Biology subjects

Shearer, H.

Publications and source records attributed to Shearer, H..

4 recordsLinked to original sources

bioRxiv2026

The Hidden Landscape of Missed Effects in Human Functional Neuroimaging

Functional neuroimaging aims to uncover brain processes underlying behavior and disease, yet studies are often underpowered to detect these effects. How this literature has shaped our understanding of brain function remains unknown, and little guidance exists for planning better powered studies. An underappreciated barrier is that commonly reported effect sizes across the brain are inflated, biasing study planning. Here, we introduce a correction for this inflation bias and show how more accurate studies can be planned using corrected effect size benchmarks from a mega-analysis of 63 typical studies across seven large datasets (52,979 participants). We find that common methods of planning studies based on uncorrected effects lead to roughly half the expected detections at typical sample sizes, with limited spatial overlap with original findings. These missed effects collectively explain meaningful additional variance in the desired outcome. We show how to recover missed effects by planning not only for power but also for a target number of detections via corrected benchmarks, or by taking a whole-brain approach with multivariate effects that individual research groups can detect (n < 50 compared to n > 1,000 for a typical univariate effect). These findings lay the groundwork for more informed study planning and a richer understanding of the widespread nature of brain effects, with implications for shared challenges (and solutions) across biomedicine.

neuroscience↗

bioRxiv2026

PRISME: A MATLAB Toolbox For Large Data-Driven Multimodal Power Benchmarking

Low statistical power in neuroimaging often undermines research in the field, leading to missed effects, wasted resources, and reduced reproducibility. Performing power analyses during the study design phase is extremely important, but often prohibitively difficult due to a lack of analytical solutions and high computational costs. We present PRISME (Power Resampling Infrastructure for Statistical Method Evaluation), a MATLAB toolbox for neuroimaging power benchmarking. PRISME provides a computational framework for empirical power analysis independent of inference methods, enabling large scale power benchmarking and method comparison. The toolbox supports diverse neuroimaging data types, including both voxel-based activation and functional connectivity analyses, with a non-parametric, flexible algorithm and unified data representations. Furthermore, unlike previous empirical power approaches, PRISME supports multiple test types, such as association and difference tests with behavioral and clinical measures. Finally, PRISMEs 25x speedup from algorithmic optimizations enables larger-scale power benchmarking, including the first power analysis for the ABCD dataset. Overall, PRISME is the first method- and data-type-agnostic power benchmarking tool for neuroimaging, providing a single solution for power analysis across diverse study designs.

neuroscience↗

bioRxiv2025

Mechanism of NanR transcriptional activation of sialic acid metabolism in Streptococcus pneumoniae.

In Streptococcus pneumoniae, the RpiR transcriptional regulator NanR (SpNanR) senses sialic acid in the environment and upregulates transcription of the nan and siaA operons to increase uptake and metabolism of sialic acid. The molecular basis of this activation is unknown. Here, we demonstrate that SpNanR binds N-acetylmannosamine-6-phosphate, a metabolite of sialic acid catabolism. SpNanR exists in a dimer-tetramer equilibrium, and N-acetylmannosamine-6-phosphate binding strongly stabilizes the tetramer. Crystal structures and site-specific substitutions demonstrate that N-acetylmannosamine-6-phosphate bridges and stabilizes the SpNanR tetramer. SpNanR binds its DNA recognition sequence with nanomolar affinity. Notably, the effector N-acetylmannosamine-6-phosphate does not affect the affinity of SpNanR for DNA. The DNA binding domains are not structurally coupled to the sugar isomerase domains, explaining why N-acetylmannosamine-6-phosphate binding does not affect DNA binding. Structural analysis reveals that sequence specificity arises through distortion of B-DNA and an unusual {pi}-stack formed by two arginine residues in the minor groove, while affinity is driven by backbone contacts. We propose a mechanism by which S. pneumoniae regulates sialic acid metabolism, consistent with our biophysical experiments and in vivo regulatory behavior. These findings define a unique activation mechanism for an RpiR regulator and provide new insights into carbohydrate-responsive gene regulation in pneumococci.

molecular biology↗

bioRxiv2025

Patterns of intersubject correlations parallel organizational gradients during naturalistic viewing

Recent studies have robustly demonstrated that human cortical function can be described through sensory-transmodal gradients of cortical function, while naturalistic movie watching paradigms have been leveraged to index cortical synchronization. We leveraged two independent 7T movie fMRI datasets to assess correlations between intersubject correlation and functional gradients across movies, datasets, and spatial scales. At the whole-brain level, we observed robust relationships between intersubject correlations and a visual-transmodal connectivity gradient which was independent of movie content. Within functional networks, correlations were particularly pronounced for the visual, dorsal attention, and default mode networks. Our results demonstrate that naturalistic paradigms can provide targeted insight into multiscale processing hierarchies. Robust relationships across movies suggest that movie-watching can be viewed as a brain state that is independent of movie-content. Overall, this work suggests an important confluence of within-subject functional organizational axes and inter-subject synchronization when the brain is engaged in the processing of naturalistic stimuli.

neuroscience↗