Less is more: Aesthetic liking is inversely related to metabolic expense by the visual system
Why this work is in the frame
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Bibliographic record
Abstract
Energy efficiency is a major driving force in the evolution of organisms, and previous research implies that humans may have evolved pleasure-based signals to guide optimal actions. But could this energy-saving heuristic also apply to aesthetic pleasure? We test this hypothesis using both an in silico model of the visual system (VGG19) and human observers, finding strong evidence in both. First, we measure the proxy for metabolic cost incurred by VGG19-either pretrained for object and scene categorization or randomly initialized-as it processes 4,914 images of objects and scenes, revealing an inverse relationship between aesthetic preferences and metabolic cost, and only in the pretrained model. Next, we compare aesthetic ratings of visual stimuli to metabolic activity in the human visual system, measured via the blood oxygen level-dependent signal during functional magnetic resonance imaging. We observe the same inverse relationship between blood oxygen level dependent signals and aesthetic preferences in both early visual regions (V1, V2, and V4) and higher-level regions (fusiform face area, occipital place area, and parahippocampal place area). These findings suggest that aesthetic preferences may at least partially arise from an affective heuristic favoring low-energy states, and they offer a unified framework linking empirical evidence on visual discomfort with theories of processing fluency, image complexity, and prototypicality, providing a straightforward model for understanding aesthetic judgments.
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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 | 0.001 |
| 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) | 0.000 | 0.001 |
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