scholarly journals Success of Hand Movement Imagination Depends on Personality Traits, Brain Asymmetry, and Degree of Handedness

2021 ◽  
Vol 11 (7) ◽  
pp. 853
Author(s):  
Elena V. Bobrova ◽  
Varvara V. Reshetnikova ◽  
Elena A. Vershinina ◽  
Alexander A. Grishin ◽  
Pavel D. Bobrov ◽  
...  
Keyword(s):  
Personality Traits ◽  
Brain Activity ◽  
Hand Movement ◽  
Eeg Analysis ◽  
Hemispheric Differences ◽  
Left Hand ◽  
Left Handedness ◽  
Computer Interfaces ◽  
Brain States ◽  
Subjective Complexity

Brain-computer interfaces (BCIs), based on motor imagery, are increasingly used in neurorehabilitation. However, some people cannot control BCI, predictors of this are the features of brain activity and personality traits. It is not known whether the success of BCI control is related to interhemispheric asymmetry. The study was conducted on 44 BCI-naive subjects and included one BCI session, EEG-analysis, 16PF Cattell Questionnaire, estimation of latent left-handedness, and of subjective complexity of real and imagery movements. The success of brain states recognition during imagination of left hand (LH) movement compared to the rest is higher in reserved, practical, skeptical, and not very sociable individuals. Extraversion, liveliness, and dominance are significant for the imagination of right hand (RH) movements in “pure” right-handers, and sensitivity in latent left-handers. Subjective complexity of real LH and of imagery RH movements correlates with the success of brain states recognition in the imagination of movement of LH compared to RH and depends on the level of handedness. Thus, the level of handedness is the factor influencing the success of BCI control. The data are supposed to be connected with hemispheric differences in motor control, lateralization of dopamine, and may be important for rehabilitation of patients after a stroke.

scholarly journals EEG activity during balance platform test in humans

2019 ◽  
pp. 132-136 ◽  
Author(s):  
Vladimir Khorev ◽  
Artem Badarin ◽  
Vladimir Antipov ◽  
Vladimir Maksimenko ◽  
Semen Kurkin
Keyword(s):  
Cerebral Cortex ◽  
Human Brain ◽  
Brain Activity ◽  
Body Posture ◽  
Future Research ◽  
Eeg Activity ◽  
Common Features ◽  
Computer Interfaces ◽  
New Directions ◽  
Brain States

In order to analyze different human brain states related to perception and maintaining of body posture, we implemented an experiment with a balance platform. It is known the cerebral cortex regulates subcortical postural centers to maintain upright balance and posture and balance demands. However, the cortical mechanisms that support standing balance remain elusive. In this work, we present an EEG-based analysis during execution of balance responses with distinct postural demands. The results suggest the existence of common features in the EEG structure associated with distinct activity during balance maintaining. This may give new directions for future research in the field of brain activity, and for the development of brain-computer interfaces.

Brain-Computer Interfaces and Visual Activity

2013 ◽  
pp. 1549-1570
Author(s):  
Carmen Vidaurre ◽  
Andrea Kübler ◽  
Michael Tangermann ◽  
Klaus-Robert Müller ◽  
José del R. Millán
Keyword(s):  
Video Game ◽  
Brain Activity ◽  
Visual Stimuli ◽  
Robot Arm ◽  
Virtual Keyboard ◽  
Computer Interfaces ◽  
Brain Signals ◽  
Brain States ◽  
Physically Disabled People ◽  
The Brain

There is growing interest in the use of brain signals for communication and operation of devices, in particular, for physically disabled people. Brain states can be detected and translated into actions such as selecting a letter from a virtual keyboard, playing a video game, or moving a robot arm. This chapter presents what is known about the effects of visual stimuli on brain activity and introduces means of monitoring brain activity. Possibilities of brain-controlled interfaces, either with the brain signals as the sole input or in combination with the measured point of gaze, are discussed.

scholarly journals Artifacts in EEG-based BCI therapies: friend or foe?

2021 ◽  
Author(s):  
Eric James McDermott ◽  
Philipp Raggam ◽  
Sven Kirsch ◽  
Paolo Belardinelli ◽  
Ulf Ziemann ◽  
...  
Keyword(s):  
Therapeutic Potential ◽  
Brain Activity ◽  
Mental States ◽  
Extraction Methods ◽  
Brain State ◽  
Eeg Signal ◽  
Motor Tasks ◽  
Computer Interfaces ◽  
Eeg Data ◽  
Brain States

EEG-based brain-computer interfaces (BCI) have promising therapeutic potential beyond traditional neurofeedback training, such as enabling personalized and optimized virtual reality (VR) neurorehabilitation paradigms where the timing and parameters of the visual experience is synchronized with specific brain-states. While BCI algorithms are often designed to focus on whichever portion of a signal is most informative, in these brain-state-synchronized applications, it is of critical importance that the resulting decoder is sensitive to physiological brain activity representative of various mental states, and not to artifacts such as those arising from naturalistic movements. In this study, we compare the relative classification accuracy with which different motor tasks can be decoded from both extracted brain activity and artifacts contained in the EEG signal. EEG data was collected from 17 chronic stroke patients while performing six different head, hand, and arm movements in a realistic VR-based neurorehabilitation paradigm. Results show that the artifact component of the EEG signal is significantly more informative than brain activity to the classifier. This finding is consistent across different feature extraction methods and classification pipelines. Whereas informative artifacts are a helpful friend in BCI-based communication applications, they can be a problematic foe in the estimation of physiological brain states.

Propagation of EEG Activity in the Beta and Gamma Band during Movement Imagery in Humans

2005 ◽  
Vol 44 (01) ◽  
pp. 106-113 ◽  
Author(s):  
J. Ginter ◽  
M. Kamiński ◽  
P. J. Durka ◽  
G. Pfurtscheller ◽  
C. Neuper ◽  
...  
Keyword(s):  
Brain Activity ◽  
Hand Movement ◽  
Specific Information ◽  
Beta Band ◽  
Directed Transfer Function ◽  
Left Hand ◽  
Electrical Brain Activity ◽  
Movement Imagery ◽  
Short Time

Summary Objectives: The objective of the paper was the determination of electrical brain activity propagation in sensorimotor areas during hand movement imagery. Methods: Right-hand and left-hand movement imagination was studied in three subjects. The 10-channel Multivariate Autoregressive Model (MVAR) was fitted to EEG signals recorded from subsets of electrodes overlying central and related brain areas. By means of the Short-time Directed Transfer Function (SDTF) the propagation of brain activity as a function of frequency and time was found. Results: During imagery the relation between propagations in gamma and beta bands changed significantly for electrodes overlying sensorimotor areas, namely the increase in gamma was accompanied by the decrease in the beta band. Conclusions: The hypothesis was put forward that these kinds of changes in flow of electrical brain activity are connected with the specific information processing.

Brain-Computer Interfaces and Visual Activity

2012 ◽  
pp. 153-174
Author(s):  
Carmen Vidaurre ◽  
Andrea Kübler ◽  
Michael Tangermann ◽  
Klaus-Robert Müller ◽  
José del R. Millán
Keyword(s):  
Video Game ◽  
Brain Activity ◽  
Visual Stimuli ◽  
Robot Arm ◽  
Virtual Keyboard ◽  
Computer Interfaces ◽  
Brain Signals ◽  
Brain States ◽  
Physically Disabled People ◽  
The Brain

There is growing interest in the use of brain signals for communication and operation of devices – in particular, for physically disabled people. Brain states can be detected and translated into actions such as selecting a letter from a virtual keyboard, playing a video game, or moving a robot arm. This chapter presents what is known about the effects of visual stimuli on brain activity and introduces means of monitoring brain activity. Possibilities of brain-controlled interfaces, either with the brain signals as the sole input or in combination with the measured point of gaze, are discussed.

Shall I Move My Right or My Left Hand?

2003 ◽  
Vol 17 (2) ◽  
pp. 69-86 ◽  
Author(s):  
Claudio Babiloni ◽  
Fabio Babiloni ◽  
Filippo Carducci ◽  
Febo Cincotti ◽  
Claudio Del Percio ◽  
...  
Keyword(s):  
Bimanual Coordination ◽  
Central Area ◽  
Eeg Analysis ◽  
Complementary Information ◽  
Left Hand ◽  
Mirror Movements ◽  
Related Potentials ◽  
Motor Acts ◽  
Abstract Event

Abstract Event-related desynchronization/synchronization (ERD/ERS) at alpha (10Hz), beta (20Hz), and gamma (40Hz) bands and movement-related potentials (MRPs) were investigated in right-handed subjects who were “free” to decide the side of unilateral finger movements (“fixed” side as a control). As a novelty, this “multi-modal” EEG analysis was combined with the evaluation of involuntary mirror movements, taken as an index of “bimanual competition.” A main issue was whether the decision regarding the hand to be moved (“free” movements) could modulate ERD/ERS or MRPs overlying sensorimotor cortical areas typically involved in bimanual tasks. Compared to “fixed” movements, “free” movements induced the following effects: (1) more involuntary mirror movements discarded from EEG analysis; (2) stronger vertex MRPs (right motor acts); (3) a positive correlation between these potentials and the number of involuntary mirror movements; (4) gamma ERS over central areas; and (5) preponderance of postmovement beta ERS over left central area (dominant hemisphere). These results suggest that ERD/ERS and MRPs provide complementary information on the cortical processes belonging to a lateralized motor act. In this context, the results on vertex MRPs would indicate a key role of supplementary/cingulate motor areas not only for bimanual coordination but also for the control of “bimanual competition” and involuntary mirror movements.

Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

2018 ◽  
pp. 115-122 ◽  
Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann
Keyword(s):  
Epileptic Seizure ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Automated System ◽  
Brain Computer Interfaces ◽  
Electrical Brain Activity ◽  
Computer Interfaces ◽  
Prediction And Prevention ◽  
The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 

scholarly journals Anytime collaborative brain–computer interfaces for enhancing perceptual group decision-making

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Saugat Bhattacharyya ◽  
Davide Valeriani ◽  
Caterina Cinel ◽  
Luca Citi ◽  
Riccardo Poli
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Brain Activity ◽  
Event Related Potentials ◽  
Brain Computer Interfaces ◽  
Appearance Time ◽  
Perceptual Group ◽  
Computer Interfaces ◽  
Related Potentials

AbstractIn this paper we present, and test in two realistic environments, collaborative Brain-Computer Interfaces (cBCIs) that can significantly increase both the speed and the accuracy of perceptual group decision-making. The key distinguishing features of this work are: (1) our cBCIs combine behavioural, physiological and neural data in such a way as to be able to provide a group decision at any time after the quickest team member casts their vote, but the quality of a cBCI-assisted decision improves monotonically the longer the group decision can wait; (2) we apply our cBCIs to two realistic scenarios of military relevance (patrolling a dark corridor and manning an outpost at night where users need to identify any unidentified characters that appear) in which decisions are based on information conveyed through video feeds; and (3) our cBCIs exploit Event-Related Potentials (ERPs) elicited in brain activity by the appearance of potential threats but, uniquely, the appearance time is estimated automatically by the system (rather than being unrealistically provided to it). As a result of these elements, in the two test environments, groups assisted by our cBCIs make both more accurate and faster decisions than when individual decisions are integrated in more traditional manners.

scholarly journals Daytime micro-naps in a nocturnal migrant: an EEG analysis

2008 ◽  
Vol 5 (1) ◽  
pp. 77-80 ◽  
Author(s):  
T Fuchs ◽  
D Maury ◽  
F.R Moore ◽  
V.P Bingman
Keyword(s):  
Brain Activity ◽  
Sleep Loss ◽  
Eeg Analysis ◽  
Observable Effect ◽  
Brain Response ◽  
Night Time ◽  
Avian Migration ◽  
Unihemispheric Sleep ◽  
Daytime Behaviour ◽  
Behavioural Evidence

Many species of typically diurnal songbirds experience sleep loss during the migratory seasons owing to their nocturnal migrations. However, despite substantial loss of sleep, nocturnally migrating songbirds continue to function normally with no observable effect on their behaviour. It is unclear if and how avian migrants compensate for sleep loss. Recent behavioural evidence suggests that some species may compensate for lost night-time sleep with short, uni- and bilateral ‘micro-naps’ during the day. We provide electrophysiological evidence that short episodes of sleep-like daytime behaviour (approx. 12 s) are accompanied by sleep-like changes in brain activity in an avian migrant. Furthermore, we present evidence that part of this physiological brain response manifests itself as unihemispheric sleep, a state during which one brain hemisphere is asleep while the other hemisphere remains essentially awake. Episodes of daytime sleep may represent a potent adaptation to the challenges of avian migration and offer a plausible explanation for the resilience to sleep loss in nocturnal migrants.

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