Aftereffects following adaptation to face mental images
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Bibliographic record
Abstract
Recent neuroimaging studies using fMRI and EEG have consistently revealed overlapping brain activation during both mental imagery and visual perception. Yet, the extent to which these processes share underlying mechanisms remains elusive. Our prior work uncovered a weak correlation between perceptual thresholds and mental imagery (i.e., vividness judgments) for identical natural scenes (Charest et al., 2023), prompting a new investigation using adaptation as a psychophysiological tool. Adaptation is an invaluable tool for non-invasive exploration of low- to high-level visual processing, including face (e.g. Leopold et al., 2001), object (e.g. Feng & He, 2005), and scene (e.g., Greene & Oliva, 2005) processing. Importantly, adaptation has been previously used to induce aftereffects of imagined motion (Winawer et al., 2010). However, it is still unknown if adaptation can elicit aftereffects following high-level adaptation. In each trial, participants viewed the same two full-frontal, color faces simultaneously for 1 second, one on each side of a fixation cross. Subsequently, they were instructed to imagine the face previously shown either on the left or the right for 6 seconds. Participants then assessed whether a morph resembled the face initially shown on the left or the right (40 repetitions × 7 morph levels × 2 imagined faces, totaling 560 trials). Preliminary results from five participants revealed significantly different means for the cumulative Gaussian distributions fitted to the proportions of responses in favor of face B as a function of morph levels when face A or face B was imagined (t(4) = -4.69, p < 0.01; adapted to face A: M = 0.55; and to face B: M = 0.61). These initial results offer a promising avenue for finely comparing high-level visual processing and mental imagery across individuals with diverse cognitive proficiencies, paving the way for a deeper understanding of the interconnected nature of these cognitive domains.
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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 | 0.000 |
| 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) | 0.001 | 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