No aftereffect of transcranial alternating current stimulation (tACS) on theta activity during an inter-sensory selective attention task
Bibliographic record
Abstract
BACKGROUND: Selective attention is essential to filter the constant flow of sensory information reaching the brain. The contribution of theta neuronal oscillations to attentional function has been the subject of several electrophysiological studies, yet no causal relationship has been established between theta rhythms and selective attention mechanisms. OBJECTIVE AND HYPOTHESES: We aimed to clarify the causal role of theta oscillations in inter-sensory selective attention processes by combining transcranial alternating current stimulation (tACS) and electrophysiology (EEG) techniques. We hypothesized that modulation of theta activity by tACS enhances selective attention, with greater behavioral efficiency and theta power over fronto-central regions after theta-tACS compared to control conditions. METHODS: In a double-blinded within-subject study conducted in young adults (n = 20), three stimulation conditions were applied prior to a cued inter-sensory (auditory and visual) selective attention task. The frequency of theta stimulation was individualized to match the endogenous theta peak of each participant. In addition to a sham condition, stimulation at an off-target frequency (20 Hz) was also applied. We analyzed behavioral efficiency and variability measures and performed spectral and time-frequency power analyses. RESULTS: No statistically significant differences in task performance or theta EEG activity were found between theta-tACS and control-tACS conditions (ps > 0.05). CONCLUSIONS: The results of our study suggest that theta-tACS did not modulate performance or offline oscillations in the context of inter-sensory attention. These findings challenge the design of tACS protocols for future studies aiming to understand the contribution of theta oscillations in attentional processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".