Category-Selective Visual Regions Have Distinctive Signatures of Connectivity in Neonates
Bibliographic record
Abstract
Abstract The development of the ventral visual stream is shaped both by an innate proto-organization and by experience. The fusiform face area (FFA), for example, has stronger connectivity to early visual regions representing the fovea and lower spatial frequencies. In adults, category-selective regions in the ventral stream (e.g. the FFA) also have distinct signatures of connectivity to widely distributed brain regions, which are thought to encode rich cross-modal, motoric, and affective associations (e.g., tool regions to the motor cortex). It is unclear whether this long-range connectivity is also innate, or if it develops with experience. We used MRI diffusion-weighted imaging with tractography to characterize the connectivity of face, place, and tool category-selective regions in neonates (N=445), 1-9 month old infants (N=11), and adults (N=14). Using a set of linear-discriminant classifiers, category-selective connectivity was found to be both innate and shaped by experience. Connectivity for faces was the most developed, with no evidence of significant change in the time period studied. Place and tool networks were present at birth but also demonstrated evidence of development with experience, with tool connectivity developing over a more protracted period (9 months). Taken together, the results support an extended proto-organizon to include long-range connectivity that could provide additional constraints on experience dependent development.
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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 | 0.000 |
| 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) | 0.001 | 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".