. The results showed that at the beginning of the training period with HG/EA, an error-detection network, including cerebellum and angular gyrus, was activated, consistent with subjects recognizing discrepancies between their intended actions and the actual movement timing. At the end of the training period, an error-detection network was still present for EA, while a memory consolidation/automatization network (caudate head and parahippocampal gyrus) was activated for HG. The results indicate that training movement with various kinds of robotic input relies on different brain networks. Better understanding the neurophysiological underpinnings of brain processes during HG/EA could prove useful for optimizing rehabilitative movement training for people with different patterns of brain damage.

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Section: Introductionmentioning

confidence: 99%

Neural circuits activated by error amplification and haptic guidance training techniques during performance of a timing-based motor task by healthy individuals

et al. 2018

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“…In addition to its value as a predictor of performance for a variety of functional tasks, RT is known to be prolonged in many of the populations commonly encountered in physiatric practice. Examples include persons with stroke [16], traumatic brain injury [17,18], dementia [19,20], and polyneuropathy [21,22], and in those experiencing adverse effects from medication [23,24]. The role of RT prolongation in sports‐related concussion deserves special mention.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Role of Feedback and Motivation in Clinical Reaction Time Assessment

Eckner

Chandran

Richardson

2011

PM&R

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Objective To investigate the influence of performance feedback and motivation during two tests of simple visuo-motor reaction time. Design Cross-sectional, observational study. Setting Outpatient academic physiatry clinic. Participants 31 healthy adults aged 54 ± 15 years. Methods Participants completed a clinical test of reaction time (RTclin) and a computerized test of reaction time with and without performance feedback (RTcompFB and RTcompNoFB, respectively) in randomly assigned order. They then ranked their degree of motivation during each test. RTclin measured the time required to catch a suspended vertical shaft by hand closure after its release by the examiner. RTcompFB and RTcompNoFB both measured the time required to press a computer key in response to a visual cue displayed on a computer monitor. Performance feedback (visual display of the previous trial and summary results) was provided for RTcompFB, but not for RTcompNoFB. Main Outcome Measurements Means and standard deviations of RTclin, RTcompFB, and RTcompNoFB; Participants’ self-reported motivation on a 5-point Likert scale for each test. Results There were significant differences in both the means and standard deviations of RTclin, RTcompFB, and RTcompNoFB (F2,60 = 81.66, p < 0.0001; F2,60 = 32.46, p < 0.0001, respectively) with RTclin being both the fastest and least variable of the reaction time measures. RTclin was more strongly correlated with RTcompFB (r = 0.449, p = 0.011) than with RTcompNoFB (r = 0.314, p = 0.086). Participants reported similar levels of motivation between RTclin and RTcompFB, both of which were reported to be more motivating than RTcompNoFB. Conclusions The stronger correlation between RTclin and RTcompFB as well as the higher reported motivation during RTclin and RTcompFB testing suggest that performance feedback is a positive motivating factor that is implicit to RTclin testing. RTclin is a simple, inexpensive technique for measuring reaction time and appears to be an intrinsically motivating task. This motivation may promote faster, more consistent reaction time performance compared to currently available computerized programs, which do not typically provide performance feedback.

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“…, 2003; McDonnell et al. , 2006; Miscio et al. , 2006) and Parkinsonian patients (Müller & Abbs, 1990; Gauntlett‐Gilbert & Brown, 1998).…”

Section: Introductionmentioning

confidence: 99%

Role of the primary motor and sensory cortex in precision grasping: a transcranial magnetic stimulation study

Schabrun

Ridding

Miles

2008

Eur J of Neuroscience

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Human precision grip requires precise scaling of the grip force to match the weight and frictional conditions of the object. The ability to produce an accurately scaled grip force prior to lifting an object is thought to be the result of an internal feedforward model. However, relatively little is known about the roles of various brain regions in the control of such precision grip-lift synergies. Here we investigate the role of the primary motor (M1) and sensory (S1) cortices during a grip-lift task using inhibitory transcranial magnetic theta-burst stimulation (TBS). Fifteen healthy individuals received 40 s of either (i) M1 TBS, (ii) S1 TBS or (iii) sham stimulation. Following a 5-min rest, subjects lifted a manipulandum five times using a precision grip or completed a simple reaction time task. Following S1 stimulation, the duration of the pre-load phase was significantly longer than following sham stimulation. Following M1 stimulation, the temporal relationship between changes in grip and load force was altered, with changes in grip force coming to lag behind changes in load force. This result contrasts with that seen in the sham condition where changes in grip force preceded changes in load force. No significant difference was observed in the simple reaction task following either M1 or S1 stimulation. These results further quantify the contribution of the M1 to anticipatory grip-force scaling. In addition, they provide the first evidence for the contribution of S1 to object manipulation, suggesting that sensory information is not necessary for optimal functioning of anticipatory control.

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Concurrent changes in shortening reaction latency and reaction time of forearm muscles in post-stroke patients

Cited by 8 publications

References 30 publications

Neural circuits activated by error amplification and haptic guidance training techniques during performance of a timing-based motor task by healthy individuals

Neural circuits activated by error amplification and haptic guidance training techniques during performance of a timing-based motor task by healthy individuals

Investigating the Role of Feedback and Motivation in Clinical Reaction Time Assessment

Role of the primary motor and sensory cortex in precision grasping: a transcranial magnetic stimulation study

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