A multimodal characterization of low-dimensional thalamocortical structural connectivity patterns
Bibliographic record
Abstract
The human thalamus is a heterogeneous subcortical structure coordinating whole-brain activity. Investigations of its internal organization reveal differentiable subnuclei, however, a consensus on subnuclei boundaries remains absent. Recent work suggests that thalamic organization additionally reflects continuous axes transcending nuclear boundaries. Here, we study how low-dimensional axes of thalamocortical structural connectivity relate to intrathalamic microstructural features, functional connectivity, and structural covariance. Using diffusion MRI, we compute a thalamocortical structural connectome and derive two main axes of thalamic organization. The principal axis, extending from medial to lateral, relates to intrathalamic myelin, and functional connectivity organization. The secondary axis corresponds to the core-matrix cell distribution. Lastly, exploring multimodal associations globally, we observe the principal axis consistently differentiating limbic, frontoparietal, and default mode network nodes from dorsal and ventral attention networks across modalities. However, the link with sensory modalities varies. In sum, we show the coherence between lower dimensional patterns of thalamocortical structural connectivity and various modalities, shedding light on multiscale thalamic 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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".