Ventral striatal gamma oscillations are highly variable from trial to trial, and are dominated by behavioural state, and only weakly influenced by outcome value
Bibliographic record
Abstract
The human and rodent ventral striatal local field potentials show striking oscillations in the gamma band (~ 40-100 Hz), which have been linked to aspects of behaviour such as reward anticipation and delivery, movement initiation, learning from feedback, and decision-making. These oscillations show a rich temporal organization, whose relationship with behavioural variables is not well understood. Here, we show that, in rats performing a conditioned approach task, low-gamma and high-gamma oscillations during an immobile reward anticipation epoch were largely insensitive to outcome value, even though rats distinguished behaviourally between different outcomes, and single units encoded outcome value. Behaviour was highly stereotyped, yet we observed large variability from trial to trial in the occurrence and timing of these oscillations. Furthermore, higher-order features such as high-gamma power leading low-gamma power, and phase-amplitude coupling to lower-frequency bands, were only marginally modulated by outcome value. Moreover, these patterns closely resembled those found during off-task rest periods in which no rewards could be earned. These observations suggest a new interpretation of ventral striatal gamma oscillations as reflecting a default or resting state, with only minor and highly variable modulation by specific task-related variables.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".