Biology subjects

Dierker, D.

Publications and source records attributed to Dierker, D..

4 recordsLinked to original sources

bioRxiv2025

Comparative Evaluation of Assumption Lean Community Detection Methods for Human Connectome Networks

Community detection on resting-state functional connectivity provides a principled lens on mesoscale organization in functional brain networks. Currently, the choice of community count K, lacks a standardized or principled guideline. We conducted a systematic benchmark of three assumption-lean approaches on weighted functional connectivity matrices: the Weighted Stochastic Block Model, Spectral Clustering, and K-means Clustering. Performance was assessed on synthetic networks with known ground truth and on three neuroimaging cohorts which included adult and infant datasets. We compared several strategies for selecting K, including the silhouette index and other approaches commonly used in the existing literature. These were evaluated alongside a likelihood-based criterion for the weighted stochastic block model that employs bootstrap confidence intervals for differences in log-likelihood between successive values of K. For the synthetic networks, WSBM and Spectral Clustering correctly identified the true number of communities, whereas K-means Clustering did not. In adult datasets, most indices did not yield a unique optimum, whereas the likelihood-based criterion selected K = 11, which is consistent with established sensory and association systems. In infants and toddlers, the same procedure supports a larger K around 15 and reveals developmentally distinct mesoscale architecture, including anterior and posterior subdivisions within default mode and fronto parietal systems.

neuroscience↗

bioRxiv2025

Commonality and Variability in Functional Networks In Young Children Under 5 Years Old

Functional brain networks support human cognition, yet how individualized network architecture emerges in early childhood remains poorly understood. Averaging across participants can obscure age-specific organization and person-to-person differences, particularly in slowly developing association cortices. We developed an age-appropriate functional reference that captured common structure across toddlers without averaging away individual variability, enabling estimation of each childs networks from resting-state fMRI. Across cohorts of 8-60-month-old children, we found individualized network organization--including finer-scale subdivisions and emerging language lateralization--well before age five. Network layouts showed longitudinal stability, with greater consistency in sensory than association regions. Within-network connectivity was stronger and explained age-related variance when networks were defined using individualized rather than group-consensus topography. Left-lateralization of language networks tracked age-normalized verbal ability, linking early functional architecture to emerging cognition. These findings show that behaviorally relevant brain networks arise far earlier than previously recognized, providing a foundation for studying typical development and early biomarkers.

neuroscience↗

bioRxiv2024

Early Life Neuroimaging: The Generalizability of Cortical Area Parcellations Across Development

The cerebral cortex consists of distinct areas that develop through intrinsic embryonic patterning and postnatal experiences. Accurate parcellation of these areas in neuroimaging studies improves statistical power and cross-study comparability. Given significant brain changes in volume, microstructure, and connectivity during early life, we hypothesized that cortical areas in 1- to 3-year-olds would differ markedly from neonates and increasingly resemble adult patterns as development progresses. Here, we parcellated the cerebral cortex into putative areas using local functional connectivity gradients in 92 toddlers at 2 years old. We demonstrate high reproducibility of these cortical regions across 1- to 3-year-olds in two independent datasets. The area boundaries in 1- to 3-year-olds were more similar to those in adults than those in neonates. While the age-specific group area parcellation better fit the underlying functional connectivity in individuals during the first 3 years, adult area parcellations might still have some utility in developmental studies, especially in children older than 6 years. Additionally, we provide connectivity-based community assignments of the parcels, showing fragmented anterior and posterior components based on the strongest connectivity, yet alignment with adult systems when weaker connectivity was included.

neuroscience↗

bioRxiv2024

A subset of brain regions within adult functional connectivity networks demonstrate high reliability across early development

The human cerebral cortex contains groups of areas that support sensory, motor, cognitive, and affective functions, often categorized into functional networks. These networks show stronger internal and weaker external functional connectivity (FC), with FC profiles more similar within the same network. Previous studies have shown these networks develop from nascent forms before birth to their mature, adult-like structures in childhood. However, these analyses often rely on adult functional network definitions. This study assesses the potential misidentification of infant functional networks when using adult models and explores the consequences and possible solutions to this problem. Our findings suggest that although adult networks only marginally describe infant FC organization better than chance, misidentification is primarily driven by specific areas. Restricting functional networks to areas with adult-like network clustering revealed consistent within-network FC across scans and throughout development. These areas are also near locations with low network identity variability. Our results highlight the implications of using adult networks for infants and offer guidance for selecting and utilizing functional network models based on research questions and scenarios. HighlightsO_LIPrevious studies primarily investigated age-specific networks in infants, with limited focus on how well adult networks describe infant functional connectivity (FC). C_LIO_LIur analysis identified a subset of areas in infants showing adult-like network organization, where within-network FC shows less age-related variation and higher scan-to-scan reliability. C_LIO_LIThese areas are positioned near locations with low variability in functional network identity in adults, indicating a potential link between developmental sequence and interindividual variability in functional network organization. C_LI

neuroscience↗