Existence of Functional Connectome Fingerprint during Infancy and Its Stability over Months

Journal of Neuroscience, Journal Year: 2021, Volume and Issue: 42(3), P. 377 - 389

Published: Nov. 17, 2021

The functional connectome fingerprint is a cluster of individualized brain connectivity patterns that are capable distinguishing one individual from others. Although its existence has been demonstrated in adolescents and adults, whether such exist during infancy barely investigated despite importance identifying the origin intrinsic potentially mirror distinct behavioral phenotypes. To fill this knowledge gap, capitalizing on longitudinal high-resolution structural resting-state MRI dataset with 104 human infants (53 females) 806 scans (age, 16–876 d) infant-specific parcellation maps, we observe may since keeps stable over months early development. Specifically, achieve an ∼78% identification rate by using ∼5% selected connections, compared best 60% without connection selection. frontoparietal networks recognized as most contributive adult fingerprinting retain their superiority being widely acknowledged rapidly developing systems childhood. stability further validated adjacent age groups. Moreover, show infant can reach similar accuracy predicting learning composite scores whole-brain connectome, again resembling observations adults highlighting relevance to cognitive performance. For first time, these results suggest each unique marker SIGNIFICANCE STATEMENT Functional featuring rapid development remains almost uninvestigated even though it essential for understanding individual-level pattern organization relationship With infant-tailored selection validation strategy, strive provide delineation examining existence, stability, We 2 years. identified key connections also verified be highly predictive score prediction, which reveals association between

Language: Английский

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Profiling cortical morphometric similarity in perinatal brains: Insights from development, sex difference, and inter-individual variation

NeuroImage, Journal Year: 2024, Volume and Issue: 295, P. 120660 - 120660

Published: May 28, 2024

The topological organization of the macroscopic cortical networks are important for development complex brain functions. However, how morphometric develops during third trimester and whether it demonstrates sexual individual differences at this particular stage remain unclear. Here, we constructed similarity network (MSN) based on morphological microstructural features derived from multimodal MRI two independent cohorts (cross-sectional longitudinal) scanned 30-44 postmenstrual weeks (PMW). Sex difference inter-individual variations MSN were also examined these cohorts. cross-sectional analysis revealed that both integration segregation changed in a nonlinear biphasic trajectory, which was supported by results obtained longitudinal analysis. community structure showed remarkable consistency between bilateral hemispheres maintained stability across PMWs. Connectivity within primary cortex strengthened faster than high-order communities. Compared to females, male neonates significant reduction participation coefficient prefrontal parietal cortices, while their overall architecture remained comparable. Furthermore, using as features, achieved over 65% accuracy identifying an term-equivalent age images acquired after birth, vice versa. These findings provide comprehensive insights into throughout perinatal cortex, enhancing our understanding establishment neuroanatomical early life.

Language: Английский

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Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction

Neuropsychopharmacology, Journal Year: 2024, Volume and Issue: 50(1), P. 114 - 123

Published: Aug. 15, 2024

Language: Английский

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Network controllability of structural connectomes in the neonatal brain

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Sept. 19, 2023

Abstract White matter connectivity supports diverse cognitive demands by efficiently constraining dynamic brain activity. This efficiency can be inferred from network controllability, which represents the ease with moves between distinct mental states based on white connectivity. However, it remains unclear how networks support functions at birth, a time of rapid changes in Here, we investigate development controllability during perinatal period and effect preterm birth 521 neonates. We provide evidence that elements are exhibited infant’s as early third trimester develop rapidly across period. Preterm disrupts altered energy required to drive state transitions different levels. In addition, is associated ability 18 months. Our results suggest develops but could environmental impacts like birth.

Language: Английский

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Connectome-based biophysical models of pathological protein spreading in neurodegenerative diseases

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(1), P. e1012743 - e1012743

Published: Jan. 21, 2025

Neurodegenerative diseases are a group of disorders characterized by progressive degeneration or death neurons. The complexity clinical symptoms and irreversibility disease progression significantly affects individual lives, leading to premature mortality. prevalence neurodegenerative keeps increasing, yet the specific pathogenic mechanisms remain incompletely understood effective treatment strategies lacking. In recent years, convergent experimental evidence supports “prion-like transmission” assumption that abnormal proteins induce misfolding normal proteins, these misfolded propagate throughout neural networks cause neuronal death. To elucidate this dynamic process in vivo from computational perspective, researchers have proposed three connectome-based biophysical models simulate spread pathological proteins: Network Diffusion Model, Epidemic Spreading agent-based Susceptible-Infectious-Removed model. These demonstrated promising predictive capabilities. This review focuses on explanations their fundamental principles applications. Then, we compare strengths weaknesses models. Building upon foundation, introduce new directions for model optimization propose unified framework evaluation We expect could lower entry barrier field, accelerate optimization, thereby advance translation

Language: Английский

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The overgrowth of structure-function coupling in premature brain during infancy

Developmental Cognitive Neuroscience, Journal Year: 2025, Volume and Issue: 72, P. 101535 - 101535

Published: Feb. 21, 2025

Language: Английский

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Early Development and Co‐Evolution of Microstructural and Functional Brain Connectomes: A Multi‐Modal MRI Study in Preterm and Full‐Term Infants

Human Brain Mapping, Journal Year: 2025, Volume and Issue: 46(5)

Published: March 18, 2025

Functional networks characterized by coherent neural activity across distributed brain regions have been observed to emerge early in neurodevelopment. Synchronized maturation that relate functional connectivity (FC) could be partially reflected the developmental changes underlying microstructure. Nevertheless, covariation of regional microstructural properties, termed "microstructural connectivity" (MC), and its relationship emergence specialization during neurodevelopmental period remain poorly understood. We investigated evolution MC FC postnatally a set cortical subcortical regions, focusing on 45 preterm infants scanned longitudinally, compared matched full-term neonates as part developing Human Connectome Project (dHCP) using direct comparisons grey-matter strengths well network-based analyses. Our findings revealed global strengthening both with age, connection-specific variability influenced connection maturational stage. Prematurity at term-equivalent age was associated significant disruptions, particularly FC. During period, strength showed positive linear relationship, which seemed weaken development. On other hand, overlaps between MC- FC-derived (estimated Mutual Information) increased suggesting potential convergence towards shared network structure may support co-evolution systems. study offers novel insights into dynamic interplay development highlights complementary descriptor for characterizing alterations due perinatal insults such premature birth.

Language: Английский

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Revealing morphological fingerprints in perinatal brains using quasi-conformal mapping: occurrence and neurodevelopmental implications

Brain Imaging and Behavior, Journal Year: 2025, Volume and Issue: unknown

Published: March 27, 2025

Language: Английский

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Toward a more informative representation of the fetal–neonatal brain connectome using variational autoencoder

eLife, Journal Year: 2023, Volume and Issue: 12

Published: May 15, 2023

Recent advances in functional magnetic resonance imaging (fMRI) have helped elucidate previously inaccessible trajectories of early-life prenatal and neonatal brain development. To date, the interpretation fetal–neonatal fMRI data has relied on linear analytic models, akin to adult neuroimaging data. However, unlike brain, fetal newborn develops extraordinarily rapidly, far outpacing any other development period across life span. Consequently, conventional computational models may not adequately capture these accelerated complex neurodevelopmental during this critical along prenatal-neonatal continuum. obtain a nuanced understanding development, including nonlinear growth, for first time, we developed quantitative, systems-wide representations activity large sample (>500) fetuses, preterm, full-term neonates using an unsupervised deep generative model called variational autoencoder (VAE), shown be superior representing resting-state healthy adults. Here, demonstrated that features, is, latent variables, derived with VAE pretrained rsfMRI human adults, carried important individual neural signatures, leading improved representation maturational patterns more accurate stable age prediction neonate cohort compared models. Using decoder, also revealed distinct networks spanning sensory default mode networks. VAE, are able reliably quantify complex, connectivity. This will lay foundation detailed mapping aberrant signatures their origins life.

Language: Английский

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Separating Group- and Individual-level Brain Signatures in the Newborn Functional Connectome: A Deep Learning Approach

NeuroImage, Journal Year: 2024, Volume and Issue: 299, P. 120806 - 120806

Published: Aug. 23, 2024

Recent studies indicate that differences in cognition among individuals may be partially attributed to unique brain wiring patterns. While functional connectivity (FC)-based fingerprinting has demonstrated high accuracy identifying adults, early on neonates suggest individualized FC signatures are absent. We posit individual uniqueness is present neonatal data and conventional linear models fail capture the rapid developmental trajectories characteristic of newborn brains. To explore this hypothesis, we employed a deep generative model, known as variational autoencoder (VAE), leveraging two extensive public datasets: one comprising resting-state MRI (rs-fMRI) scans from 100 adults other 464 neonates. VAE trained rs-fMRI both newborns produced superior age prediction performance (with r between predicted- actual ∼ 0.7) identification (∼45 %) compared solely adult or data. The model also showed significantly higher than (=10∼30 %). Importantly, differentiated connections reflecting age-related changes those indicative uniqueness, distinction not possible with models. Moreover, derived 20 latent variables, each corresponding distinct patterns cortical network (CFNs). These CFNs varied their representation maturation signatures; notably, certain failed neurodevelopmental traits, fact, exhibited signatures. associated neurodevelopment predominantly encompassed unimodal regions such visual sensorimotor areas, whereas linked spanned multimodal transmodal regions. VAE's capacity extract features beyond capabilities positions it valuable tool for delineating cognitive traits inherent exploring imaging phenotypes.

Language: Английский

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