Visuospatial integration: Paleoanthropological and archaeological perspectives
Bibliographic record
Abstract
The visuospatial system integrates inner and outer functional processes, organizing spatial, temporal, and social interactions between brain, body, and environment. These processes involve sensorimotor networks like the eye–hand circuit, which is especially important to primates, given their reliance on vision and touch as primary sensory modalities and the use of the hands in social and environmental interactions. At the same time, visuospatial cognition is intimately connected with egocentric memory, self-awareness, and simulation capacity. In the present article, we review issues associated with investigating visuospatial integration in extinct human groups through the use of anatomical and behavioral data gleaned from the paleontological and archaeological records. In modern humans, paleoneurological analyses have demonstrated noticeable and unique morphological changes in parietal cortex, an area crucial to visuospatial management. Archaeological data provides information on hand-tool interaction, the spatial behavior of past populations and their interaction with the environment (e.g. in domains like landscape use and navigation, the spatial relations implicit in social networks, etc.). Visuospatial integration may represent a critical bridge between extended cognition, self-awareness, and social perception. As such, visuospatial functions are relevant to the hypothesis that human evolution is characterized by changes in brain–body–environment interactions and relations, which enhance possibilities for integrating inner and outer cognitive components through neural plasticity and a specialized embodiment capacity. We therefore advocate the investigation of visuospatial functions in past populations through the paleoneurological study of anatomical elements and archaeological analysis of visuospatial behaviors.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".