Transcranial Direct Current Stimulation of the Dorsolateral Prefrontal Cortex Modulates Repetition Suppression to Unfamiliar Faces: An ERP Study
Bibliographic record
Abstract
Repeated visual processing of an unfamiliar face suppresses neural activity in face-specific areas of the occipito-temporal cortex. This "repetition suppression" (RS) is a primitive mechanism involved in learning of unfamiliar faces, which can be detected through amplitude reduction of the N170 event-related potential (ERP). The dorsolateral prefrontal cortex (DLPFC) exerts top-down influence on early visual processing. However, its contribution to N170 RS and learning of unfamiliar faces remains unclear. Transcranial direct current stimulation (tDCS) transiently increases or decreases cortical excitability, as a function of polarity. We hypothesized that DLPFC excitability modulation by tDCS would cause polarity-dependent modulations of N170 RS during encoding of unfamiliar faces. tDCS-induced N170 RS enhancement would improve long-term recognition reaction time (RT) and/or accuracy rates, whereas N170 RS impairment would compromise recognition ability. Participants underwent three tDCS conditions in random order at ∼72 hour intervals: right anodal/left cathodal, right cathodal/left anodal and sham. Immediately following tDCS conditions, an EEG was recorded during encoding of unfamiliar faces for assessment of P100 and N170 visual ERPs. The P3a component was analyzed to detect prefrontal function modulation. Recognition tasks were administered ∼72 hours following encoding. Results indicate the right anodal/left cathodal condition facilitated N170 RS and induced larger P3a amplitudes, leading to faster recognition RT. Conversely, the right cathodal/left anodal condition caused N170 amplitude and RTs to increase, and a delay in P3a latency. These data demonstrate that DLPFC excitability modulation can influence early visual encoding of unfamiliar faces, highlighting the importance of DLPFC in basic learning mechanisms.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".