Electroencephalogram Theta-Beta Band Power Features Generated from Writing for the Classification of Dyslexic Chidren

2018 ◽  
Author(s):  
Z. Mahmoodin ◽  
W. Mansor ◽  
Khuan Y. Lee ◽  
A. Z. A Zainuddin
Keyword(s):  
Beta Band ◽  
Band Power

scholarly journals Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2461
Author(s):  
Alexander Kuc ◽  
Vadim V. Grubov ◽  
Vladimir A. Maksimenko ◽  
Natalia Shusharina ◽  
Alexander N. Pisarchik ◽  
...  
Keyword(s):  
Decision Making ◽  
Sensory Information ◽  
Stimulus Onset ◽  
Perceptual Process ◽  
Perceptual Decision Making ◽  
Beta Band ◽  
Perceptual Decision ◽  
Time Frequency ◽  
Band Power ◽  
Sensory Features

Perceptual decision-making requires transforming sensory information into decisions. An ambiguity of sensory input affects perceptual decisions inducing specific time-frequency patterns on EEG (electroencephalogram) signals. This paper uses a wavelet-based method to analyze how ambiguity affects EEG features during a perceptual decision-making task. We observe that parietal and temporal beta-band wavelet power monotonically increases throughout the perceptual process. Ambiguity induces high frontal beta-band power at 0.3–0.6 s post-stimulus onset. It may reflect the increasing reliance on the top-down mechanisms to facilitate accumulating decision-relevant sensory features. Finally, this study analyzes the perceptual process using mixed within-trial and within-subject design. First, we found significant percept-related changes in each subject and then test their significance at the group level. Thus, observed beta-band biomarkers are pronounced in single EEG trials and may serve as control commands for brain-computer interface (BCI).

AUDITORY VERBAL HALLUCINATIONS ARE RELATED TO DECREASED BETA-BAND POWER IN THE ANTERIOR SUPERIOR FRONTAL GYRUS – AN MEG STUDY

2010 ◽  
Vol 117 (2-3) ◽  
pp. 475
Author(s):  
Remko Van Lutterveld ◽  
Arjan Hillebrand ◽  
Cornelis J. Stam ◽  
René S. Kahn ◽  
Iris E. Sommer
Keyword(s):  
Beta Band ◽  
Superior Frontal Gyrus ◽  
Auditory Verbal Hallucinations ◽  
Band Power

Wavelet Transform Based Feature Extraction for EEG Signal Classification

2021 ◽  
Vol 20 ◽  
pp. 199-206
Author(s):  
Seda Postalcioglu
Keyword(s):  
Wavelet Transform ◽  
High Performance ◽  
Feature Vector ◽  
Fast Response ◽  
Eeg Signal ◽  
Real Time Control ◽  
Time Control ◽  
Band Power ◽  
Performance Rate

This study focused on the classification of EEG signal. The study aims to make a classification with fast response and high-performance rate. Thus, it could be possible for real-time control applications as Brain-Computer Interface (BCI) systems. The feature vector is created by Wavelet transform and statistical calculations. It is trained and tested with a neural network. The db4 wavelet is used in the study. Pwelch, skewness, kurtosis, band power, median, standard deviation, min, max, energy, entropy are used to make the wavelet coefficients meaningful. The performance is achieved as 99.414% with the running time of 0.0209 seconds

scholarly journals Beta-band desynchronization reflects uncertainty in effector selection during motor planning

2021 ◽  
Author(s):  
Milou J.L. van Helvert ◽  
Leonie Oostwoud Wijdenes ◽  
Linda Geerligs ◽  
W. Pieter Medendorp
Keyword(s):  
Time Window ◽  
Brain Activity ◽  
Motor Planning ◽  
Reaction Times ◽  
Motor Preparation ◽  
Motion Artifact ◽  
Theta Band ◽  
Beta Band ◽  
Target Uncertainty ◽  
Band Power

AbstractWhile beta-band activity during motor planning is known to be modulated by uncertainty about where to act, less is known about its modulations to uncertainty about how to act. To investigate this issue, we recorded oscillatory brain activity with EEG while human participants (n = 17) performed a hand choice reaching task. The reaching hand was either predetermined or of participants’ choice, and the target was close to one of the two hands or at about equal distance from both. To measure neural activity in a motion-artifact-free time window, the location of the upcoming target was cued 1000-1500 ms before the presentation of the target, whereby the cue was valid in 50% of trials. As evidence for motor planning during the cueing phase, behavioral observations showed that the cue affected later hand choice. Furthermore, reaction times were longer in the choice than in the predetermined trials, supporting the notion of a competitive process for hand selection. Modulations of beta-band power over central cortical regions, but not alpha-band or theta-band power, were in line with these observations. During the cueing period, reaches in predetermined trials were preceded by larger decreases in beta-band power than reaches in choice trials. Cue direction did not affect reaction times or beta-band power, which may be due to the cue being invalid in 50% of trials, retaining effector uncertainty during motor planning. Our findings suggest that effector uncertainty, similar to target uncertainty, selectively modulates beta-band power during motor planning.New & NoteworthyWhile reach-related beta-band power in central cortical areas is known to modulate with the number of potential targets, here we show, using a cueing paradigm, that the power in this frequency band, but not in the alpha or theta-band, is also modulated by the uncertainty of which hand to use. This finding supports the notion that multiple possible effector-specific actions can be specified in parallel up to the level of motor preparation.

scholarly journals Frequency-based Segregation of Syntactic and Semantic Unification during Online Sentence Level Language Comprehension

2015 ◽  
Vol 27 (11) ◽  
pp. 2095-2107 ◽  
Author(s):  
Marcel Bastiaansen ◽  
Peter Hagoort
Keyword(s):  
Language Comprehension ◽  
Syntactic Structure ◽  
Critical Word ◽  
Beta Band ◽  
Brain Areas ◽  
Oscillatory Dynamics ◽  
Band Power ◽  
Sentence Level ◽  
Word Onset ◽  
Semantic Unification

During sentence level language comprehension, semantic and syntactic unification are functionally distinct operations. Nevertheless, both recruit roughly the same brain areas (spatially overlapping networks in the left frontotemporal cortex) and happen at the same time (in the first few hundred milliseconds after word onset). We tested the hypothesis that semantic and syntactic unification are segregated by means of neuronal synchronization of the functionally relevant networks in different frequency ranges: gamma (40 Hz and up) for semantic unification and lower beta (10–20 Hz) for syntactic unification. EEG power changes were quantified as participants read either correct sentences, syntactically correct though meaningless sentences (syntactic prose), or sentences that did not contain any syntactic structure (random word lists). Other sentences contained either a semantic anomaly or a syntactic violation at a critical word in the sentence. Larger EEG gamma-band power was observed for semantically coherent than for semantically anomalous sentences. Similarly, beta-band power was larger for syntactically correct sentences than for incorrect ones. These results confirm the existence of a functional dissociation in EEG oscillatory dynamics during sentence level language comprehension that is compatible with the notion of a frequency-based segregation of syntactic and semantic unification.

scholarly journals A Comparison between BCI Simulation and Neurofeedback for Forward/Backward Navigation in Virtual Reality

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Bilal Alchalabi ◽  
Jocelyn Faubert
Keyword(s):  
Computer Interface ◽  
Neurofeedback Training ◽  
Brain Signals ◽  
Band Power ◽  
Control Signals ◽  
Power Spectral ◽  
Control Command ◽  
Feedback Data ◽  
The Brain

A brain-computer interface (BCI) decodes the brain signals representing a desire to do something and transforms those signals into a control command. However, only a limited number of mental tasks have been previously investigated and classified. This study aimed to investigate two motor imagery (MI) commands, moving forward and moving backward, using a small number of EEG channels, to be used in a neurofeedback context. This study also aimed to simulate a BCI and investigate the offline classification between MI movements in forward and backward directions, using different features and classification methods. Ten healthy people participated in a two-session (48 min each) experiment. This experiment investigated neurofeedback of navigation in a virtual tunnel. Each session consisted of 320 trials where subjects were asked to imagine themselves moving in the tunnel in a forward or backward motion after a randomly presented (forward versus backward) command on the screen. Three electrodes were mounted bilaterally over the motor cortex. Trials were conducted with feedback. Data from session 1 were analyzed offline to train classifiers and to calculate thresholds for both tasks. These thresholds were used to form control signals that were later used online in session 2 in neurofeedback training to trigger the virtual tunnel to move in the direction requested by the user’s brain signals. After 96 min of training, the online band-power neurofeedback training achieved an average classification of 76%, while the offline BCI simulation using power spectral density asymmetrical ratio and AR-modeled band power as features, and using LDA and SVM as classifiers, achieved an average classification of 80%.

scholarly journals Electrocorticographic dissociation of alpha and beta rhythmic activity in the human sensorimotor system

2019 ◽  
Author(s):  
Arjen Stolk ◽  
Loek Brinkman ◽  
Mariska J. Vansteensel ◽  
Erik Aarnoutse ◽  
Frans S. S. Leijten ◽  
...  
Keyword(s):  
Sensorimotor Cortex ◽  
Rhythmic Activity ◽  
Neuronal Population ◽  
Imagery Task ◽  
Beta Band ◽  
Neuronal Populations ◽  
Band Power ◽  
Movement Selection ◽  
Spatiotemporal Coordination ◽  
Phase Relationships

AbstractThis study uses electrocorticography in humans to assess how alpha- and beta-band rhythms modulate excitability of the sensorimotor cortex during movement selection, as indexed through a psychophysically-controlled movement imagery task. Both rhythms displayed effector-specific modulations, tracked spectral markers of action potentials in the local neuronal population, and showed spatially systematic phase relationships (traveling waves). Yet, alpha- and beta-band rhythms differed in their anatomical and functional properties, were weakly correlated, and traveled along opposite directions across the sensorimotor cortex. Increased alpha-band power in the somatosensory cortex ipsilateral to the selected arm was associated with spatially-unspecific inhibition. Decreased beta-band power over contralateral motor cortex was associated with a focal shift from relative inhibition to excitation. These observations indicate the relevance of both inhibition and disinhibition mechanisms for precise spatiotemporal coordination of neuronal populations during movement selection. Those mechanisms are implemented through the substantially different neurophysiological properties of sensorimotor alpha- and beta-band rhythms.

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