Selective Biasing of a Specific Bistable-Figure Percept Involves fMRI Signal Changes in Frontostriatal Circuits: A Step Toward Unlocking the Neural Correlates of Top-Down Control and Self-Regulation
Bibliographic record
Abstract
Attention, suggestion, context and expectation can all exert top-down influence on bottom-up processes (e.g., stimulus-driven mechanisms). Identifying the functional neuroanatomy that subserves top-down influences on sensory information processing can unlock the neural substrates of how suggestion can modulate behavior. Using functional magnetic resonance imaging (fMRI), we scanned 10 healthy participants (five men) viewing five bistable figures. Participants received a directional cue to perceive a particular spatial orientation a few seconds before the bistable figure appeared. After presentation, participants pressed a button to indicate their locking into the one desired orientation of the two possible interpretations. Participants additionally performed tests of impulse control and sustained attention. Our findings reveal the role of specific frontostriatal structures in selecting a particular orientation for bistable figures, including dorsolateral prefrontal regions and the putamen. Additional contrasts further bolstered the role of the frontostriatal system in the top-down processing of competing visual perceptions. Separate correlations of behavioral variables with fMRI activations support the idea that the frontostriatal system may mediate attentional control when selecting among competing visual perceptions. These results may generalize to other psychological functions. With special relevance to clinical neuroscience and applications involving attention, expectation and suggestion (e.g., hypnosis), our results address the importance of frontostriatal circuitry in behavioral modulation.
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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".