Does Motor Imagery Task Alter H-Reflex in FCR Muscle of The Human Hand?

2018 ◽  
Author(s):  
Seyyedeh Ensiyeh Hashemi ◽  
Mohammad Ali Ahmadi-Pajouh ◽  
Elham Shamsi
Keyword(s):  
Motor Imagery ◽  
H Reflex ◽  
Human Hand ◽  
Imagery Task

Experience Influences Brain Mechanisms of Watching Dance

2011 ◽  
Vol 29 (supplement) ◽  
pp. 352-377 ◽  
Author(s):  
Seon Hee Jang ◽  
Frank E Pollick
Keyword(s):  
Motor Imagery ◽  
Visual Experience ◽  
Primary Motor Cortex ◽  
Action Observation ◽  
Brain Area ◽  
Retrosplenial Cortex ◽  
Imagery Task ◽  
Temporoparietal Junction ◽  
Action Observation Network ◽  
Viewing Experience

The study of dance has been helpful to advance our understanding of how human brain networks of action observation are influenced by experience. However previous studies have not examined the effect of extensive visual experience alone: for example, an art critic or dance fan who has a rich experience of watching dance but negligible experience performing dance. To explore the effect of pure visual experience we performed a single experiment using functional Magnetic Resonance Imaging (fMRI) to compare the neural processing of dance actions in 3 groups: a) 14 ballet dancers, b) 10 experienced viewers, c) 12 novices without any extensive dance or viewing experience. Each of the 36 participants viewed short 2-second displays of ballet derived from motion capture of a professional ballerina. These displays represented the ballerina as only points of light at the major joints. We wished to study the action observation network broadly and thus included two different types of display and two different tasks for participants to perform. The two different displays were: a) brief movies of a ballet action and b) frames from the ballet movies with the points of lights connected by lines to show a ballet posture. The two different tasks were: a) passively observe the display and b) imagine performing the action depicted in the display. The two levels of display and task were combined factorially to produce four experimental conditions (observe movie, observe posture, motor imagery of movie, motor imagery of posture). The set of stimuli used in the experiment are available for download after this paper. A random effects ANOVA was performed on brain activity and an effect of experience was obtained in seven different brain areas including: right Temporoparietal Junction (TPJ), left Retrosplenial Cortex (RSC), right Primary Somatosensory Cortex (S1), bilateral Primary Motor Cortex (M1), right Orbitofrontal Cortex (OFC), right Temporal Pole (TP). The patterns of activation were plotted in each of these areas (TPJ, RSC, S1, M1, OFC, TP) to investigate more closely how the effect of experience changed across these areas. For this analysis, novices were treated as baseline and the relative effect of experience examined in the dancer and experienced viewer groups. Interpretation of these results suggests that both visual and motor experience appear equivalent in producing more extensive early processing of dance actions in early stages of representation (TPJ and RSC) and we hypothesise that this could be due to the involvement of autobiographical memory processes. The pattern of results found for dancers in S1 and M1 suggest that their perception of dance actions are enhanced by embodied processes. For example, the S1 results are consistent with claims that this brain area shows mirror properties. The pattern of results found for the experienced viewers in OFC and TP suggests that their perception of dance actions are enhanced by cognitive processes. For example, involving aspects of social cognition and hedonic processing – the experienced viewers find the motor imagery task more pleasant and have richer connections of dance to social memory. While aspects of our interpretation are speculative the core results clearly show common and distinct aspects of how viewing experience and physical experience shape brain responses to watching dance.

EEG based Graph Network Analysis for Motor Imagery Task

2021 ◽  
Author(s):  
Wenwen Chang ◽  
Wenqie Huang ◽  
Guanghui Yan ◽  
Yuchan Zhang
Keyword(s):  
Network Analysis ◽  
Motor Imagery ◽  
Imagery Task

Classification of EEG Signals for Motor Imagery Based on Mutual Information and Adaptive Neuro Fuzzy Inference System

Fuzzy Systems ◽  
2017 ◽  
pp. 347-366
Author(s):  
Shereen A. El-aal ◽  
Rabie A. Ramadan ◽  
Neveen Ghali
Keyword(s):  
Mutual Information ◽  
Motor Imagery ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Imagery Task ◽  
Eeg Signals ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Anfis Classifier ◽  
Maximal Relevance

Electroencephalogram (EEG) signals based Brain Computer Interface (BCI) is employed to help disabled people to interact better with the environment. EEG signals are recorded through BCI system to translate it to control commands. There are a large body of literature targeting EEG feature extraction and classification for Motor Imagery tasks. Motor imagery task have several features can be extracted to use in classification. However, using more features consume running time and using irrelevant and redundant features affect the performance of the used classifier. This paper is dedicated to extracting the best feature vector for motor imagery task. This work suggests two feature selection methods based on Mutual Information (MI) including Minimum Redundancy Maximal Relevance (MRMR) and maximal Relevance (MaxRel). Adaptive Neuro Fuzzy Inference System (ANFIS) classifier with Subtractive clustering method is utilized for EEG signals classifications. The suggested methods are applied to BCI Competition III dataset IVa and IVb and BCI Competition II dataset III.

Classification of EEG Signals for Motor Imagery based on Mutual Information and Adaptive Neuro Fuzzy Inference System

2016 ◽  
Vol 5 (4) ◽  
pp. 64-82 ◽  
Author(s):  
Shereen A. El-aal ◽  
Rabie A. Ramadan ◽  
Neveen I. Ghali
Keyword(s):  
Mutual Information ◽  
Motor Imagery ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Subtractive Clustering ◽  
Imagery Task ◽  
Eeg Signals ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Maximal Relevance

Electroencephalogram (EEG) signals based Brain Computer Interface (BCI) is employed to help disabled people to interact better with the environment. EEG signals are recorded through BCI system to translate it to control commands. There are a large body of literature targeting EEG feature extraction and classification for Motor Imagery tasks. Motor imagery task have several features can be extracted to use in classification. However, using more features consume running time and using irrelevant and redundant features affect the performance of the used classifier. This paper is dedicated to extracting the best feature vector for motor imagery task. This work suggests two feature selection methods based on Mutual Information (MI) including Minimum Redundancy Maximal Relevance (MRMR) and maximal Relevance (MaxRel). Adaptive Neuro Fuzzy Inference System (ANFIS) classifier with Subtractive clustering method is utilized for EEG signals classifications. The suggested methods are applied to BCI Competition III dataset IVa and IVb and BCI Competition II dataset III.

Classification of Motor Imagery Task by Using Novel Ensemble Pruning Approach

2020 ◽  
Vol 28 (1) ◽  
pp. 85-91 ◽  
Author(s):  
Muhammad Ammar Ali ◽  
Duygu Ucuncu ◽  
Pinar Karadayi Atas ◽  
Sureyya Ozogur-Akyuz
Keyword(s):  
Motor Imagery ◽  
Imagery Task ◽  
Ensemble Pruning

scholarly journals Hypnosis-induced modulation of corticospinal excitability during motor imagery

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Paola Cesari ◽  
Michele Modenese ◽  
Sara Benedetti ◽  
Mehran Emadi Andani ◽  
Mirta Fiorio
Keyword(s):  
Individual Differences ◽  
Motor Imagery ◽  
Primary Motor Cortex ◽  
Ad Hoc ◽  
Imagery Task ◽  
Hypnotic Susceptibility ◽  
Motor Abilities ◽  
Neurophysiological Mechanisms ◽  
Altered State Of Consciousness ◽  
System Activation

Abstract Hypnosis can be considered an altered state of consciousness in which individuals produce movements under suggestion without apparent voluntary control. Despite its application in contexts implying motor control, evidence for the neurophysiological mechanisms underlying hypnosis is scarce. Inter-individual differences in hypnotic susceptibility suggest that sensorimotor strategies may manifest in a hypnotic state. We tested by means of transcranial magnetic stimulation applied over the primary motor cortex whether motor system activation during a motor imagery task differs in the awake and in the hypnotic state. To capture individual differences, 30 healthy volunteers were classified as high or low hypnotizable (Highs and Lows) according to ad-hoc validated scales measuring hypnotic susceptibility and personality questionnaires. Corticospinal activation during motor imagery in the hypnotic state was greater in the Highs than the Lows. Intrinsic motivation in task performance and level of persuasion modulated corticospinal activation in the Highs. Corticospinal system activation under hypnosis may have practical implications that merit research in areas where hypnosis can be applied to improve motor performance, such as loss of motor abilities and sports.

scholarly journals Jaya Based ANFIS for Monitoring of Two Class Motor Imagery Task

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 9273-9282 ◽  
Author(s):  
Suraj ◽  
Rakesh Kumar Sinha ◽  
Subhojit Ghosh
Keyword(s):  
Motor Imagery ◽  
Imagery Task
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