bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.08.27.608544

Developmental trajectory of thalamus topography during the late preterm and perinatal period in normal development, after premature birth and in congenital heart defects

Ji, H.·Wu, Z.·Speckert, A.·Tuura, R.·Hagmann, C.·Latal, B.·Knirsch, W.·Jakab, A.
View original source ↗Export metadata ↓

Abstract

The thalamus plays a critical role in neural circuit maturation and brain connectivity. It is well known to show a characteristic topographical organization of local and long-range connectivity, yet developmental changes in this topography remains incompletely understood. Our study aims to first validate the use of diffusion MRI for the topographic delineation of thalamic subdivisions (nuclei), to characterize thalamic topography during development and assess the impact of congenital heart defects (CHD) on thalamus development. We used local fiber orientation distribution functions, derived from diffusion MRI (dMRI) data, to subdivide the thalamus into seven clusters. We first evaluated the within-subject reproducibility of a dMRI based clustering method across 30 adults scan-rescan datasets (n = 30) using K-means clustering, achieving reproducible segmentation of the thalamus into seven parts. This was applied to a large developmental cohort comprising normally developing infants from the term-born dHCP cohort (n = 68, gestational age [GW] at MRI scan ranging from 37.4 to 44.8 weeks, mean {+/-} SD: 41.4 {+/-} 2.1 weeks) and the Zurich cohort (n = 42, GW at MRI ranging from 39.0 to 48.7 weeks, mean {+/-} SD: 42.55 {+/-} 1.96 weeks). The cohort also included preterm-born dHCP cohort (n = 48, GW at MRI scan ranging from 29.3 to 37.4 corrected gestational weeks, mean {+/-} SD: 34.4 {+/-} 2.02 weeks) and one case of a postmortem fetal specimen (n = 1, GW at MRI = 21 weeks). Cluster volumes were analyzed as a function of age using multivariate linear regression. Differences in cluster volumes between control subjects (n = 42, GW at MRI ranging from 39.0 to 48.7 weeks, mean {+/-} SD: 42.55 {+/-} 1.96 weeks) and newborns with congenital heart disease (CHD) (n = 49, GW at MRI ranging from 37.6 to 42.9 weeks, mean {+/-} SD: 40.23 {+/-} 1.30 weeks) were analyzed using variance analysis, controlling for sex and age at MRI scan. The clustering on average had a within-subject overlap of 0.811 (Dice overlap metric). While absolute thalamus volumes increased with age, their relative volumes remained stable in the studied developmental period. CHD infants shown reduced absolute volumes in six of the seven thalamic nuclei, with significant increasing in the relative volume of the cluster overlapping with the mediodorsal nucleus. While the perinatal period comprises rapid developmental events including the maturation of white matter, the topography of thalamic circuitry remains stable. Our study highlights alterations in thalamic topology and potential impacts on brain connectivity in CHD infants. By leveraging local diffusion properties from diffusion MRI, our validated segmentation technique offers a robust, data-centric approach to thalamic delineation.

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ji, H., Wu, Z., Speckert, A., Tuura, R., Hagmann, C., Latal, B., Knirsch, W., Jakab, A.. 2024-08-28. Developmental trajectory of thalamus topography during the late preterm and perinatal period in normal development, after premature birth and in congenital heart defects. https://doi.org/10.1101/2024.08.27.608544

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Attention Across Scales: From Individual Variation to Social Hierarchies and Brain Networks in Semi-Free-Ranging Macaques

Attention is a fundamental brain function supporting perception, decision-making, and social behavior, and its dysfunction profoundly impairs daily life. It is both dynamic and stable, varying across observations and individuals, changing across the lifespan, and being shaped by social and environmental experience. Yet capturing this complexity remains a central challenge in neuroscience. Here, we integrated longitudinal behavioral assessments of semi-free-ranging macaques living in naturalistic social groups with resting-state fMRI. We quantified performance across days, ages, and social hierarchies and related it to intrinsic brain organization. Distinct attentional phenotypes emerged, including individuals with reduced attentional control. Performance followed an inverted-U lifespan trajectory, improving from childhood to adulthood before declining. Social status modulated attentional performance. Critically, nonlinear lifespan trajectories and associations with individual attentional differences were most clearly expressed in frontoparietal connectivity. Together, these findings reveal how sustained attention is organized across scales, providing a biological framework for its individual diversity, social modulation, and neural basis.

neuroscience↗
bioRxiv2026

Decoding natural scenes from patterned optogenetic responses in mouse visual cortex

A central challenge in developing visual cortical prostheses is to determine how visual stimuli should be transformed into effective patterns of cortical stimulation. Although advances in stimulation technologies, including optogenetics, provide increasingly precise control over cortical activity, it remains unclear whether artificially evoked activity can reproduce the information content of naturally evoked visual representations. Here we establish a quantitative framework for evaluating visual encoding strategies by decoding cortical responses evoked by natural vision and patterned optogenetic stimulation. We developed a novel dual-modal paradigm in awake mice to bridge the gap between endogenous photostimulation and artificial network driving. By co-expressing the high-performance calcium indicator GCaMP6s and the red-shifted, ultra-sensitive opsin rsChRmine-oScarlet in the primary visual cortex (V1), we successfully translated dynamic natural movie frames into patterned, spatiotemporal optogenetic stimulation. Quantitative comparisons of macro-scale dynamics demonstrated that this patterned optogenetic injection evokes cortical states highly comparable and representationally aligned with those driven by actual visual photostimulation. To systematically evaluate the fidelity of these responses, we developed STAR, a deep learning model featuring spatial and temporal attention mechanisms, and successfully reconstructed the frames of natural movies from V1 signals under both experimental modalities. Collectively, our results demonstrate that complex sensory information can be both naturally encoded and synthetically injected into V1 circuits with high decoding fidelity. This work provides an empirical and computational proof-of-concept for intelligent, closed-loop biomimetic encoders, establishing a robust framework for next-generation cortical visual neuroprostheses and bidirectional brain-machine interfaces.

neuroscience↗
bioRxiv2026

Why Is Spontaneous Blink Timing Informative? An Adaptive Scheduling Perspective

Spontaneous eye blinks have long been linked to cognitive processing, yet how task demands shape blink timing and its relationship to behavioral performance remains unclear. We examined spontaneous blink behavior in 576 adults performing two variants of the Continuous Performance Task (CPT). Blink occurrence and timing were most strongly modulated by the experimental condition in the more demanding CPT-AX task, whereas their association with response time was stronger in the CPT-X task, where more consistent blink timing predicted faster responses. This dissociation suggests that task structure changes not only blink behavior but also the behavioral relevance of blink timing. These findings are consistent with an adaptive scheduling account of spontaneous blinking and provide a conceptual framework for understanding when and why blink timing contains chronometric information about ongoing cognition.

neuroscience↗