scholarly journals Handedness effects on motor imagery during kinesthetic and visual-motor conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dariusz Zapała ◽  
Paulina Iwanowicz ◽  
Piotr Francuz ◽  
Paweł Augustynowicz

AbstractRecent studies show that during a simple movement imagery task, the power of sensorimotor rhythms differs according to handedness. However, the effects of motor imagery perspectives on these differences have not been investigated yet. Our study aimed to check how handedness impacts the activity of alpha (8–13 Hz) and beta (15–30 Hz) oscillations during creating a kinesthetic (KMI) or visual-motor (VMI) representation of movement. Forty subjects (20 right-handed and 20 left-handed) who participated in the experiment were tasked with imagining sequential finger movement from a visual or kinesthetic perspective. Both the electroencephalographic (EEG) activity and behavioral correctness of the imagery task performance were measured. After the registration, we used independent component analysis (ICA) on EEG data to localize visual- and motor-related EEG sources of activity shared by both motor imagery conditions. Significant differences were obtained in the visual cortex (the occipital ICs cluster) and the right motor-related area (right parietal ICs cluster). In comparison to right-handers who, regardless of the task, demonstrated the same pattern in the visual area, left-handers obtained higher power in the alpha waves in the VMI task and better performance in this condition. On the other hand, only the right-handed showed different patterns in the alpha waves in the right motor cortex during the KMI condition. The results indicate that left-handers imagine movement differently than right-handers, focusing on visual experience. This provides new empirical evidence on the influence of movement preferences on imagery processes and has possible future implications for research in the area of neurorehabilitation and motor imagery-based brain–computer interfaces (MI-BCIs).

2020 ◽  
Author(s):  
Dariusz Zapała ◽  
Paulina Iwanowicz ◽  
Piotr Francuz ◽  
Paweł Augustynowicz

Abstract Recent studies show that during a simple movement imagery task, the power of sensorimotor rhythms differs according to handedness. However, the effects of motor imagery perspectives on these differences have not been investigated yet. Our study aimed to check how handedness impacts the activity of alpha (8 - 13 Hz) and beta (15 - 30 Hz) oscillations during creating a kinesthetic (KMI) or visual-motor (VMI) representation of movement. Forty subjects (20 right-handed and 20 left-handed) who participated in the experiment were tasked with imagining sequential finger movement from a visual or kinesthetic perspective. Both the electroencephalographic (EEG) activity and behavioral correctness of the imagery task performance were measured. After the registration, we used independent component analysis (ICA) on EEG data to localize visual- and motor-related EEG sources of activity shared by both motor imagery conditions. Significant differences were obtained in the visual cortex (the occipital ICs cluster) and the right motor-related area (right parietal ICs cluster). In comparison to right-handers who, regardless of the task, demonstrated the same pattern in the visual area, left-handers obtained higher power in the alpha waves in the VMI task and better performance in this condition. On the other hand, only the right-handed showed different patterns in the alpha waves in the right motor cortex during the KMI condition.The results indicate that left-handers imagine movement differently than right-handers, focusing on visual experience. This provides new empirical evidence on the influence of movement preferences on imagery processes and has possible future implications for research in the area of neurorehabilitation and motor imagery-based brain-computer interfaces (MI-BCIs).


2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Simone Rossi ◽  
Danilo Spada ◽  
Marco Emanuele ◽  
Monica Ulivelli ◽  
Emiliano Santarnecchi ◽  
...  

Transcranial magnetic stimulation was used to investigate corticospinal output changes in 10 professional piano players during motor imagery of triad chords in C major to be “mentally” performed with three fingers of the right hand (thumb, index, and little finger). Five triads were employed in the task; each composed by a stable 3rd interval (C4-E4) and a varying third note that could generate a 5th (G4), a 6th (A4), a 7th (B4), a 9th (D5), or a 10th (E5) interval. The 10th interval chord was thought to be impossible in actual execution for biomechanical reasons, as long as the thumb and the index finger remained fixed on the 3rd interval. Chords could be listened from loudspeakers, read on a staff, or listened and read at the same time while performing the imagery task. The corticospinal output progressively increased along with task demands in terms of mental representation of hand extension. The effects of audio, visual, or audiovisual musical stimuli were generally similar, unless motor imagery of kinetically impossible triads was required. A specific three-effector motor synergy was detected, governing the representation of the progressive mental extension of the hand. Results demonstrate that corticospinal facilitation in professional piano players can be modulated according to the motor plan, even if simply “dispatched” without actual execution. Moreover, specific muscle synergies, usually encoded in the motor cortex, emerge along the cross-modal elaboration of musical stimuli and in motor imagery of musical performances.


2021 ◽  
Vol 12 (1) ◽  
pp. 482-493
Author(s):  
Zhouzhou Zhou ◽  
Anmin Gong ◽  
Qian Qian ◽  
Lei Su ◽  
Lei Zhao ◽  
...  

Abstract A brain–computer interface (BCI) based on kinesthetic motor imagery has a potential of becoming a groundbreaking technology in a clinical setting. However, few studies focus on a visual-motor imagery (VMI) paradigm driving BCI. The VMI-BCI feature extraction methods are yet to be explored in depth. In this study, a novel VMI-BCI paradigm is proposed to execute four VMI tasks: imagining a car moving forward, reversing, turning left, and turning right. These mental strategies can naturally control a car or robot to move forward, backward, left, and right. Electroencephalogram (EEG) data from 25 subjects were collected. After the raw EEG signal baseline was corrected, the alpha band was extracted using bandpass filtering. The artifacts were removed by independent component analysis. Then, the EEG average instantaneous energy induced by VMI (VMI-EEG) was calculated using the Hilbert–Huang transform (HHT). The autoregressive model was extracted to construct a 12-dimensional feature vector to a support vector machine suitable for small sample classification. This was classified into two-class tasks: visual imagination of driving the car forward versus reversing, driving forward versus turning left, driving forward versus turning right, reversing versus turning left, reversing versus turning right, and turning left versus turning right. The results showed that the average classification accuracy of these two-class tasks was 62.68 ± 5.08%, and the highest classification accuracy was 73.66 ± 6.80%. The study showed that EEG features of O1 and O2 electrodes in the occipital region extracted by HHT were separable for these VMI tasks.


2021 ◽  
Vol 15 ◽  
Author(s):  
Lea Hehenberger ◽  
Luka Batistic ◽  
Andreea I. Sburlea ◽  
Gernot R. Müller-Putz

Motor imagery is a popular technique employed as a motor rehabilitation tool, or to control assistive devices to substitute lost motor function. In both said areas of application, artificial somatosensory input helps to mirror the sensorimotor loop by providing kinesthetic feedback or guidance in a more intuitive fashion than via visual input. In this work, we study directional and movement-related information in electroencephalographic signals acquired during a visually guided center-out motor imagery task in two conditions, i.e., with and without additional somatosensory input in the form of vibrotactile guidance. Imagined movements to the right and forward could be discriminated in low-frequency electroencephalographic amplitudes with group level peak accuracies of 70% with vibrotactile guidance, and 67% without vibrotactile guidance. The peak accuracies with and without vibrotactile guidance were not significantly different. Furthermore, the motor imagery could be classified against a resting baseline with group level accuracies between 76 and 83%, using either low-frequency amplitude features or μ and β power spectral features. On average, accuracies were higher with vibrotactile guidance, while this difference was only significant in the latter set of features. Our findings suggest that directional information in low-frequency electroencephalographic amplitudes is retained in the presence of vibrotactile guidance. Moreover, they hint at an enhancing effect on motor-related μ and β spectral features when vibrotactile guidance is provided.


1974 ◽  
Vol 39 (3) ◽  
pp. 1275-1281 ◽  
Author(s):  
R. Nakamura ◽  
H. Saito

The difference in RT for right and left biceps, acting on the forearm in two different movement patterns, flexion and supination, was examined for 14 normal Ss, seven right-handed and seven left-handed. The task was to flex or supinate both forearms simultaneously in response to a sound stimulus. Median RTs of each S were computed for each movement task. The analysis indicated that RT of supination is faster than that of flexion. Concerning left-right difference of RT, the flexion of the non-preferred hand is faster than that of the preferred hand and the supination of the preferred hand is faster than that of the non-preferred hand. Even in a simple movement there are differences in RTs for the right and left hands which do not depend on the muscles but on the movement patterns. Hemispheric dominance is not established by comparing the rapid initiation of movement.


2020 ◽  
Vol 32 (02) ◽  
pp. 2050015
Author(s):  
Gauri Shanker Gupta ◽  
Dusmanta Kumar Mohanta ◽  
Subhojit Ghosh ◽  
Gunjan Bhavnesh Dave ◽  
Maanvi Bhatnagar ◽  
...  

The paper proposes a novel methodology of de-noising raw electroencephalogram (EEG) data from ocular artifacts (OAs) and alpha waves extraction from motor imagery-based signals that could be further utilized for brain–computer interface (BCI)-based applications. An algorithm based on discrete wavelet transform (DWT) and nonlinear adaptive filtering for the removal of OA is advocated, with an aim of making the process computationally intelligent. This algorithm has been tested on pre-recorded EEG dataset for BCI (Dataset IIIa; obtained from the website of the BCI Competition III). To further validate the competence of the proposed method, synthetic EEG signals were created, which were fused with white Gaussian noise. A total of 20 EEG signals were generated, half of which had added noise with a signal-to-noise ratio (SNR) of 10[Formula: see text]dB and other half had added noise of 5 dBSNR. Each signal contained 1000 samples with a sampling frequency of 250[Formula: see text]Hz. An optimum bandpass filter (FIR and IIR) for extraction of alpha waves has been suggested. FIR Equiripple filter is found most appropriate for the task as it has highest SNR and computes the response faster when compared with other filters. Among different mother wavelets, Daubechies 4 wavelet obtained using statistical thresholding denoises the EEG data most successfully. Correlation and root mean square error (RMSE) parameters show that the performance of nonlinear adaptive filter developed using nonlinear Volterra series has an edge over conventional adaptive filters for the intended purpose.


2016 ◽  
Vol 1 (1) ◽  
pp. 46-51
Author(s):  
VF F Pyatin ◽  
AV V Kolsanov ◽  
MS S Segreeva ◽  
ES S Korovina ◽  
AV V Zakharov

Aim - the determination of common and individual characteristics in patterns of sensorimotor rhythms of EEG during motor imagery in upper and lower limbs. Materials and methods. 20 right-handed students of Samara State Medical University at the age of 18-20 years took part in the investigation, signing informed consent. Monopolar EEG was recorded with the use of 128-channel EEG recording system (BP-010302 BrainАmpStandart 128) at rest and during the imagining of monovector movements in 4 limbs (bending fingers of the right hand, bending fingers of the left hand, dorsiflexion of the right foot, dorsiflexion of the left foot); and during the imagining of triple-vector movements in the dominant hand (fingers bending, elbow flexion, wrist rotation). The following programs and methods were used during the processing of EEG: MatLab, IBM SPSS Statistics 22, ICA (independent component analysis), CSP (Common Spatial Pattern), LORETA. Results. It was found out that alpha2- and beta2- EEG frequency bands are highly significant for the formation of contralateral activation focus during motor imagery in the 4 limbs. ERD / ERS of the EEG rhythms were more pronounced during imagining movements in the dominant limbs (right hand, right leg) than in non-dominant.We found individuality of responses of sensorimotor EEG rhythms in addition to the general trends of EEG changes during imagination of one-type movement in the 4 limbs. The significance of changes in the power of EEG sensorimotor rhythms for differentiating 3 degrees of freedom during motor imagery in one limb was not found. Conclusion. Event-related desynchronization/synchro-nization(ERD/ERS) of sensorimotor EEG rhythms related to motor imagery has individual characteristics and their classification will lead to the significant increase of the number of degrees of freedom in creation and implementation of BCI.


2021 ◽  
Vol 15 ◽  
Author(s):  
Keisuke Irie ◽  
Amiri Matsumoto ◽  
Shuo Zhao ◽  
Toshihiro Kato ◽  
Nan Liang

Although the neural bases of the brain associated with movement disorders in children with developmental coordination disorder (DCD) are becoming clearer, the information is not sufficient because of the lack of extensive brain function research. Therefore, it is controversial about effective intervention methods focusing on brain function. One of the rehabilitation techniques for movement disorders involves intervention using motor imagery (MI). MI is often used for movement disorders, but most studies involve adults and healthy children, and the MI method for children with DCD has not been studied in detail. Therefore, a review was conducted to clarify the neuroscientific basis of the methodology of intervention using MI for children with DCD. The neuroimaging review included 20 magnetic resonance imaging studies, and the neurorehabilitation review included four MI intervention studies. In addition to previously reported neural bases, our results indicate decreased activity of the bilateral thalamus, decreased connectivity of the sensory-motor cortex and the left posterior middle temporal gyrus, bilateral posterior cingulate cortex, precuneus, cerebellum, and basal ganglia, loss of connectivity superiority in the abovementioned areas. Furthermore, reduction of gray matter volume in the right superior frontal gyrus and middle frontal gyrus, lower fractional anisotropy, and axial diffusivity in regions of white matter pathways were found in DCD. As a result of the review, children with DCD had less activation of the left brain, especially those with mirror neurons system (MNS) and sensory integration functions. On the contrary, the area important for the visual space processing of the right brain was activated. Regarding of characteristic of the MI methods was that children observed a video related to motor skills before the intervention. Also, they performed visual-motor tasks before MI training sessions. Adding action observation during MI activates the MNS, and performing visual-motor tasks activates the basal ganglia. These methods may improve the deactivated brain regions of children with DCD and may be useful as conditioning before starting training. Furthermore, we propose a process for sharing the contents of MI with the therapist in language and determining exercise strategies.


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