Common Neural Recruitment across Diverse Sustained Attention Tasks
Bibliographic record
Abstract
At one level "sustained attention" is simply a description of a task demand. It is often used, however, in reference to a putatively unitary capacity to remain engaged in tasks that are lengthy, dull, repetitive and/or characterised by long intervals between relevant events. Deficits in sustained attention have been reported in a range of clinical conditions. Despite this, there is paucity of well-controlled human functional imaging evidence about regions commonly recruited during diverse sustained attention tasks. Here, for the first time, we used functional magnetic resonance imaging (fMRI) to monitor brain activity patterns as healthy volunteers performed two sustained attention tasks. The first, widely used in clinical assessment, required participants to count tones separated by long unpredictable intervals. This was contrasted with a control counting condition in which tones were presented at a brisk, regular rate. The second task was the Sustained Attention to Response Test (SART) in which participants responded to sequentially presented digits with the exception of a nominated infrequent no-go target. In the control condition, no-go trials were explicitly absent, removing the requirement to maintain a readiness to withhold responses. Although there were distinct patterns of activation associated with each task relative to its control, activity common to both tasks was found in the bilateral inferior frontal operculum, anterior cingulate, and bilateral premotor cortex. Although some researchers argue for a specific role of the inferior frontal operculum in inhibition, our results are consistent with recent findings of a more general attentional role for this area. The maintenance of a goal directed stance in the absence of strong environmental facilitation is challenging and this may underpin the sensitivity of sustained attention tasks to functional difficulties in a range of clinical groups.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".