Biology subjects

Anwander, A.

Publications and source records attributed to Anwander, A..

14 recordsLinked to original sources

bioRxiv2026

Nucleus-level thalamic organization anchors multimodal signatures of thalamocortical maturation

The human thalamus is composed of multiple nuclei that differ in structure and function. From early development onwards, these nuclei form reciprocal, nucleus-specific connections with the cerebral cortex, contributing to sensory and cognitive processing. In childhood and adolescence, a key period of neurocognitive development, these connections undergo widespread refinement, yet how developmental trajectories of thalamocortical connections vary across nuclei remains unknown. Here, we leveraged the Human Connectome Project in Development dataset (HCP-D, N = 604, age range 8-21) and segmented 10 thalamic nuclei using a segmentation approach optimized for intrathalamic contrast. Applying probabilistic tractography, we reconstructed nucleus-specific thalamocortical connections and charted their maturational profiles based on changes in fractional anisotropy (FA) using generalized additive models. We found FA to increase in thalamocortical connections, with nucleus-specific variation in temporal profiles and magnitude of age effects. Connections of core-cell-rich, sensory-projecting nuclei, such as the lateral geniculate nucleus, showed earlier maturational plateaus, whereas matrix-cell-rich, association-projecting nuclei, such as ventral anterior nucleus, showed more sustained maturation. This links maturational heterochronicity to thalamic organization of cell distribution and connectivity embedding. In parallel, functional thalamocortical connectivity decreased with age, with FA and functional connectivity age effects coupled in nucleus-connections showing prolonged maturation. Finally, concordant age effects in connectivity and nucleus volumes suggest that intra-nucleus remodeling may support refinement of structural connections while reducing thalamocortical functional synchrony. Together, our work reveals that thalamocortical maturation is anchored in the developmental and organizational heterogeneity of thalamic nuclei, offering a framework for understanding how diverse thalamic nuclei contribute to neurocognitive development.

neuroscience↗

bioRxiv2025

Retinal nerve fibre layer thickness reflects characteristics of brain grey and white matter

The retina is a relatively accessible part of the central nervous system compared to the brain. Using high resolution optical imaging we investigated the relationship between retinal thickness, obtained with optical coherence tomography, and structural features of the brain obtained with magnetic resonance imaging. In a population-based sample of over 500 subjects, we hypothesized: (i) that there are structural associations between circumpapillary retinal nerve fibre layer thickness and brain grey matter density and white matter microstructural properties in visual information processing areas, and specifically contralateral associations for nasal retinal fibers, and (ii) that retinal findings reflect broader changes in brain grey and white matter related to cardiovascular risk factors. In support of the first hypothesis, we showed associations of circumpapillary retinal nerve fibre layer thickness with visual cortex grey matter density and with optic radiation fractional anisotropy. These correlations were stronger for the right eye, possibly reflecting right ocular dominancy. Regarding the second hypothesis, while we confirmed the broad impact of cardiovascular risk factors such as body mass index, diabetes, and hypertension on brain structure, we didnt find (adequate) significant partial correlations between circumpapillary retinal nerve fibre layer thickness and cardiovascular risk factors to support the hypothesis. As such, we couldnt confirm that circumpapillary retinal nerve fibre layer thickness is associated with the impact of cardiovascular risk factors on the brain structure. However, when the effects of cardiovascular risk factors were accounted for statistically, circumpapillary retinal nerve fibre layer thickness (particularly on the right side) was associated with fractional anisotropy of limbic system tracts, i.e., the fornix and stria terminalis including hippocampus and amygdala. To further explore the structural associations between eye and brain, in terms of a possible common underlying pathology related to cardiovascular risk factors and progressive neurodegenerative diseases on the central nervous system, longitudinal and interventional studies are necessary.

neuroscience↗

bioRxiv2024

Lifespan trajectory of chimpanzee brains characterized by magnetic resonance imaging histology

Chimpanzee brain maturation provides an invaluable framework for understanding the evolution of the human brain. We performed ultra-high resolution quantitative magnetic resonance imaging (qMRI) with histological validation on post mortem brains from captive and wild chimpanzees with a broad age range. We mapped developmental myelination and age-related iron accumulation across regions and layers of the neocortex. Compared to humans, chimpanzees showed more myelination and iron deposition in motor and premotor cortices, while the auditory cortex was more strongly myelinated in humans. Our model suggests that chimpanzees cortical myelination was largely completed by the age of nine years, while iron accumulation continued throughout the lifespan. The regions with highest adult levels of myelin and iron took the longest to mature, challenging the widespread assumption that highly myelinated regions complete their development first. The reported maps and developmental curves provide a foundation for comparative neuroscience research and understanding of human brain evolution.

neuroscience↗

bioRxiv2023

White matter plasticity during second language learning within and across hemispheres

Adult second language (L2) learning is a challenging enterprise inducing neuroplastic changes in the human brain. However, it remains unclear how the structural language connectome and its subnetworks change during adult L2-learning. The current study investigated longitudinal changes in white matter (WM) language networks in each hemisphere, as well as their interconnection, in a large group of Arabic-speaking adults who learned German intensively for six months. We found a significant increase in WM-connectivity within bilateral temporal-parietal semantic and phonological subnetworks and right temporal-frontal pathways mainly in the second half of the learning period. At the same time, WM-connectivity between the two hemispheres decreased significantly. Crucially, these changes in WM-connectivity are correlated with L2 performance. The observed changes in subnetworks of the two hemispheres suggest a network reconfiguration due to lexical learning. The reduced interhemispheric connectivity may indicate a key role of the corpus callosum in L2-learning by reducing the inhibition of the language-dominant left hemisphere. Our study highlights the dynamic changes within and across hemispheres in adult language-related networks driven by L2 learning. SignificanceThe neuroplastic changes induced by learning a second language (L2) in adulthood open up new perspectives for understanding brain function. The current study shows structural changes in the language network of Arabic native speakers who learned German intensively in two phases of three months each. We found a marked change in the left-hemispheric lexical-semantic language system and the right fronto-temporal pathway, accompanied by a decrease in white matter connectivity in the corpus callosum during L2 learning, which occurred mainly in the second period of L2 acquisition. The reduced interhemispheric connectivity suggests that the inhibitory role of the corpus callosum, relevant for native language processing, is reduced by L2 learning. Our findings demonstrate a clear experience-dependent structural plasticity in the human brain during L2 learning.

neuroscience↗

bioRxiv2023

Uncovering the Morphological Evolution of Language-Relevant Brain Areas

Human language is supported by a cortical network involving Brocas area which comprises Brodmann Areas 44 and 45 (BA44, BA45). While cytoarchitectonic homolog areas have been identified in nonhuman primates, it remains unknown how these regions evolved to support human language. Here, we use histological data and advanced cortical registration methods to precisely compare the morphology of BA44 and 45 between humans and chimpanzees. We found a general expansion of Brocas areas in humans, with the left BA44 enlarging the most, growing anteriorly into a region known to process syntax. Together with recent functional studies, our findings show that BA44 evolved from a purely action-related region to a more expanded region in humans, with a posterior portion supporting action and an anterior portion supporting syntactic processes. Furthermore, our findings provide a solution for the longstanding debate concerning the structural and functional evolution of Brocas area and its role in action and language.

neuroscience↗

bioRxiv2022

Native language leaves distinctive traces in brain connections

The worlds languages differ substantially in their sounds, grammatical rules, and expression of semantic relations. While starting from a shared neural substrate, the developing brain must therefore have the plasticity to accommodate to the specific processing needs of each language. However, there is little research on how language-specific differences impacts brain function and structure. Here, we show that speaking typologically different languages leaves unique traces in the brains white matter connections of monolingual speakers of English (fixed word order language), German (with grammatical marking), and Chinese (tonal language). Using machine learning, we classified with high accuracy the mother tongue based on the participants patterns of structural connectivity obtained with probabilistic tractography. More importantly, connectivity differences between groups could be traced back to relevant processing characteristics of each native tongue. Our results show that the life-long use of a certain language leaves distinct traces in a speakers neural network.

neuroscience↗

bioRxiv2022

Assessing Quantitative MRI Techniques using Multimodal Comparisons

The study of brain structure and change in neuroscience is commonly conducted using macroscopic morphological measures of the brain such as regional volume or cortical thickness, providing little insight into the microstructure and physiology of the brain. In contrast, quantitative MRI allows the monitoring of microscopic brain change non-invasively in-vivo, and provides normative values for comparisons between tissues, regions, and individuals. To support the development and common use of qMRI for cognitive neuroscience, we analysed a set of qMRI metrics (R1, R2*, Magnetization Transfer saturation, Proton Density saturation, Fractional Anisotropy, Mean Diffusivity) in 101 healthy young adults. Here we provide a comprehensive descriptive analysis of these metrics and their linear relationships to each other in grey and white matter to develop a more complete understanding of the relationship to tissue microstructure. Furthermore, we provide evidence that combinations of metrics may uncover informative gradients across the brain by showing that lower variance components of PCA may be used to identify cortical gradients otherwise hidden within individual metrics. We discuss these results within the context of microstructural and physiological neuroscience research.

neuroscience↗

bioRxiv2022

White Matter Brain Structure Predicts Language Performance and Learning Success

Individual differences in the ability to deal with language have long been discussed. The neural basis of these, however, is yet unknown. Here we investigated the relationship between long-range white matter connectivity of the brain, as revealed by diffusion tractography, and the ability to process syntactically complex sentences in the participants native language as well as the improvement thereof by multi-day training. We identified specific network motifs that indeed related white matter tractography to individual language processing performance. First, for two such motifs, one in the left and one in the right hemisphere, their individual prevalence significantly predicted the individual language performance suggesting a predisposition for the individual ability to process syntactically complex sentences, which manifests itself in the white matter brain structure. Both motifs comprise a number of cortical regions, but seem to be dominated by areas known for the involvement in working memory rather than the classical language network itself. Second, we identified another left hemispheric network motif, whose change of prevalence over the training period significantly correlated with the individual change in performance, thus reflecting training induced white matter plasticity. This motif comprises diverse cortical areas including regions known for their involvement in language processing, working memory and motor functions. The present findings suggest that individual differences in language processing and learning can be explained, in part, by individual differences in the brains white matter structure. Brain structure may be a crucial factor to be considered when discussing variations in human cognitive performance, more generally.

neuroscience↗

bioRxiv2021

Structural brain connectivity in children with developmental dyscalculia

Developmental dyscalculia (DD) is a neurodevelopmental disorder specific to arithmetic learning even with normal intelligence and age-appropriate education. Difficulties often persist from childhood through adulthood. Underlying neurobiological mechanisms of DD, however, are poorly understood. This study aimed to identify possible structural connectivity alterations in DD. We evaluated 10 children with pure DD (11.3 {+/-} 0.7 years) and 16 typically developing (TD) peers (11.2 {+/-} 0.6 years) using diffusion tensor imaging. We first assessed white matter microstructure with tract-based spatial statistics. Then we used probabilistic tractography to evaluate tract lengths and probabilistic connectivity maps in specific regions. At whole brain level, we found no significant microstructural differences in white matter between children with DD and TD peers. Also, seed-based connectivity probabilities did not differ between groups. However, we did find significant differences in regions-of-interest tracts which had previously been related to math ability in children. The major findings of our study were reduced white matter coherence and shorter tract lengths of the left superior longitudinal/arcuate fasciculus and left anterior thalamic radiation in the DD group. Furthermore, lower white matter coherence and shorter pathways corresponded with the lower math performance as a result of the correlation analyses. These results from regional analyses indicate that learning, memory and language-related pathways in the left hemisphere might underlie DD.

neuroscience↗

bioRxiv2021

Temporo-cerebellar connectivity underlies timing constraints in audition

The flexible and efficient adaptation to dynamic, rapid changes in the auditory environment likely involves generating and updating of internal models. Such models arguably exploit connections between the neocortex and the cerebellum, supporting proactive adaptation. Here we test the functional mechanisms associated with temporo-cerebellar connectivity, verifying these mechanisms for speech sounds. First, we identify lesion-specific deficits for the encoding of short timescale spectro-temporal non-speech and speech properties in patients with left posterior temporal cortex stroke. Second, using lesion-guided probabilistic tractography in healthy participants, we reveal bidirectional temporo-cerebellar connectivity with cerebellar dentate nuclei and crura I/II. These findings imply that the encoding and modeling of rapidly modulated auditory spectro-temporal properties engage a temporo-cerebellar interface. The data further support the conjecture that proactive adaptation to a dynamic environment via internal models is a generalizable principle. Significance StatementAsymmetric sampling in time, the principle of duration-sensitive hemispheric specialization of the cerebral cortex in the sensory decomposition of sound, is a widely tested hypothesis in auditory neuroscience. This functional organization is mirrored in the cerebellar cortex, implicated in the internal forward-modeling of sensory feedback that arises from motor actions. The potential structural and functional integration of these systems is not well understood. Using a unique combination of causal lesion-symptom mapping in persons with temporal lobe damage and diffusion-weighted magnetic resonance neuroimaging in healthy persons, we identify one key missing link and provide evidence for cross-lateral temporo-cerebellar connectivity using probabilistic white matter fiber tractography. These cerebellar-pontine-temporal cortex connections not only support asymmetric sampling in time but also establish the basis for a generalizable role of cerebellar forward-modeling in sensation beyond the monitoring of sensory feedback in the motor domain.

neuroscience↗

bioRxiv2020

Axon Diameter Measurements using Diffusion MRI are Infeasible

The feasibility of non-invasive axonal diameter quantification with diffusion MRI is a strongly debated topic due to the neuroscientific potential of such information and its relevance for the axonal signal transmission speed. It has been shown that under ideal conditions, the minimal diameter producing detectable signal decay is bigger than most human axons in the brain, even using the strongest currently available MRI systems. We show that resolving the simplest situations including multiple diameters is unfeasible even with diameters much bigger than the diameter limit. Additionally, the recently proposed effective diameter resulting from fitting a single value over a distribution is almost exclusively influenced by the biggest axons. We show how impractical this metric is for comparing different distributions. Overall, axon diameters currently cannot be quantified by diffusion MRI in any relevant way.

biophysics↗

bioRxiv2020

Mapping the Human Visual Thalamus and its Cytoarchitectonic Subdivisions Using Quantitative MRI

The human lateral geniculate nucleus (LGN) of the visual thalamus is a key subcortical processing site for visual information analysis. A non-invasive assessment of the LGN and its functionally and microstructurally distinct magnocellular (M) and parvocellular (P) subdivisions in-vivo in humans is challenging, because of its small size and location deep inside the brain. Here we tested whether recent advances in high-field structural quantitative MRI (qMRI) can enable MR-based mapping of human LGN subdivisions. We employed ultra-high resolution 7 Tesla qMRI of a post-mortem human LGN specimen and high-resolution 7 Tesla in-vivo qMRI in a large participant sample. We found that a quantitative assessment of the LGN and a differentiation of its subdivisions was possible based on microstructure-informed MR-contrast alone. In both the post-mortem and in-vivo qMRI data, we identified two components of shorter and longer longitudinal relaxation time (T1) within the LGN that coincided with the known anatomical locations of a dorsal P and a ventral M subdivision, respectively. Through a subsequent ground truth histological examination of the same post-mortem LGN specimen, we showed that the observed T1 contrast pertains to cyto- and myeloarchitectonic differences between LGN subdivisions. These differences were based on cell and myelin density, but not on iron content. Our qMRI-based mapping strategy overcomes shortcomings of previous fMRI-based mapping approaches. It paves the way for an in-depth understanding of the function and microstructure of the LGN in humans. It also enables investigations into the selective contributions of LGN subdivisions to human behavior in health and disease. Significance StatementThe lateral geniculate nucleus (LGN) is a key processing site for the analysis of visual information. Due to its small size and deep location within the brain, non-invasive mapping of the LGN and its microstructurally distinct subdivisions in humans is challenging. Using quantitative MRI methods that are sensitive to underlying microstructural tissue features, we show that a differentiation of the LGN and its microstructurally distinct subdivisions is feasible in humans non-invasively. These findings are important because they open up novel opportunities to assess the hitherto poorly understood complex role of the LGN in human perception and cognition, as well as the contribution of selective LGN subdivision impairments to various clinical conditions including developmental dyslexia, glaucoma and multiple sclerosis.

neuroscience↗

bioRxiv2020

Bridging the Gap: From Neuroanatomical Knowledge to Tractography of Brain Pathways

Despite recent advances in tractography, the gap remains wide between the descriptions of white-matter pathways in the literature and the methods to reconstruct and study them from dMRI images. Here, we tackle this challenge by proposing a language to define white matter tracts, namely WMQLT, and a tool to automatically reconstruct pathways from their WMQLT queries. Our method is performant, flexible enough to allow defining tracts using multiple modalities, and allows to extend ROI-based reconstruction methods. Leveraging our language, we define 19 major brain tracts, alongside their subdivisions, and reconstruct them in a large population. We show that the shape of the reconstructed pathways, as well as their connectivity and lateralizations are in accordance with the current neuroanatomical literature. Finally, we showcase our technique in two scenarios: computing the functional subdivisions of a tract, and assessing the role of handedness and gender in the lateralization of language-related tracts.

neuroscience↗

bioRxiv2020

Increased Sensitivity and Signal-to-Noise Ratio in Diffusion-Weighted MRI using Multi-Echo Acquisitions

Post-mortem diffusion MRI (dMRI) enables acquisitions of structural imaging data with otherwise unreachable resolutions - at the expense of longer scanning times. These data are typically acquired using highly segmented image acquisition strategies, thereby resulting in an incomplete signal decay before the MRI encoding continues. Especially in dMRI, with low signal intensities and lengthy contrast encoding, such temporal inefficiency translates into reduced image quality and longer scanning times. This study introduces Multi Echo (ME) acquisitions to dMRI on a human MRI system - a time-efficient approach, which increases SNR (Signal-to-Noise Ratio) and reduces noise bias for dMRI images. The benefit of the introduced ME dMRI method was validated using numerical Monte Carlo simulations and showcased on a post-mortem brain of a wild chimpanzee. The proposed Maximum Likelihood Estimation echo combination results in an optimal SNR without detectable signal bias. The combined strategy comes at a small price in scanning time (here 30% additional) and leads to a substantial SNR increase (here up to 1.9x which is equivalent to 3.6 averages) and a general reduction of the noise bias.

neuroscience↗