A case study of differences in brain electrical activity between recall-based mental imagery and a subjective phenomenon of “upsight”
Bibliographic record
Abstract
Background: This case study investigated differences in brain electrical activity between two laboratory conditions in an individual who reports a subjective experience of a phenomenon he calls “upsight.” The individual describes upsight as the capacity to perceive at will holographic images as though they appear on an inset screen that overlays his ordinary visual field, with eyes open or closed. Methods: The individual alternated 200 times between 30-second epochs of a control condition (recalling mentally an image he had seen previously) and the upsight (seeing the image on the internal “screen”) condition while 64-channel EEG was collected. Each of the epochs began with a randomly selected image being presented to the individual on a computer screen, along with an audio prompt to close his eyes and perform one of the two experimental conditions. Results: Strong significant differences were observed in the scalp EEG signal between the two conditions, most notably in the alpha frequency range (cluster peak at 11 Hz at channel PO8; t = -19.5; p-corrected<0.001). Source reconstruction analysis showed a strong alpha asymmetry in frontoparietal brain regions (cluster peak at 11 hz at the left frontal midline cortex at 11 Hz; t = -17.7; p-corrected<0.001). Conclusions: This finding is interpreted in line with the asymmetric inhibition model, namely that the upsight experience was associated with a strong reduction in inhibition in frontoparietal brain regions, possibly reflecting the participant's intentional suppression of the upsight perceptual stream to successfully perform the control condition. Experimental design strategies for attempting to determine the source and nature of the upsight perceptual stream are discussed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".