Biology subjects

Moraczewski, D.

Publications and source records attributed to Moraczewski, D..

8 recordsLinked to original sources

bioRxiv2026

Sex Differences in Human Subcortical Anatomy are Robust and Replicable in Adulthood, Already Evident Prepubertally, and Aligned with Sex Chromosomal and Gonadal Influences

The existence and mechanistic bases of sex effects on human subcortical anatomy remain unclear. To address these gaps, we combined structural neuroimaging of sex differences in subcortical volume and shape across three independent cohorts (combined N=2,886) with neuroimaging maps of sex chromosomal and endocrine effects from three clinical cohorts (combined N=313, including sex chromosome aneuploidies and isolated gonadotropin-releasing hormone deficiency). We found that human subcortical anatomy shows focal sex differences of moderate-strong effect size during young adulthood (male-biased surface area overlying lateral/ventral putamen and pallidum, nucleus accumbens, ventral posterior complex of thalamus, anterior hippocampus, and medial and central nuclei of amygdala; female-biased surface area overlying caudate head, posterior/dorsal pallidum, mediodorsal, lateral dorsal, lateral geniculate, and medial geniculate nuclei of thalamus, posterior hippocampus, and basolateral and lateral nuclei of amygdala). These regional sex differences show strong within-sample reproducibility at modest sample sizes (N[≥]200) and are replicable in a fully independent mid-adulthood cohort. Adult subcortical sex differences are already evident in nascent form by pre/early puberty (age 9 years), and the same holds for cortical sex differences. Comparison with neuroimaging data from rare disorder cohorts reveals a statistically significant spatial and directional congruence of subcortical sex differences with the anatomical effects of X-chromosome dosage in the striatum and effects of testicular hormones in the amygdala. Our findings provide a reference map for the fine-grained spatial patterning of sex differences in adult subcortical shape, demonstrating its replicability, establishment before pubertal progression, and spatial concordance with potentially causal sex chromosomal and gonadal effects.

neuroscience↗

bioRxiv2026

labapi: a Python object model for the LabArchives electronic lab notebook

labapi is a Python library that enables computational workflows to connect to LabArchives' electronic lab notebook (ELN). Without an Application Programming Interface (API) connection, researchers must manually add workflow outputs through the LabArchives web interface, navigating to the appropriate page and uploading each output so that it appears with the experimental notes that provide context. labapi translates the flat LabArchives API into a Python object model following the existing hierarchy of the web interface, allowing workflows to navigate and modify notebook content through familiar paths. labapi enables researchers to build interconnected workflows that both read in and write data to LabArchives' ELN automatically. Researchers can inspect those outputs in the notebook, and later analysis code can read them back for another stage of analysis.

bioinformatics↗

bioRxiv2026

Who Funds Open Data Sharing? Analysis of data availability statements in biomedical publications

Open data sharing is increasingly mandated by research funders, journals, and institutions, yet large-scale compliance measurement remains challenging. We analyzed 951,949 open access biomedical research articles published between January 2024 and June 2025 using a dual-source pipeline: PDF-based text extraction (MinerU) where PDFs were available and PMC XML otherwise, followed by algorithmic detection of data sharing statements (oddpub v7.2.3), enriched with funder, journal, and institutional metadata from OpenAlex. The corpus included 294,172 PDF-covered articles (30.9%) and 657,777 XML-only articles (69.1%). We found an over-all open data rate of 8.7%, rising to 11.7% among funder-linked articles (those with at least one funder identified in the metadata). Rates varied more than tenfold across the research ecosystem: leading major funders reached observed open data rates of 20-24%, while top journals reached observed rates of 70-86%, with corrected estimates as high as 92.9% (Nature Genetics) after adjusting for XML-only coverage limitations. PDF-based detection identified approximately 52% more data sharing statements than XML-based methods on the same articles. These observed rates differ markedly across funders and journals, and current overall sharing remains far below universal compliance. These patterns provide an empirical baseline against which future policy changes can be measured. An interactive dashboard at https://www.opensciencemetrics.org enables stakeholders to explore and benchmark these results.

scientific communication and education↗

bioRxiv2023

A bipolar taxonomy of adult human brain sulcal morphology related to timing of fetalsulcation and trans-sulcal gene expression gradients

We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (N=34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bipolar distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex; complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (N=228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.

neuroscience↗

bioRxiv2023

Improving accuracy and precision of heritability estimation in twin studies: Reassessing the measurement error assumption

IntroductionThe conventional approach to estimating heritability in twin studies implicitly assumes either the absence of measurement error or that any measurement error is incorporated into the nonshared environment component. However, this assumption can be problematic when it does not hold or when measurement error cannot be reasonably classified as part of the nonshared environment. MethodsIn this study, we demonstrate the need for improvement in the conventional structural equation modeling (SEM) used for estimating heritability when applied to trait data with measurement errors. The critical issue revolves around an assumption concerning measurement errors in twin studies. In cases where traits are measured using samples, data is aggregated during preprocessing, with only a centrality measure (e.g., mean) being used for modeling. Additionally, measurement errors resulting from sampling are assumed to be part of the nonshared environment and are thus overlooked in heritability estimation. Consequently, the presence of intra-individual variability remains concealed. Moreover, recommended sample sizes are typically based on the assumption of no measurement errors. ResultsWe argue that measurement errors in the form of intra-individual variability are an intrinsic limitation of finite sampling and should not be considered as part of the nonshared environment. Previous studies have shown that the intra-individual variability of psychometric effects is significantly larger than the inter-individual counterpart. Here, to demonstrate the appropriateness and advantages of our hierarchical linear modeling approach in heritability estimation, we utilize simulations as well as a real dataset from the ABCD (Adolescent Brain Cognitive Development) study. Moreover, we showcase the following analytical insights for data containing non-negligible measurement errors: O_LIThe conventional SEM may underestimate heritability. C_LIO_LIA hierarchical model provides a more accurate assessment of heritability. C_LIO_LILarge samples, exceeding 100 observations or thousands of twins, may be necessary to reduce imprecision. C_LI DiscussionOur study highlights the impact of measurement error on heritability estimation and introduces a hierarchical model as a more accurate alternative. These findings have significant implications for understanding individual differences and improving the design and analysis of twin studies.

genetics↗

bioRxiv2023

Social reward network connectivity differs between autistic and neurotypical youth during social interaction

A core feature of autism is difficulties with social interaction. Atypical social motivation is proposed to underlie these difficulties. However, prior work testing this hypothesis has shown mixed support and has been limited in its ability to understand real-world social-interactive processes in autism. We attempted to address these limitations by scanning neurotypical and autistic youth (n = 86) during a text-based reciprocal social interaction that mimics a "live" chat and elicits social reward processes. We focused on task-evoked functional connectivity (FC) of regions responsible for motivational-reward and mentalizing processes within the broader social reward circuitry. We found that task-evoked FC between these regions was significantly modulated by social interaction and receipt of social-interactive reward. Compared to neurotypical peers, autistic youth showed significantly greater task-evoked connectivity of core regions in the mentalizing network (e.g., posterior superior temporal sulcus) and the amygdala, a key node in the reward network. Furthermore, across groups, the connectivity strength between these mentalizing and reward regions was negatively correlated with self-reported social motivation and social reward during the scanner task. Our results highlight an important role of FC within the broader social reward circuitry for social-interactive reward. Specifically, greater context-dependent FC (i.e., differences between social engagement and non-social engagement) may indicate an increased "neural effort" during social reward and relate to differences in social motivation within autistic and neurotypical populations.

neuroscience↗

bioRxiv2020

Computationally replicating the Smith et al. (2015) positive-negative mode linking functional connectivity and subject measures

Understanding brain functionality and predicting human behavior based on functional brain activity is a major goal of neuroscience. Numerous studies have been conducted to investigate the relationship between functional brain activity and attention, subject characteristics, autism, psychiatric disorders, and more. By modeling brain activity data as networks, researchers can leverage the mathematical tools of graph and network theory to probe these relationships. In their landmark study, Smith et al. (2015) analyzed the relationship of young adult connectomes and subject measures, using data from the Human Connectome Project (HCP). Using canonical correlation analysis (CCA), Smith et al. found that there was a single prominent CCA mode which explained a statistically significant percentage of the observed variance in connectomes and subject measures. They also found a strong positive correlation of 0.87 between the primary CCA mode connectome and subject measure weights. In this study, we computationally replicate the findings of the original study in both the HCP 500 and HCP 1200 subject releases. The exact computational replication in the HCP 500 dataset was a success, validating our analysis pipeline for extension studies. The extended replication in the larger HCP 1200 dataset was partially successful and demonstrated a dominant primary mode.

neuroscience↗

bioRxiv2019

Cortical temporal hierarchy is immature in middle childhood

The development of successful social-cognitive abilities requires one to track, accumulate, and integrate knowledge of other peoples mental states across time. Regions of the brain differ in their temporal scale (i.e., a cortical temporal hierarchy) and those receptive to long temporal windows may facilitate social-cognitive abilities; however, the cortical development of long timescale processing remains to be investigated. The current study utilized naturalistic viewing to examine cortical development of long timescale processing and its relation to social-cognitive abilities in middle childhood - a time of expanding social spheres and increasing social-cognitive abilities. We found that, compared to adults, children exhibited reduced low-frequency power in the temporo-parietal junction (TPJ) and reduced specialization for long timescale processing within the TPJ and other regions broadly implicated in the default mode network and higher-order visual processing. Further, specialization for long timescales within the right dorsal medial prefrontal cortex became more adult-like as a function of childrens comprehension of character mental states. These results suggest that cortical temporal hierarchy in middle childhood is immature and may be important for an accurate representation of complex naturalistic social stimuli during this age.

neuroscience↗