Biology subjects

Duerden, E. G.

Publications and source records attributed to Duerden, E. G..

5 recordsLinked to original sources

bioRxiv2026

Hippocampal subfield macrostructure and myelination demonstrate distinct maturational signatures

The hippocampus is essential for learning and memory and undergoes prolonged development throughout childhood and adolescence. Evidence concerning hippocampal maturation is based primarily on volumetric measures. However, macrostructural growth and myelination processes may represent distinct biological processes. Using Hippunfold, we quantified hippocampal subfield volumes and myelin-sensitive tissue concentrations as proxies for tissue maturation using T1w/T2w ratios in 175 community-recruited participants aged 9 months to 21 years. Hippocampal subfield volumes were best described by quadratic developmental trajectories, whereas T1w/T2w ratios increased linearly with age across all subfields. Males exhibited larger hippocampal volumes, and females demonstrated higher and steeper age-related increases in T1w/T2w ratios. Sex-related hippocampal subfield differences were observed despite largely comparable cognitive and behavioural profiles. Hippocampal subfield volumes and myelin follow distinct developmental pathways, revealing sex-specific patterns of development that are not fully captured by morphology alone.

neuroscience↗

bioRxiv2026

fNIRS reveals that live social interactions and visual realism influence neural responses

The human face is central to social interactions, supporting the ability to interpret others' mental states using theory of mind (ToM). We examined whether functional near-infrared spectroscopy (fNIRS) would reveal brain-activation differences between live and pre-recorded social conversations in brain regions implicated in ToM. Furthermore, we examined whether activation depended on the visual realism of a social partner - viewed as a human or an animated avatar. By one view, social interactions may be dependent on how natural the social partner appears; by another view, social interactions may depend only upon the attribution of responses to a real human regardless of visual appearance. Neural activation for pre-recorded compared to live interactions was prolonged, consistent with extended cognitive effort. Activation patterns in the right temporoparietal junction differed between interacting with humans versus avatars, along with a stronger preference for looking at the eyes when interacting with a human (vs. avatar), underscoring the social relevance of real faces. Findings highlight the importance of both live interactions and facial realism in shaping social-cognitive processing, a finding with relevance for optimizing online social interactions.

neuroscience↗

bioRxiv2025

Longitudinal Associations Between Screen Time, Brain Development, and Language Outcomes in Early Childhood

Language development during toddlerhood is supported by both neurobiological maturation and environmental experiences. It relies on reciprocal interaction, and excessive screen time exposure may have a negative impact. In the current study, we investigated how screen time at age two relates to language outcomes and brain development at ages two and three. Seventy toddlers underwent MRI scanning and neurodevelopmental testing, and brain volumes in language-related areas were extracted. Structural equation modelling showed that at age two, there was a negative relationship between screen time and pars triangularis volumes. Importantly, smaller volumes at age two predicted greater screen time usage at age three, mediated by poorer language outcomes. These results suggest that over time, children with smaller volumes and weaker language skills at age 2 became more likely to rely on screens at age 3, suggesting that early vulnerabilities amplify later screen use, highlighting the sensitivity of language networks to environmental input and the potential for screen exposure to alter developmental trajectories.

neuroscience↗

bioRxiv2022

A radiofrequency coil for infants and toddlers

BackgroundInfants and toddlers are a challenging population on which to perform MRI of the brain, both in research and clinical settings. Due to the large range in head size during the early years of development, paediatric neuro-MRI requires a radiofrequency (RF) coil, or set of coils, that is tailored to head size to provide the highest image quality. Mitigating techniques must also be employed to reduce and correct for subject motion. ObjectiveTo develop an RF coil with a tailored mechanical-electrical design that can adapt to the head size of three-month-old infants to three-year-old toddlers. Materials and methodsAn RF coil was designed with tight-fitting coil elements to improve SNR in comparison to commercially available adult head coils, while simultaneously aiding in immobilization. The coil was designed without visual obstruction to facilitate an unimpeded view of the childs face and the potential application of camera or motion-tracking systems. ResultsDespite the lack of elements over the face, the paediatric coil produced higher SNR over most of the brain compared to adult coils, including more than 2-fold in the periphery. Acceleration rates of 4-fold in each Cartesian direction could be achieved. Higher SNR allowed for shorter acquisition times through accelerated imaging protocols, reducing the probability of motion during a scan. ConclusionModification to the acquisition protocol, with immobilization of the head through the adjustable coil geometry, and subsequently combined with a motion tracking system provides a compelling platform for scanning paediatric populations without sedation and with improved image quality.

biophysics↗

bioRxiv2022

An automated BIDS-App for brain segmentation of human fetal functional MRI data

Fetal functional magnetic resonance imaging (fMRI) offers critical insight into the developing brain and could aid in predicting developmental outcomes. As the fetal brain is surrounded by heterogeneous tissue, it is not possible to use adult- or child-based segmentation toolboxes. Manually-segmented masks can be used to extract the fetal brain; however, this comes at significant time costs. Here, we present a new BIDS App for masking fetal fMRI, funcmasker-flex, that overcomes these issues with a robust 3D convolutional neural network (U-net) architecture implemented in an extensible and transparent Snakemake workflow. Open-access fetal fMRI data with manual brain masks from 159 fetuses (1103 total volumes) were used for training and testing the U-net model. We also tested generalizability of the model using 82 locally acquired functional scans from 19 fetuses, which included over 2300 manually segmented volumes. Dice metrics were used to compare performance of funcmasker-flex to the ground truth manually segmented volumes, and segmentations were consistently robust (all Dice metrics [≥]0.74). The tool is freely available and can be applied to any BIDS dataset containing fetal bold sequences. funcmasker-flex reduces the need for manual segmentation, even when applied to novel fetal functional datasets, resulting in significant time-cost savings for performing fetal fMRI analysis.

neuroscience↗