Top–Down Modulation of Human Early Visual Cortex after Stimulus Offset Supports Successful Postcued Report
Bibliographic record
Abstract
Modulations of sensory processing in early visual areas are thought to play an important role in conscious perception. To date, most empirical studies focused on effects occurring before or during visual presentation. By contrast, several emerging theories postulate that sensory processing and conscious visual perception may also crucially depend on late top-down influences, potentially arising after a visual display. To provide a direct test of this, we performed an fMRI study using a postcued report procedure. The ability to report a target at a specific spatial location in a visual display can be enhanced behaviorally by symbolic auditory postcues presented shortly after that display. Here we showed that such auditory postcues can enhance target-specific signals in early human visual cortex (V1 and V2). For postcues presented 200 msec after stimulus termination, this target-specific enhancement in visual cortex was specifically associated with correct conscious report. The strength of this modulation predicted individual levels of performance in behavior. By contrast, although later postcues presented 1000 msec after stimulus termination had some impact on activity in early visual cortex, this modulation no longer related to conscious report. These results demonstrate that within a critical time window of a few hundred milliseconds after a visual stimulus has disappeared, successful conscious report of that stimulus still relates to the strength of top-down modulation in early visual cortex. We suggest that, within this critical time window, sensory representation of a visual stimulus is still under construction and so can still be flexibly influenced by top-down modulatory processes.
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.
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 | 0.000 | 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".