Biology subjects

Fitzgerald, N. E.

Publications and source records attributed to Fitzgerald, N. E..

3 recordsLinked to original sources

bioRxiv2026

Probabilistic Retinotopic Parcellation of the Macaque Visual Cortex

Probabilistic brain atlases provide anatomically and functionally interpretable normative references that summarize population-level organization while explicitly representing spatial uncertainty. Yet such resources remain scarce due to the resource-intensive experimental efforts required to construct them. Here, we present a probabilistic retinotopic atlas of the macaque visual cortex, derived from contrast-enhanced phase-encoded fMRI data acquired in 13 subjects. The dataset includes a 50% probability parcellation covering 19 visual areas, individual subject labels, and voxel-wise probability maps for each area, all registered to the MEBRAINS macaque template. By combining a consensus parcellation with spatial estimates of confidence for each visual area, this atlas enables more informed anatomical localization and interpretation than deterministic or single-subject-based atlases. As a standardized reference for the macaque visual cortex, it supports experimental design, data interpretation, and multimodal data integration while providing a quantitative framework for investigating the developmental and evolutionary principles that shape the primate visual cortex.

neuroscience↗

bioRxiv2026

Volumetric functional ultrasound imaging in macaques

Linking circuit level activity to large scale functional organization requires imaging methods combining high spatial resolution, broad coverage, and single trial sensitivity. We present volumetric functional ultrasound imaging (3D-fUS) in behaving macaques, enabling imaging of ~1 cm3 cortical volumes at high spatiotemporal resolution (100 x 150 x 150 m3 voxels, 1.67 Hz). Visually evoked responses were reliably detected at the level of single trials and single voxels, substantially reducing experimental time. To enable model-based analyses analogous to functional magnetic resonance imaging (fMRI), we estimated a canonical fUS hemodynamic response function (fUS-HRF) that was consistent across subjects, cortical areas, and visual stimuli and was well approximated by a gamma function. Compared with canonical fMRI HRFs, the fUS-HRF exhibited faster dynamics, enabling shorter and more closely spaced stimulus presentations. Together, these results establish 3D-fUS as a fast, volumetric, and circuit relevant imaging modality for efficient investigation of distributed cortical dynamics in primates.

neuroscience↗

bioRxiv2025

OfUSA: OpenfUS Analyzer, a versatile open-source framework for the analysis and visualization of functional ultrasound imaging data across animal models

Functional ultrasound (fUS) imaging is rapidly gaining interest for its unprecedented ability to study large-scale brain dynamics, yet its adoption and broader dissemination have been hindered by the lack of standardized tools and methodologies to analyze and interpret its rich datasets. We present OpenfUS Analyzer (OfUSA), a companion software suite designed to help researchers quickly engage with fUS data and perform the full range of analyses needed to generate publication-ready results and figures without relying on additional software. OfUSA offers a versatile and modular architecture including preprocessing, recording quality assessment, signal dynamics exploration, statistical analysis and visualization. These functions are separated yet easily combined into analytic pipelines through a programming-free graphical interface. The framework can be applied across species and experimental contexts, either by registering data to anatomical atlases, as shown here for the mouse brain, or by analyzing data without atlas constraints, as illustrated in a primate dataset. This flexibility, together with its comprehensive functionality, makes OfUSA a practical solution for standardized and reproducible analysis of fUS data in both preclinical and translational research. Using OfUSA, we demonstrate the capacity to detect stimulus-evoked responses with high sensitivity, identify their spatial localization within brain networks, and quantify both their extent and temporal dynamics. These results highlight the softwares ability to capture robust activation patterns and provide detailed insights into brain function, thereby accelerating the use of fUS as a powerful tool for systems neuroscience. HighlightsWe present OpenfUS Analyzer (OfUSA), a novel software platform for the complete analysis of functional ultrasound (fUS) datasets. OfUSA combines a user-friendly graphical interface with a standardized, flexible workflow and powerful visualization tools, making it an ideal solution for fUS researchers at all experience levels. The softwares utility is first demonstrated through the analysis of rodent fUS data using a standardized atlas, while its versatility is further emphasized by the successful analysis of a primate fUS dataset without a template, thereby illustrating its adaptability to non-standard experimental conditions.

neuroscience↗