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Record W6888629479 · doi:10.21227/c8mn-8525

The use of tACS on movement-related brain waves

2022· dataset· en· W6888629479 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE DataPort · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsMcGill University
Fundersnot available
KeywordsNeuroplasticityElectroencephalographyMotor cortexMotor learningElectrophysiologyBrain stimulationPrimary motor cortexCerebral cortexBeta RhythmLocal field potential

Abstract

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Background. MEG and EEG are techniques used to study the electrical activity from different brain areas. The signal arises from synchronized postsynaptic potentials of neurons that generate electrophysiological oscillations in different frequency bands. During movement process, the EEG/MEG spectral power within the beta range (15–29 Hz) decreases in amplitude and this is termed as Event-Related Desynchronization (ERD) [1]. It has been revealed that ERD is related with increased excitability of neurons in sensorimotor areas [2], [3]. Moreover, ERD amplitudes at baseline and during movement vary between age groups of young and old [4]. Abnormal increases in beta EEG power at baseline ERD are also well documented in e.g. Parkinson’s diseases and stroke [5], [6].There is converging evidence suggesting an association of cortical oscillations in the motor cortex with neuroplasticity events underlying motor memory consolidation [7], [8]. Using EEG, positive effects of exercise on motor learning by quantifying the modulation of ERD has been studied [9]. It was revealed that improvements in motor learning was associated with a significant acute decrease in beta-band ERD in sensorimotor areas measured during a grip task. Based on previous research studies, non-invasive brain stimulation (NIBS) protocols can induce neuroplasticity changes[10]–[12]. For instance, tACS allows for inducing direct cortical alterations in the underlying intrinsic neural oscillations by modulating cortical excitability through electrodes placed on the surface of the scalp [11]. Therefore, NIBS is considered as promising therapy for patients with motor deficits caused by neurodegenerative diseases.Objective. Since NIBS could induce changes in neuroplasticity and ERD is closely related with motor performance, the objective of this study is to determine the effects of NIBS protocols (tDCS and tACS) on baseline ERD.Hypothesis. We will use of a novel HD-EEG cap which allows for simultaneous EEG recording and NIBS (tDCS or tACS); this will increase spatial accuracy of stimulation and eliminate the delay between stimulation and EEG recordings. We hypothesize that tDCS applied through a custom electrode configuration in the HD-EEG cap will decrease baseline ERD, whereas tACS could induce an increase in baseline ERD. Successful outcome will further help to design NIBS therapy for patients with motor deficits.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0160.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.297
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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