Neuronal Activity in the Visual Cortex Reveals the Temporal Order of Cognitive Operations
Bibliographic record
Abstract
Most mental processes consist of a number of processing steps that are executed sequentially. The timing of the individual mental operations can usually only be estimated indirectly, from the pattern of reaction times. In vision, however, many processing steps are associated with the modulation of neuronal activity in early visual areas. Here we exploited this association to elucidate the time course of neuronal activity related to each of the self-paced mental processing steps in complex visual tasks. We trained monkeys to perform two tasks, search-trace and trace-search, which required performing a sequence of two operations: a visual search for a specific color and the mental tracing of a curve. We used multielectrode recording techniques to monitor the representations of multiple visual items in area V1 at the same time and found that the relevant curve as well as the target of visual search evoked enhanced neuronal activity with a timing that depended on the order of operations. This modulation of neuronal activity in early visual areas could allow these areas to (1) act as a cognitive blackboard that permits the exchange of information between successive processing steps of a sequential visual task and to (2) contribute to the orderly progression of task-dependent endogenous attention shifts that are driven by task structure and evolve over hundreds of milliseconds.
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How this classification was reachedexpand
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".