Biology subjects

Schwartz, S. T.

Publications and source records attributed to Schwartz, S. T..

3 recordsLinked to original sources

bioRxiv2026

Dissociable structural and molecular pathways of age-related change in sustained attention

Sustained attention, the capacity to maintain goal-directed attention over extended periods, declines with age but with substantial individual variability across cognitively unimpaired (CU) older adults. We sought to determine the contributions of microstructural deterioration of the superior longitudinal fasciculus (SLF), the principal white-matter tract coupling prefrontal and parietal nodes of the dorsal attention network, as well as markers of preclinical Alzheimers disease (AD) to individual differences in sustained attention in ageing. In 162 CU older adults (mean (SD) age = 73.0 (4.9), %F = 64.8) drawn from two Stanford ageing cohorts, we measured sustained attention using the gradual-onset Continuous Performance Task (gradCPT). Performance was indexed by a composite score (Att-Z) derived from discriminability (d') and response-time variability (RTV). We used diffusion MRI tractography to quantify SLF fractional anisotropy (FA) and mean diffusivity (MD) alongside two control tracts, the corticospinal tract (CST) and cingulum (CGC). NULISA multiplex plasma immunoassays were used to measured AD-related pathology (pTau-181, pTau-217), neuroaxonal injury (NfL), and astrocytic reactivity (GFAP; plasma subsample N = 146). Parallel mediation and commonality analyses tested whether structural and plasma biomarker pathways contribute independently to individual differences in sustained attention function. Older age was associated with lower Att-Z ({beta} = -0.315, p < 0.001). In simultaneous three-tract regression models, only SLF microstructure uniquely predicted Att-Z (FA: {beta} = +0.275, p < 0.001; MD: {beta} = -0.320, p < 0.001). SLF microstructure mediated the age-attention relationship (FA indirect {beta}unstandardised = -0.01, pboot <0.01, MD indirect {beta}unstandardised = -0.009 to -0.01, pboot <0.05). Plasma pTau-181 ({beta} = -0.212, pFDR < 0.03), pTau-217 ({beta} = -0.163, pFDR < 0.05), and NfL ({beta} = -0.156, pFDR < 0.05) were negatively associated with Att-Z and each mediated effects of age on performance (pTau-181 indirect {beta}unstandardised = -0.008, pboot < 0.01; pTau-217 indirect {beta}unstandardised= -0.006, pboot< 0.05; NfL indirect {beta}unstandardised = -0.011, pboot< 0.05), whereas GFAP showed no association with sustained attention in any model. SLF microstructure was negatively associated with age (FA {beta} = -0.207, p < 0.01; MD {beta} = +0.270, p < 0.001) but was not significantly associated with plasma biomarkers (all p > 0.10). In parallel mediation models, SLF microstructure and plasma pTau exhibited significant independent indirect effects on Att-Z (SLF FA indirect {beta}unstandardised= -0.010, pboot< 0.01; SLF MD indirect {beta}unstandardised = -0.009 to -0.010, pboot< 0.05; pTau-181 indirect {beta}unstandardised = -0.008 to -0.009, pboot< 0.01; pTau-217 indirect {beta}unstandardised= -0.006 to -0.007, pboot< 0.05). Effects of NfL were attenuated when combined in a model with pTau (indirect {beta}unstandardised = -0.005 to -0.008, pboot> 0.15), suggesting shared variance among these markers. These findings reveal multiple pathways that contribute to individual differences in sustained attention in ageing that are detectable before clinical impairment, including SLF white matter integrity -- which is linked to the structural disconnection of the dorsal attention network -- and preclinical AD pathology. The independence of these pathways identifies two separable biological targets for preserving attentional capacity in CU older adults.

neuroscience↗

bioRxiv2025

charisma: An R package to perform reproducible color characterization of digital images for biological studies

O_LIAdvances in digital imaging and software tools have provided increasingly accessible datasets and methods for analyzing color evolution. Despite the variety of computational packages available, most rely on color classification before running analyses. Previous methods to characterize color limit the ability to analyze large-scale image databases and are not always representative of biologically relevant color classes, which decrease the accuracy of downstream analyses. C_LIO_LIHere, we present charisma, an R package designed to characterize the distribution of distinct color classes in images suitable for large-scale studies of biological organisms. Here, we demonstrate the utility of our package through an analysis of color evolution in a sample of diverse and charismatic birds, tanagers, in the subfamily Thraupinae. C_LIO_LIWe show that charisma can quickly and accurately classify every pixel in an image and validate these results using pre-identified, canonical color swatches. We find that charisma color classifications are consistent with those made by color-pattern experts in the field. Applying charisma to tanager color evolution, we find that charisma outputs seamlessly integrate with downstream evolutionary analyses. C_LIO_LIOur results demonstrate that using charisma to manually curate and characterize colors in images provides a standardized, reliable, and reproducible framework for high-throughput color classification. C_LI Anonymized Data/Code for Peer ReviewO_LIAnalytic data/code for this manuscript can be found on the following Open Science Frame-work repo: https://osf.io/cqg59/overview?view_only=29c9786a338e48618fabbab2883937cc C_LIO_LIcharisma package GitHub repo: https://anonymous.4open.science/r/charisma-C87E/ C_LI

evolutionary biology↗

bioRxiv2025

eyeris: A flexible, extensible, and reproducible pupillometry preprocessing framework in R

Pupillometry provides a non-invasive window into the mind and brain, particularly as a psychophysiological readout of autonomic and cognitive processes like arousal, attention, stress, and emotional states. Pupillometry research lacks a robust, standardized framework for data preprocessing, whereas in functional magnetic resonance imaging and electroencephalography, researchers have converged on tools such as fMRIPrep, EEGLAB and MNE-Python. Many established pupillometry preprocessing packages and workflows fall short of serving the goal of enhancing reproducibility, especially since most existing solutions lack designs based on Findability, Accessibility, Interoperability, and Reusability (FAIR) principles. To promote FAIR and open science practices for pupillometry research, we developed eyeris, a complete pupillometry preprocessing suite designed to be intuitive, modular, performant, and extensible (https://github.com/shawntz/eyeris). Out-of-the-box, eyeris provides a recommended preprocessing workflow and considers signal processing best practices for tonic and phasic pupillometry. Moreover, eyeris further enables open and reproducible science workflows, as well as quality control workflows by following a well-established file management schema and generating interactive output reports for both record keeping/sharing and quality assurance of preprocessed pupil data prior to formal analysis. Taken together, eyeris provides a robust all-in-one transparent and adaptive solution for high-fidelity pupillometry preprocessing with the aim of further improving reproducibility in pupillometry research.

neuroscience↗