ERP Evidence for Rapid Hedonic Evaluation of Logos
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We know that human neurocognitive systems rapidly and implicitly evaluate emotionally charged stimuli. But what about more everyday, frequently encountered kinds of objects, such as computer desktop icons and business logos? Do we rapidly and implicitly evaluate these more prosaic visual images, attitude objects that might only engender a mild sense of liking or disliking, if at all? To address this question, we asked participants to view a set of unfamiliar commercial logos in the context of a target identification task as brain electrical responses to these objects were recorded via event-related potentials (ERPs). Following this task, participants individually identified those logos that were most liked or disliked, allowing us to then compare how ERP responses to logos varied as a function of hedonic evaluation-a procedure decoupling evaluative responses from any normative classification of the logos themselves. In Experiment 1, we found that visuocortical processing manifest a specific bias for disliked logos that emerged within the first 200 msec of stimulus onset. In Experiment 2, we replicated this effect while dissociating normative- and novelty-related influences. Taken together, our results provide direct electrophysiological evidence suggesting that we rapidly and implicitly evaluate commercial branding images at a hedonic level.
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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 | 0.002 | 0.019 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it