Frontal-striatal circuit functions: Context, sequence, and consequence
Bibliographic record
Abstract
The exact role of the basal ganglia in both the motor and non-motor domains has proven elusive since it is virtually impossible to refer to its function in isolation of cortical, and especially frontal cortical circuits. The result is that we often speak of frontal-striatal circuits and functions but this still leaves us in the dark when trying to specify basal ganglia information processing. A critical review of the data from both basic science and clinical studies suggests that we should break down processing along a temporal continuum, including the domains of context, sequential information processing, and feedback or reinforcement (i.e., the consequences of action). This analysis would cut across other theoretical constructs, such as attention, central executive, memory, and learning functions, traditionally employed in the neuropsychological literature. Under specified behavioral constraint, the basal ganglia can then be seen to be involved in fundamental aspects of attentional control (often covert), in the guidance of the early stages of learning (especially reinforcement-based, but also encoding strategies in explicit paradigms), and in the associative binding of reward to cue salience and response sequences via dopaminergic mechanisms. Parkinson's disease is considered to offer only a limited view of basal ganglia function due to partial striatal depletion of dopamine and the potential involvement of other structures and transmitters in its pathology. It is hoped that the present formulation will suggest new heuristic research strategies for basal ganglia research, permitting a closer link to be established between neurophysiological, functional imaging and neuropsychological paradigms.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".