Garikoitz Lerma‐Usabiaga

This paper designs and validates a hybrid fMRI paradigm to simultaneously map retinotopy and reading-selective visual cortex by decoupling spatial mapping carriers from central reading processes.

This study evaluates tractometry reproducibility and generalizability across different MRI scanners, models, and protocols, finding high consistency with identical settings but reduced reliability with variations.

The paper demonstrates specific thalamic nucleus activation during language processing tasks using fMRI in human participants.

The paper compares volumetric and surface-based pRF mapping analyses, finding that surface upsampling increases pRF coverage in the central visual field due to cortical magnification.

This paper develops a computational framework to estimate spatiotemporal population receptive fields from fMRI data, finding that a compressive spatiotemporal model better explains responses than a spatial model across visual areas.

This paper introduces a Bayesian segmentation algorithm for thalamic nuclei using diffusion MRI and an improved histological atlas, showing improved accuracy in identifying nuclei and detecting Alzheimer's disease involvement.

The paper introduces RTP2, a reproducible and automated method for white-matter tractography and tractometry using diffusion MRI data.

The paper examines how different visual patterns affect pRF estimates in the visual cortex and reading network, finding differences in sensory and cognitive signal integration.

This study evaluates variability in white matter bundle segmentation across 42 groups using the same dataset, finding protocol variability exceeds other sources of inconsistency.

The paper evaluates the shape of population receptive fields in early visual cortex, finding that aspect ratios are less than 2, contradicting previous claims of highly elliptical shapes.

The paper introduces a framework for validating neuroimaging software using ground-truth testing, applied to population receptive field analysis in fMRI data.

The paper identifies shared and segregated white matter tracts for math and reading networks using multimodal MRI, revealing structural differences related to myelination in sub-bundles.

The paper introduces a system for reproducible tractography using diffusion MRI data through a cloud-based platform and containerized tools.