Broca’s region: linking human brain functional connectivity data and non‐human primate tracing anatomy studies
Bibliographic record
Abstract
Brodmann areas 6, 44 and 45 in the ventrolateral frontal cortex of the left hemisphere of the human brain constitute the anterior language production zone. The anatomical connectivity of these areas with parietal and temporal cortical regions was recently examined in an autoradiographic tract-tracing study in the macaque monkey. Studies suggest strong correspondence between human resting state functional connectivity (RSFC) based on functional magnetic resonance imaging data and experimentally demonstrated anatomical connections in non-human primates. Accordingly, we hypothesized that areas 6, 44 and 45 of the human brain would exhibit patterns of RSFC consistent with patterns of anatomical connectivity observed in the macaque. In a primary analysis, we examined the RSFC associated with regions-of-interest placed in ventrolateral frontal areas 6, 44 and 45, on the basis of local sulcal and gyral anatomy. We validated the results of the primary hypothesis-driven analysis with a data-driven partitioning of ventrolateral frontal cortex into regions exhibiting distinct RSFC patterns, using a spectral clustering algorithm. The RSFC of ventrolateral frontal areas 6, 44 and 45 was consistent with patterns of anatomical connectivity shown in the macaque. We observed a striking dissociation between RSFC for the ventral part of area 6 that is involved in orofacial motor control and RSFC associated with Broca's region (areas 44 and 45). These findings indicate rich and differential RSFC patterns for the ventrolateral frontal areas controlling language production, consistent with known anatomical connectivity in the macaque brain, and suggest conservation of connectivity during the evolution of the primate brain.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".