Variability in Brain Responses to Galvanic Vestibular Stimulation: A Granger Causality Analysis of Independent Components in Resting-State EEG
Bibliographic record
Abstract
BackgroundVestibular stimulation has emerged as a promising therapeutic tool for neurological conditions, including Parkinson's Disease.However, selecting optimal stimulation parameters is challenging due to the complexity of natural vestibular processing, where head movements occur around 1 Hz, and vestibular afferents fire between 60 and 100 spikes per second. ObjectiveThis study aimed to investigate electroencephalogram (EEG) responses to over 300 distinct Galvanic Vestibular Stimulation (GVS) protocols to understand how different waveforms affect brain activity.The protocols included sinusoidal, amplitude-modulated (AM), chirp AM, frequencymodulated (FM), and binary modulated (BN) stimuli.Methods EEG data were collected from five healthy subjects and analyzed using Independent Component Analysis (ICA) to isolate neural sources.ICASSO was employed to assess the stability of ICs across multiple ICA runs, ensuring their reliability.Granger causality (GC) tests were applied between GVS stimuli and extracted ICs to assess causal relationships, with corrections for multiple comparisons. ResultsPreliminary results from five subjects showed that approximately 250 out of 304 GVS protocols elicited significant Granger causality with EEG activity.Although inter-subject variability was notable, consistent patterns were observed within subjects.Specifically, in each subject, certain brain regions were consistently affected by particular GVS waveforms.For example, in subject 5, components in the occipital, central-parietal, frontal, and central regions showed significant causal relationships with GVS waveforms, including Chirp AM (75 Hz carrier, Beta chirp modulation), BN modulated (50-75 Hz), BN modulated (Gamma band), and FM (125 Hz carrier, 25 Hz modulation). DiscussionThe results indicate that GVS reliably influences brain activity, with significant causal relationships between GVS stimuli and EEG signals in most protocols.Although affected brain regions varied between subjects, consistent patterns within subjects suggest predictable neural modulation by GVS.This inter-subject variability highlights the need to optimize stimulation parameters for individualized therapeutic interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".