Intrinsic Functional Boundaries of Lateral Frontal Cortex in the Common Marmoset Monkey
Bibliographic record
Abstract
The common marmoset (Callithrix jacchus) is a small New World primate species that has been recently targeted as a potentially powerful preclinical model of human prefrontal cortex dysfunction. Although the structural boundaries of frontal cortex were described in marmosets at the start of the 20th century (Brodmann, 1909) and refined more recently (Paxinos et al., 2012), the broad functional boundaries of marmoset frontal cortex have yet to be established. In this study, we sought to functionally derive boundaries of the marmoset lateral frontal cortex (LFC) using ultra-high field (9.4 T) resting-state functional magnetic resonance imaging (RS-fMRI). We collected RS-fMRI data in seven (four females, three males) lightly anesthetized marmosets and used a data-driven hierarchical clustering approach to derive subdivisions of the LFC based on intrinsic functional connectivity. We then conducted seed-based analyses to assess the functional connectivity between these clusters and the rest of the brain. The results demonstrated seven distinct functional clusters within the LFC. The functional connectivity patterns of these clusters with the rest of the brain were also found to be distinct and organized along a rostrocaudal gradient, consonant with those found in humans and macaques. Overall, these results support the view that marmosets are a promising preclinical modeling species for studying LFC dysfunction related to neuropsychiatric or neurodegenerative human brain diseases. SIGNIFICANCE STATEMENTThe common marmoset is a New World primate that has garnered recent attention as a powerful complement to canonical Old World primate (e.g., macaques) and rodent models (e.g., rats, mice) for preclinical modeling of the human brain in healthy and diseased states. A critical step in the development of marmosets for such models is to characterize functional network topologies of frontal cortex in healthy, normally functioning marmosets, that is, how these circuitries are functionally divided and how those topologies compare to human circuitry. To our knowledge, this is the first study to demonstrate functional boundaries of the lateral frontal cortex and the corresponding network topologies in marmoset monkeys.
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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 | 0.001 |
| 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".