Asymmetric Functional Gradients in the Human Subcortex
Bibliographic record
Abstract
ABSTRACT A central principle in our understanding of cerebral cortical organization is that homotopic left and right areas are functionally linked to each other, and also connected with structures that share similar functions within each cerebral cortical hemisphere. Here we refer to this concept as interhemispheric functional symmetry (IHFS). While multiple studies have described the distribution and variations of IHFS in the cerebral cortex, descriptions of IHFS in the subcortex are largely absent in the neuroscientific literature. Further, the proposed anatomical basis of IHFS is centered on callosal and other commissural tracts. These commissural fibers are present in virtually all cerebral cortical areas, but almost absent in the subcortex. There is thus an important knowledge gap in our understanding of subcortical IHFS. What is the distribution and variations of subcortical IHFS, and what are the anatomical correlates and physiological implications of this important property in the subcortex? Using fMRI functional gradient analyses in a large dataset (Human Connectome Project, n=1003), here we explored IHFS in human thalamus, lenticular nucleus, cerebellar cortex, and caudate nucleus. Our detailed descriptions provide an empirical foundation upon which to build hypotheses for the anatomical and physiological basis of subcortical IHFS. Our results indicate that direct or driver cerebral cortical afferent connectivity, as opposed to indirect or modulatory cerebral cortical afferent connectivity, is associated with stronger subcortical IHFS in thalamus and lenticular nucleus. In cerebellar cortex and caudate, where there is no variability in terms of either direct vs. indirect or driver vs. modulatory cerebral cortical afferent connections, connectivity to cerebral cortical areas with stronger cerebral cortical IHFS is associated with stronger IHFS in the subcortex. These two observations support a close relationship between subcortical IHFS and connectivity between subcortex and cortex, and generate new testable hypotheses that advance our understanding of subcortical organization.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".