Neural Representations of Relevant and Irrelevant Features in Perceptual Decision Making
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although perceptual decision making activates a network of brain areas involved in sensory, integrative, and motor functions, circuit activity can clearly be modulated by factors beyond the stimulus. Of particular interest is to understand how the network is modulated by top-down factors such as attention. Here, we demonstrate in a motion coherence task that selective attention produces marked changes in the blood oxygen level-dependent (BOLD) response in a subset of regions within a human perceptual decision-making circuit. Specifically, when motion is attended, the BOLD response decreases with increasing motion coherence in many regions, including the motion-sensitive area MT+, the intraparietal sulcus, and the inferior frontal sulcus. However, when motion is ignored, the negative parametric response in a subset of this circuit becomes positive. Through both modeling and connectivity analyses, we demonstrate that this inversion both reflects a top-down influence and segregates attentional from accumulation regions, thereby permitting us to further delineate the contributions of different regions to the perceptual decision.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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