A Positron Emission Tomography Study of Silent and Oral Single Word Reading in Stuttering and Nonstuttering Adults
Bibliographic record
Abstract
Over the last decade positron emission tomography (PET) has been used extensively for the study of language and other cognitive and sensorimotor processes in healthy and diseased individuals. In the present study, [15O]H2O PET scanning was used to investigate the lateralization and functional distribution of cortical and subcortical activity involved in single word reading in stuttering and nonstuttering individuals. Ten right-handed male stuttering adults and matched nonstuttering individuals were instructed to read individually presented single words either silently or out loud. Subtraction of functional brain images obtained during each of the two reading tasks, and during a non-linguistic baseline task, was used to calculate within-group and between-group differences in regional cerebral blood flow by means of statistical parametric mapping. Increased activation in the left anterior cingulate cortex (ACC) was observed during silent reading in the stuttering speakers but not in the nonstuttering group. Because of the hypothesized role of the ACC in selective attention and covert articulatory practice, it is suggested that the observed increased ACC activation in the stuttering individuals reflects the presence of cognitive anticipatory reactions related to stuttering. During the oral reading task, within-group comparisons showed bilateral cortical and subcortical activation in both the stuttering and the nonstuttering speakers. Between-group comparisons showed a proportionally greater left hemisphere activation in the nonstuttering speakers, and a proportionally greater right hemisphere activation in the stuttering individuals. The results of the present study provide qualified support for the hypothesis that stuttering adults show atypical lateralization of language 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".