An ART Tour de Force on Mental Imagery: Vividness, Individual Bias Differences, and Complementary Visual Processing Streams
Bibliographic record
Abstract
Grossberg’s adaptive resonance theory (ART) provides a framework for understanding possible interactions between mental imagery and visual perception. Our purpose was to integrate, within ART, the phenomenological notion of mental image vividness and thus investigate the possible biasing effects of individual differences on visual processing. Using a Vernier acuity task, we tested whether indirect estimation of relative V1 size (small, medium, large) and self-reported vividness, in three subgroups of 53 observers, could predict significant effects of priming, interference, or more extreme Perky effects (negative and positive), which could be induced by imagery, impacting acuity performance. The results showed that small V1 was correlated with priming and/or negative Perky effects independently of vividness; medium V1 was related to interference at low vividness but priming at high vividness; and large V1 was related to positive Perky effects at high vividness but negative Perky effects at low vividness. Our interpretation of ART and related modeling based on ARTSCAN contributes to expanding Grossberg’s comprehensive understanding of how and why individually experienced vividness may drive the differential use of the dorsal and ventral complementary visual processing pathways, resulting in the observed effects of imagery on concurrent perception.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.003 |
| 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 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".