Functional displacement of cortical neuromagnetic somatosensory responses: enhancing embodiment in the rubber hand illusion
Bibliographic record
Abstract
Abstract The integration of an artificial limb as part of one’s body involves complex neuroplastic changes resulting from various sensory inputs to the brain. While sensory feedback is known to be crucial for embodiment, current evidence points merely to the attenuation of somatosensory processing, while the positive contributions of somatosensory areas to embodiment remain unknown. This study investigated the relationship between embodiment and adaptive neuroplasticity of early-latency somatosensory evoked fields (SEFs) in the primary somatosensory cortex (S1) following the Rubber Hand Illusion (RHI), known to induce short-term artificial limb embodiment. Nineteen healthy adults underwent neuromagnetic recordings during electrical stimulation of the little finger and thumb, before and after the RHI. We found a displacement of early SEF sources. In particular, we observed a correlation between the extent of rubber hand embodiment and specific changes to the m20 component (magnetic equivalent to the N20) in Brodmann Area 3b: a larger displacement and a greater reduction in m20 magnitude predicted the amount of embodiment, highlighting an important functional contribution of this first cortical input. Furthermore, we observed a posteriorly directed m35 displacement towards Area 1, known to be important for visual integration during touch perception (Rosenthal et al., 2023). Our finding that the larger displacement for the m35 did not correlate with the extent of embodiment implies a functional distinction between neuroplastic changes across these two components and areas in their contributions to successful artificial limb embodiment: (i) the earlier neuroplastic changes to m20 may shape the extent of artificial limb ownership, and (ii) the posteriorward shift of the m35 into Area 1 is suggestive of a mechanistic contribution to early visual-tactile integration that initially establishes the embodiment. Taken together, these findings suggest that multiple distinct changes occur during early-latency SEFs and their displacement in S1 last beyond the duration of the illusion and are important for the successful integration of an artificial limb within the body representation.
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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 | 0.001 |
| 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) | 0.002 | 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".