Activation in Right Dorsolateral Prefrontal Cortex Underlies Stuttering Anticipation
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Bibliographic record
Abstract
People who stutter learn to anticipate many of their overt stuttering events. Despite the critical role of anticipation, particularly how responses to anticipation shape stuttering behaviors, the neural bases associated with anticipation are unknown. We used a novel approach to identify anticipated and unanticipated words, which were produced by 22 adult stutterers in a delayed-response task while hemodynamic activity was measured using functional near infrared spectroscopy (fNIRS). Twenty-two control participants were included such that each individualized set of anticipated and unanticipated words was produced by one stutterer and one control participant. We conducted an analysis on the right dorsolateral prefrontal cortex (R-DLPFC) based on converging lines of evidence from the stuttering and cognitive control literatures. We also assessed connectivity between the R-DLPFC and right supramarginal gyrus (R-SMG), two key nodes of the frontoparietal network (FPN), to assess the role of cognitive control, and particularly error-likelihood monitoring, in stuttering anticipation. All analyses focused on the five-second anticipation phase preceding the go signal to produce speech. The results indicate that anticipated words are associated with elevated activation in the R-DLPFC, and that compared to non-stutterers, stutterers exhibit greater activity in the R-DLPFC, irrespective of anticipation. Further, anticipated words are associated with reduced connectivity between the R-DLPFC and R-SMG. These findings highlight the potential roles of the R-DLPFC and the greater FPN as a neural substrate of stuttering anticipation. The results also support previous accounts of error-likelihood monitoring and action-stopping in stuttering anticipation. Overall, this work offers numerous directions for future research with clinical implications for targeted neuromodulation.
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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) | 0.002 | 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 it