Mental rotation of feet in individuals with Body Integrity Identity Disorder, lower-limb amputees, and normally-limbed controls
Bibliographic record
Abstract
Body Integrity Identity Disorder (BIID) is a non-psychotic condition wherein individuals desire amputation or paralysis of one or more healthy, fully-functioning limbs (predominantly the legs). Individuals with BIID have been suggested to have a mismatch between the perceived mental representation of the body and its actual physical structure, such that their desired identity matches that of a lower-limb amputee. Accordingly, studies have reported an altered central network involving body representation of the legs in BIID, but its relationship to behavior remains unclear. In the present study, we investigated the integrity of body representation in individuals with BIID, acquired lower-limb amputees, and normally-limbed controls using an online mental rotation task. Participants judged the laterality of left and right foot images presented from different views, orientations, and of different types. We expected BIID participants to be slower for mentally rotating images that corresponded to their affected legs than lower-limb amputees and normally-limbed participants. We found that the groups did not significantly differ in their performance. All participants were slower at judging feet presented in awkward postures than natural postures, replicating previous studies and validating our online paradigm. The results are discussed in terms of the robust nature of visual and sensorimotor lower-limb representations, whether related to the self or as prototype, in the context of disturbed lower-limb integrity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".