To Go or Not to Go: Exploring brain activation during response inhibition reading tasks
Bibliographic record
Abstract
Objective: Response inhibition is an understudied component of reading that aids in the selection of appropriate responses amidst complicated tasks. Our objective was to explore the contribution of brain regions associated with response inhibition processing in reading tasks that vary in difficulty of response inhibition. Method: Participants (N = 15) completed two go/no-go reading tasks while in a functional magnetic resonance imaging (fMRI) scanner, with the instructions to “name aloud the letter strings that spell a real word.” For the minimal response inhibition condition, the foils, which are stimuli that should not be repsonded to, were nonwords with unfamiliar spelling and sound (e.g., “bink”). For the maximal response inhibition condition, the foils were pseudohomophones with unfamiliar spelling but familiar sound (e.g., “pynt”). The following brain regions associated with decision-making processes were analyzed: the anterior cingulate cortex (ACC), the dorsomedial prefrontal cortex (DMPFC), the inferior frontal gyrus (IFG), the middle temporal gyrus (MTG), the middle occipital gyrus (MOG), and the posterior insula (PI). Results: Significant differences in activation within the nonword task were found for the DMPFC and the PI (the ACC approached significance). Significant differences in activation within the pseudohomophone task were found for the ACC, the MTG, and the PI. The IFG was found to be greatly activated for all words that had familiar phonemes (sounds). The MOG was found to be activated across all tasks. Conclusion: We provide evidence for differential response inhibition processing in the decision-making network during reading tasks. This work is a necessary step in better understanding response inhibition ability for individuals with and without reading impairments.
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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 | 0.000 | 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".