Chopped Arms & Big Macs: ERP Correlates of Viewing and Imagining Aversive and Food Photos
Bibliographic record
Abstract
Abstract OBJECTIVESWe investigated the Event-Related Potential (ERP) correlates of perceived and imagined food photos and their relation to the perception and imagery of unpleasant emotional photos. Our aim was to determine whether similar or different patterns of neural activity were associated with viewing and imagining food photos versus emotional photos. METHODS Nine volunteers with prescreened normal mood and anxiety levels wore a 32 channel Cap with embedded electrodes (10/20 international system) connected to a high-density low-noise Neuroscan EEG system. Participants were tested during two different blocks: a hunger block (containing 25 neutral and food photos) and an emotional block (containing 3 sets of 20 neutral, unpleasant and pleasant photos). The photos were selected from the International Affective Picture System (Lang, Bradley, & Cuthbert, 1999). In both blocks, each trial began with a blank screen followed by presentation of a centered fixation point, displayed for 1 second. A photo was displayed for 3 seconds followed by a 1-second blank mask. For the next 3 seconds, participants were asked to form a mental image of the photo they had just viewed and then rate its vividness (i.e., the self-reported imagery intensity, D’Angiulli & Reeves, 2002) on a 5-point rating scale (1 = no image, 5 = very vivid). RESULTSGrand averages of ERPs recorded during perception of unpleasant and food photos revealed an early negative deflection (150-250 milliseconds post-stimulus) in the anterior areas (Centro-Frontal electrodes) followed by a late positive waveform (850-950 milliseconds post-stimulus) in the posterior areas (Parietal and Occipital electrodes). A similar pattern was observed for the ERPs recorded during the imagery of unpleasant photos, except that it was observed across the entire scalp and at significantly lower amplitudes. For food imagery, we found a negative deflection (450-550 milliseconds post-stimuli) followed by a late positive waveform for all anterior and posterior areas. Importantly, unpleasant imagery was rated as less vivid than food imagery. CONCLUSION These results suggest that unpleasant and food photos involve similar top-down EEG activation patterns during perception, but not during imagery. Indeed, the vividness data strongly suggest that the negative deflection may indicate suppression of unpleasant imagery. Our findings may have important application for desensitization and conditioning in the treatment of eating disorders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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".