Biology subjects

Karipidis, I. I.

Publications and source records attributed to Karipidis, I. I..

10 recordsLinked to original sources

bioRxiv2026

Highly replicable multisite patterns of adolescent white matter maturation

The Adolescent Brain Cognitive Development (ABCD) Study is the largest U.S.-based neuroimaging initiative of adolescent brain maturation. Diffusion MRI (dMRI) provides unique insights into white matter organization, yet applying advanced processing pipelines and managing technical variability across scanning environments remains challenging at scale. To address these issues, we present ABCD-BIDS Community Collection (ABCC) release 3.1.0, including a curated resource of more than 24,000 fully processed ABCD dMRI datasets. ABCC provides fully processed images, nuanced image quality metrics, advanced microstructural measures, and person-specific bundle tractography. Evaluating these rich data revealed that measures of diffusion restriction and non-Gaussianity--in particular the intracellular volume fraction from NODDI and return-to-origin probability from MAP-MRI--were highly sensitive to neurodevelopment and robust to variation in image quality. Additionally, harmonization of microstructural features markedly improved the cross-vendor generalizability of developmental effects. Together, ABCC accelerates reproducible, rigorous research on adolescent white matter development.

neuroscience↗

bioRxiv2026

Predicting children's literacy from task-based fMRI: Neural heterogeneity and task-dependent performance

Reading is a complex skill with a well-characterized neural basis. Multivariate fMRI analyses have deepened our neuroscientific understanding of literacy by linking neural patterns to behavioral traits. Although task-based fMRI often outperforms resting-state fMRI in predicting cognitive traits, few studies have applied it to continuous measures of childrens reading ability. To identify neural markers of literacy, we compared predictive performance across multiple fMRI tasks and reading-related measures. In this data-driven study, we predicted literacy skills in school-aged children (6.7-10.3 years) from eleven behavioral scores grouped into Reading (fluency and comprehension), Verbal (vocabulary knowledge and verbal intelligence), and Naming (object naming speed). Predictive performance was examined across four fMRI tasks completed by subgroups of children (n = 73-97): two active tasks - phonological-lexical decisions (PhonLex) and audiovisual character learning (Learn) - and two passive tasks - word and face viewing (Localizer) and character processing (CharProc). Individual activation contrast maps, categorized as simple (single condition) or subtractive (condition contrasts), were analyzed using a machine learning model with whole-brain predictors derived from principal component analysis. Results showed the highest predictive performance for Reading and Naming with PhonLex > Learn > Localizer = CharProc, and for Verbal with PhonLex = Learn > Localizer = CharProc. Simple contrasts generally outperformed subtractive contrasts in predicting behavioral scores. Key neural predictors, identified through whole-brain and region-of-interest analyses, included the left inferior frontal gyrus, supramarginal gyrus, ventral occipitotemporal cortex, insula, and default mode network regions. Together, these findings indicate that, for predicting literacy traits in children, active tasks and tasks that engage brain systems involved in multisensory learning tend to outperform both passive paradigms and simple subtractive task contrasts. This study provides a methodological benchmark for brain-based prediction of reading ability and highlights the value of activation heterogeneity across distributed regions as a potential marker for tracking literacy development over time.

neuroscience↗

bioRxiv2026

Relationship between X chromosome mosaicism, neuroanatomy and cognitive performance in females

Females have two X chromosomes, one of which is inactivated early in development with specific regions and genes escaping inactivation. Thus, X chromosome loss putatively results in decreased dosage of X chromosome escapee and pseudoautosomal genes, impacting downstream pathways. Evidence from Turner syndrome indicates that X chromosome monosomy results in consistent neuroanatomical and cognitive phenotypes. However, it remains unclear whether mosaic karyotypes, with mixed proportions of 45X and 46XX cells, attenuate these phenotypes. We examined whether X chromosome mosaicism is predicted by neuroanatomical and cognitive features. Higher proportion of 46XX cells was significantly predicted by structural properties in somatosensory, motor, visual, and language brain areas, and by performance in visuospatial, fine-motor, and language tasks. Thus, mosaicism partially rescues phenotypes linked to full 45X monosomy and may explain the role of the X chromosome not only across heterogeneous phenotypic expression in females, but also in sex differences observed in neuropsychiatric conditions.

neuroscience↗

bioRxiv2025

Growing Minds, Integrating Senses: Neural and Computational Insights into Age-related Changes in Audio-Visual and Tactile-Visual Learning in Children

Multisensory processing and learning shape cognitive and language development, influencing how we perceive and interact with the world from an early age. While multisensory processes mature into adolescence, it remains poorly understood how age influences multisensory associative learning. This study investigated age-related effects on multisensory processing and learning during audio-visual and tactile-visual learning in 67 children (5.7-13 years) by integrating behavioural and neuroimaging data with computational methods. A reinforcement-learning drift diffusion model revealed that older children processed information faster and made more efficient decisions on multisensory associations. These age-related increases coincided with higher activity in brain regions associated with cognitive control, multisensory integration, and memory retrieval, specifically during audio-visual learning. Notably, the bilateral anterior insula exhibited heightened activation in response to lower reward prediction errors, indicative of increased sensitivity to negative feedback with development. Finally, reward prediction errors modulated activation in reward processing and cognitive control regions, with this modulation remaining modality-independent and largely stable across age. In conclusion, while children employ similar learning strategies, older children make decisions more efficiently and engage neural resources more strongly. Our findings reflect ongoing maturation of neural networks supporting multisensory learning in middle childhood, enabling more adaptive learning in later childhood. Highlights- faster information processing in older children during a multisensory learning task - increasing brain activation with age in visual, parietal, and frontal regions - reward prediction error processing are independent of age and modality - heightened response to negative reward prediction errors with increasing age

neuroscience↗

bioRxiv2024

Assessing white matter plasticity in a randomized controlled trial of early literacy training in preschoolers

Reading is a cognitive skill that requires our brain to go through a myriad of changes during learning. While many studies have described how reading acquisition shapes childrens brain function, less is known about the impact of reading on brain structure. Here we examined short-term causal effects of reading training on preschoolers behavior and white matter structure. Forty-eight English-speaking preschoolers (4y10m to 6y2m) participated in a randomized controlled trial where they were randomly assigned to two training programs: the Letter training program was focused on key skills for reading (e.g., decoding and letter knowledge), while the Language training program strengthened oral language comprehension skills without exposure to text. Longitudinal behavioral data showed that only the Letter Training group increased letter knowledge and decoding skills after the two-week training. Diffusion MRI measures (FA and MD) of eighteen white matter pathways (including the left arcuate and the left inferior longitudinal fasciculus) did not reveal any statistically significant changes for either group despite high degrees of scan-rescan reliability across sessions. These findings suggest that a two- week reading training program can cause changes in preschoolers letter knowledge and decoding abilities, without being accompanied by measurable changes in the diffusion properties of the major white matter pathways of the reading network. We conclude highlighting possible constraints (i.e., age, training onset and duration, cognitive profile) to reading-related white matter plasticity.

neuroscience↗

bioRxiv2023

The transition from vision to language:distinct patterns of functional connectivity for sub-regions of the visual word form area

Reading entails transforming visual symbols to sound and meaning. This process depends on specialized circuitry in the visual cortex, the Visual Word Form Area (VWFA). Recent findings suggest that this word-selective cortex comprises at least two distinct subregions: the more posterior VWFA-1 is sensitive to visual features, while the more anterior VWFA-2 processes higher level language information. Here, we explore whether these two subregions exhibit different patterns of functional connectivity, and whether these patterns have relevance for reading development. We address these questions using two complementary datasets: Using the Natural Scenes Datasets (NSD; Allen et al, 2022) we identify word-selective responses in high-quality 7T individual adult data (N=8; 6 females), and investigate functional connectivity patterns of VWFA-1 and VWFA-2 at the individual level. We then turn to the Healthy Brain Network (HBN; Alexander et al., 2017) database to assess whether these patterns a) replicate in a large developmental sample (N=224; 98 females, age 5-21y), and b) are related to reading development. In both datasets, we find that VWFA-1 is more strongly correlated with bilateral visual regions including ventral occipitotemporal cortex and posterior parietal cortex. In contrast, VWFA-2 is more strongly correlated with language regions in the frontal and lateral parietal lobes, particularly bilateral inferior frontal gyrus (IFG). Critically, these patterns do not generalize to adjacent face-selective regions, suggesting a unique relationship between VWFA-2 and the frontal language network. While connectivity patterns increased with age, no correlations were observed between functional connectivity and reading ability. Together, our findings support the distinction between subregions of the VWFA, and portray the functional connectivity patterns of the reading circuitry as an intrinsic stable property of the brain.

neuroscience↗

bioRxiv2022

An open, analysis-ready, and quality controlled resource for pediatric brain white-matter research

We created resources to facilitate research on the role of human brain microstructure in the development of mental health disorders, based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N=2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI, and we provide automated quality control (QC) scores for every scan, as part of the data release. To scale QC to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers a resource for transdiagnostic research in brain connectivity and pediatric mental health and serves as a novel tool for automated QC of large datasets.

neuroscience↗

bioRxiv2021

Visual occipito-temporal sensitivity to digits through elementary school

Number processing abilities are important for academic and personal development. The course of initial specialization of ventral occipito-temporal cortex (vOTC) for visual number processing is crucial for the development of numeric and arithmetic skills. We examined the visual N1, the electrophysiological correlate of vOTC activations across five time points in kindergarten (T1), middle and end of first grade (T2, T3), second (T4) and fifth grade (T5). 62 children (35 female) performed a target detection task which included visual presentation of digits, false fonts, and letters. Arithmetic skills were measured at T4 and T5 with standardized math tests. Stronger N1 amplitudes for digits than false fonts were found across all 5 measurements. Arithmetic skills correlated negatively with visual N1 sensitivity to digits at T4 (2nd grade, mean age 8.3 yrs) over the left hemisphere, possibly reflecting allocation of more attentional or cognitive resources with poorer arithmetic skills. Our main result shows persistent visual N1 sensitivity to digits that is already present early on in pre-school and remains stable until fifth grade. This differs from the relatively sharp rise and fall of the visual N1 sensitivity to words or letters between kindergarten and middle of elementary school. The present study thus indicates different trajectories in the development of visual processing for written characters that are relevant to numeracy and literacy.

neuroscience↗

bioRxiv2021

Evaluating the reliability of human brain white matter tractometry

The validity of research results depends on the reliability of analysis methods. In recent years, there have been concerns about the validity of research that uses diffusion-weighted MRI (dMRI) to understand human brain white matter connections in vivo, in part based on reliability of the analysis methods used in this field. We defined and assessed three dimensions of reliability in dMRI-based tractometry, an analysis technique that assesses the physical properties of white matter pathways: (1) reproducibility, (2) test-retest reliability and (3) robustness. To facilitate reproducibility, we provide software that automates tractometry (https://yeatmanlab.github.io/pyAFQ). In measurements from the Human Connectome Project, as well as clinical-grade measurements, we find that tractometry has high test-retest reliability that is comparable to most standardized clinical assessment tools. We find that tractometry is also robust: showing high reliability with different choices of analysis algorithms. Taken together, our results suggest that tractometry is a reliable approach to analysis of white matter connections. The overall approach taken here both demonstrates the specific trustworthiness of tractometry analysis and outlines what researchers can do to demonstrate the reliability of computational analysis pipelines in neuroimaging.

neuroscience↗

bioRxiv2020

Measuring reading ability in the web-browser with a lexical decision task

An accurate model of the factors that contribute to individual differences in reading ability depends on data collection in large, diverse and representative samples of research participants. However, that is rarely feasible due to the constraints imposed by standardized measures of reading ability which require test administration by trained clinicians or researchers. Here we explore whether a simple, two-alternative forced choice, time limited lexical decision task (LDT), self-delivered through the web-browser, can serve as an accurate and reliable measure of reading ability. We found that performance on the LDT is highly correlated with scores on standardized measures of reading ability such as the Woodcock-Johnson Letter Word Identification test (r = 0.91, disattenuated r = 0.94). Importantly, the LDT reading ability measure is highly reliable (r = 0.97). After optimizing the list of words and pseudowords based on item response theory, we found that a short experiment with 76 trials (2-3 minutes) provides a reliable (r = 0.95) measure of reading ability. Thus, the self-administered, Rapid Online Assessment of Reading ability (ROAR) developed here overcomes the constraints of resource-intensive, in-person reading assessment, and provides an efficient and automated tool for effective online research into the mechanisms of reading (dis)ability.

animal behavior and cognition↗