Variability in the effects of transcranial direct current stimulation on free choice behaviour
Bibliographic record
Abstract
Abstract Transcranial direct current stimulation (tDCS) is used as a tool to causally influence neural activity in humans non-invasively. Although most studies recruit a large number of participants in order to uncover population-level effects, growing evidence suggests that tDCS may be expected to induce different effects in different individuals, leading to large inter-individual variability and confounds in population-level testing. Additionally, variability may arise from intra-individual differences and confounds that are difficult to assess in studies with limited to no re-testing. Here, we performed 10 sessions of tDCS each on 5 human participants performing a free choice saccade task while neural activity was measured via EEG. Participants first underwent functional MRI to localize the human right frontal eye field (rFEF) homologue. An HD-tDCS montage was then used to focally target rFEF based on individual MRI localizations, alternating the polarity between anodal or cathodal current over repeated sessions during a 5 week period (twice weekly). On stimulation days, participants performed a free choice task prior to and after administration of tDCS while EEG activity was recorded. To quantify the likelihood that tDCS induced a causal effect on behaviour and neural activity across different levels of analysis, we developed a multilevel causal inference method based on permutation testing of a quasi-experiment (difference-in-differences). We then used this method to assess the likelihood of a causal effect at different levels of abstraction: group-level, participant-level, and paired-session level. At the group-level, we found evidence for an influence of tDCS on choice reaction times, which followed a reaction-time dependent change in EEG activity, and on how choices depended on previous trials. However, individuals showed heterogeneous effects. Further, analysis of paired-session variability often belied the pooled individual effect, suggesting that different sessions of tDCS may have produced markedly different effects in the same participants. In light of this, we discuss potential causes of this variability, and the counterfactuals that should be considered when making data-driven inferences about the effects of tDCS. Author Summary Developing reliable interventions on human neural activity is important for establishing causal relationships in basic research and developing therapeutics for pathological brain states. Transcranial direct current stimulation is a promising technique to intervene on neural activity safely in humans, but it is poorly understood if tDCS reliably impacts brain and behaviour in the same way across sessions. We performed an extensive test-retest study on tDCS in humans, and developed statistical methods to assess variability across sessions. Our results provide strong evidence against a consistent effect of tDCS in the same individual across different sessions. This warrants caution in using tDCS as a predictable intervention on neural activity in research and clinical practices.
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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 | 0.003 | 0.014 |
| 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 | 0.001 |
| 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".