Revealing Connections in Object and Scene Processing Using Consecutive TMS and fMR-Adaptation
Bibliographic record
Abstract
When processing the visual world, our brain must perform many computations that may occur across several regions. It is important to understand communications between regions in order to understand perceptual processes underlying processing of our environment. We sought to determine the connectivity of object and scene processing regions of the cortex, which are not fully established. In order to determine these connections repetitive transcranial magnetic stimulation (rTMS) and functional magnetic resonance-adaptation (fMR-A) were paired together. rTMS was applied to object-selective lateral occipital (LO) and scene-selective transverse occipital sulcus (TOS). Immediately after stimulation, participants underwent fMR-A, and pre- and post-TMS responses were compared. TMS disrupted remote regions revealing connections from LO and TOS to remote object and scene-selective regions in the occipital cortex. In addition, we report important neural correlates regarding the transference of object related information between modalities, from LO to outside the ventral network to parietal and frontal areas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".