Secondary somatosensory cortex of primates: beyond body maps, toward conscious self-in-the-world maps
Bibliographic record
Abstract
Recent human imaging studies have revealed the involvement of the secondary somatosensory cortex (SII) in processes that require high-level information integration, such as self-consciousness, social relations, whole body representation, and metaphorical extrapolations. These functions are far beyond its known role in the formation of body maps (even in their most complex forms), requiring the integration of different information modalities in addition to somatosensory information. However, no evidence of such complex processing seems to have been detected at the neuronal level in animal experiments, which would constitute a major discrepancy between human and non-human animals. This article scrutinizes this gap, introducing experimental evidence of human and non-human primates' SII functions set in context with their evolutionary significance and mechanisms, functionally situating the human SII as a primate brain. Based on the presented data, a new concept of a somatocentric holistic self is proposed, represented as a more comprehensive body-in-the-world map in the primate SII, taking into account evolutionary aspects that characterize the human SII and its implication in the emergence of self-consciousness. Finally, the idea of projection is introduced from the viewpoint of cognitive science, providing a logical explanation to bridge this gap between observed behavior and neurophysiological data.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".