Theta-activity in anterior cingulate cortex predicts task rules and their adjustments following errors
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
Accomplishing even simple tasks depend on neuronal circuits to configure how incoming sensory stimuli map onto responses. Controlling these stimulus-response (SR) mapping rules relies on a cognitive control network comprising the anterior cingulate cortex (ACC). Single neurons within the ACC convey information about currently relevant SR mapping rules and signal unexpected action outcomes, which can be used to optimize behavioral choices. However, its functional significance and the mechanistic means of interaction with other nodes of the cognitive control network remain elusive and poorly understood. Here, we report that core aspects of cognitive control are encoded by rhythmic theta-band activity within neuronal circuits in the ACC. Throughout task performance, theta-activity predicted which of two SR mapping rules will be established before processing visual target information. Task-selective theta-activity emerged particularly early during those trials, which required the adjustment of SR rules following an erroneous rule representation in the preceding trial. These findings demonstrate a functional correlation of cognitive control processes and oscillatory theta-band activity in macaque ACC. Moreover, we report that spike output of a subset of cells in ACC is synchronized to predictive theta-activity, suggesting that the theta-cycle could serve as a temporal reference for coordinating local task selective computations across a larger network of frontal areas and the hippocampus to optimize and adjust the processing routes of sensory and motor circuits to achieve efficient sensory-motor control.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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