Functional networks in the infant brain during sleep and wake states
Bibliographic record
Abstract
Abstract Functional brain networks are assessed differently early in development than at maturity: infants are almost universally scanned during sleep, whereas adults are typically scanned awake while resting or performing tasks. Observed differences between infant and adult functional networks may thus reflect these differing states of consciousness rather than or in addition to developmental changes. We explore this question by comparing functional networks in fMRI scans acquired from infants during natural sleep and awake movie-watching. As a reference, we also acquired fMRI scans in adults during awake rest and awake movie-watching. Whole-brain functional connectivity was more similar within-state (sleep-sleep, wake-wake) than across-state (sleep-wake) in infants, demonstrating that movies elicit a different network configuration than typical sleep acquisitions. Indeed, a classifier trained on patterns of functional connectivity during infant sleep versus wake robustly decoded the state of additional infants and even generalized to decode rest versus movie in adults; interestingly, a classifier trained on rest versus movie in adults did not generalize nearly as well to sleep versus wake in infants. Moreover, the overall level of similarity between infant and adult functional connectivity was modulated by adult state (stronger for movie than rest) but not infant state (equivalent for sleep and wake). Nevertheless, the network connections that drove similarity between infants and adults, particularly in frontoparietal network, were modulated by infant state. In sum, infant functional connectivity can differ between sleep and wake states, highlighting the potential value of awake data for studying the early development of functional brain networks. Significance statement Functional networks in the infant brain provide a foundation for early cognitive abilities and act as a marker of brain maturation and developmental disorders. What we know about these networks comes from fMRI data acquired during sleep, given the challenges of awake infant fMRI. This contrasts with the dominant approach in older populations of assessing networks during awake rest or tasks. These differing levels of consciousness cloud the interpretation of developmental changes. Here we show that whole-brain functional connectivity differs between sleeping and awake infants, and that the similarity of these infant states to adults loads on dissociable network connections. This research suggests that a full understanding of early functional brain networks will benefit from complementary insights in awake infants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".