Dataset Information

Combining motor imagery with action observation training does not lead to a greater autonomic nervous system response than motor imagery alone during simple and functional movements: a randomized controlled trial.

ABSTRACT: Both motor imagery (MI) and action observation (AO) trigger the activation of the neurocognitive mechanisms that underlie the planning and execution of voluntary movements in a manner that resembles how the action is performed in a real way. The main objective of the present study was to compare the autonomic nervous system (ANS) response in an isolated MI group compared to a combined MI + AO group. The mental tasks were based on two simple movements that are recorded in the revised movement imagery questionnaire in third-person perspective. The secondary objective of the study was to test if there was any relationship between the ANS variables and the ability to generate mental motor imagery, the mental chronometry and the level of physical activity. The main outcomes that were measured were heart rate, respiratory rate and electrodermal activity. A Biopac MP150 system, a measurement device of autonomic changes, was used for the quantification and evaluation of autonomic variables. Forty five asymptomatic subjects were selected and randomized in three groups: isolated MI, MI + AO and control group (CG). In regards to the activation of the sympathetic nervous system (SNS), no differences were observed between MI and MI + AO groups (p > .05), although some differences were found between both groups when compared to the CG (p < .05). Additionally, even though no associations were reported between the ANS variables and the ability to generate mental motor imagery, moderate-strong positive associations were found in mental chronometry and the level of physical activity. Our results suggest that MI and MI + AO, lead to an activation of the SNS, although there are no significant differences between the two groups. Based on results obtained, we suggest that tasks of low complexity, providing a visual input through the AO does not facilitates their subsequent motor imagination. A higher level of physical activity as well as a longer time to perform mental task, seem to be associated with a greater increase in the ANS response.

SUBMITTER: Cuenca-Martinez F

PROVIDER: S-EPMC6037142 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Combining motor imagery with action observation training does not lead to a greater autonomic nervous system response than motor imagery alone during simple and functional movements: a randomized controlled trial.

Cuenca-Martínez Ferran F Suso-Martí Luis L Grande-Alonso Mónica M Paris-Alemany Alba A La Touche Roy R

PeerJ 20180706

Both motor imagery (MI) and action observation (AO) trigger the activation of the neurocognitive mechanisms that underlie the planning and execution of voluntary movements in a manner that resembles how the action is performed in a real way. The main objective of the present study was to compare the autonomic nervous system (ANS) response in an isolated MI group compared to a combined MI + AO group. The mental tasks were based on two simple movements that are recorded in the revised movement ima ...[more]

PMID: 30002975

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Project description:Motor imagery (MI) and action observation have proven to be efficacious adjuncts to traditional physiotherapy for enhancing motor recovery following stroke. Recently, researchers have used a combined approach called imagined imitation (II), where an individual watches a motor task being performed, while simultaneously imagining they are performing the movement. While neurofeedback (NFB) has been used extensively with MI to improve patients' ability to modulate sensorimotor activity and enhance motor recovery, the effectiveness of using NFB with II to modulate brain activity is unknown. This project tested the ability of participants to modulate sensorimotor activity during electroencephalography-based II-NFB of a complex, multi-part unilateral handshake, and whether this ability transferred to a subsequent bout of MI. Moreover, given the goal of translating findings from NFB research into practical applications, such as rehabilitation, the II-NFB system was designed with several user interface and user experience features, in an attempt to both drive user engagement and match the level of challenge to the abilities of the subjects. In particular, at easy difficulty levels the II-NFB system incentivized contralateral sensorimotor up-regulation (via event related desynchronization of the mu rhythm), while at higher difficulty levels the II-NFB system incentivized sensorimotor lateralization (i.e., both contralateral up-regulation and ipsilateral down-regulation). Thirty-two subjects, receiving real or sham NFB attended four sessions where they engaged in II-NFB training and subsequent MI. Results showed the NFB group demonstrated more bilateral sensorimotor activity during sessions 2-4 during II-NFB and subsequent MI, indicating mixed success for the implementation of this particular II-NFB system. Here we discuss our findings in the context of the design features included in the II-NFB system, highlighting limitations that should be considered in future designs.

Project description:Motor imagery (MI) has been widely used to operate brain-computer interface (BCI) systems for rehabilitation and some life assistive devices. However, the current performance of an MI-based BCI cannot fully meet the needs of its in-field applications. Most of the BCIs utilizing a generalized feature for all participants have been found to greatly hamper the efficacy of the BCI system. Hence, some attempts have made on the exploration of subject-dependent parameters, but it remains challenging to enhance BCI performance as expected. To this end, in this study, we used the independent component analysis (ICA), which has been proved capable of isolating the pure motor-related component from non-motor-related brain processes and artifacts and extracting the common motor-related component across MI, motor execution (ME), and motor observation (MO) conditions. Then, a sliding window approach was used to detect significant mu-suppression from the baseline using the electroencephalographic (EEG) alpha power time course and, thus, the success rate of the mu-suppression detection could be assessed on a single-trial basis. By comparing the success rates using different parameters, we further quantified the extent of the improvement in each motor condition to evaluate the effectiveness of both generalized and individualized parameters. The results showed that in ME condition, the success rate under individualized latency and that under generalized latency was 90.0% and 77.75%, respectively; in MI condition, the success rate was 74.14% for individual latency and 58.47% for generalized latency, and in MO condition, the success rate was 67.89% and 61.26% for individual and generalized latency, respectively. As can be seen, the success rate in each motor condition was significantly improved by utilizing an individualized latency compared to that using the generalized latency. Moreover, the comparison of the individualized window latencies for the mu-suppression detection across different runs of the same participant as well as across different participants showed that the window latency was significantly more consistent in the intra-subject than in the inter-subject settings. As a result, we proposed that individualizing the latency for detecting the mu-suppression feature for each participant might be a promising attempt to improve the MI-based BCI performance.

Project description:Female sex steroids (FSS) can affect the motor system, modulating motor cortex excitability as well as performance in dexterity and coordination tasks. However, it has not yet been explored whether FSS affects the cognitive components of motor behavior. Mu is a sensorimotor rhythm observed by electroencephalography (EEG) in alpha (8-12 Hz) and beta (15-30 Hz) frequency bands in practices such as motor imagery (MI) and action observation (AO). This rhythm represents a window for studying the activity of neural circuits involved in motor cognition. Herein we investigated whether the alpha-mu and beta-mu power in the sensorimotor region (C3 and C4, hypothesis-driven approach) and the alpha and beta power over frontal, parietal, and occipital regions (data-driven approach) are modulated differently in the menstrual, follicular, and luteal phases of menstrual cycles in right-handed dominant women. To do so, these women underwent MI and AO in the three menstrual cycle phases. The spectral activity of the cortical regions for the alpha and beta bands were compared between phases of the menstrual cycle and a correlation analysis was also performed in relation to estrogen and progesterone levels. For the hypothesis-based approach, beta-mu event-related desynchronization (ERD) was significantly stronger in the C3 channel in the follicular phase than in the menstrual and luteal phases. For the data-driven approach, beta ERD during MI was higher in the follicular phase than in the menstrual and luteal phases in the frontal region. These findings suggest the effect of FSS on executive movement control. No effect of menstrual cycle phases was observed in cortical areas investigated during OA, but alpha and beta bands correlated positively with the follicular phase plasma estradiol level. Thus, the attenuation of alpha and beta bands referring to mirror neuron activities appears to be associated with inhibition of cortical activity when estradiol levels are lower, improving cognitive processing of motor action.

Dataset Information

Combining motor imagery with action observation training does not lead to a greater autonomic nervous system response than motor imagery alone during simple and functional movements: a randomized controlled trial.

Publications

Combining motor imagery with action observation training does not lead to a greater autonomic nervous system response than motor imagery alone during simple and functional movements: a randomized controlled trial.

Similar Datasets

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