Biology subjects

Lerma-Usabiaga, G.

Publications and source records attributed to Lerma-Usabiaga, G..

10 recordsLinked to original sources

bioRxiv2026

Design and Validation of a Hybrid Stimulus fMRI Paradigm for Simultaneous Retinotopy and Mapping of Reading-Selective Visual Cortex

Reading selectively recruits specialized cortical patches within the left ventral occipitotemporal cortex (vOTC), such as the visual word form area (VWFA). Under the framework of the interactive account of word recognition, these neural responses emerge from dynamic, bidirectional loops where top-down linguistic predictions continuously modulate and constrain bottom-up sensory visual inputs. Consequently, identifying and isolating these top-down cognitive signals fundamentally requires a precise characterization of the underlying low-level sensory baseline. This dense-sampling fMRI study (11 right-handed adults, 10 sessions each) systematically addresses the spatial and functional architecture of the reading network using population receptive field (pRF) modeling and functional localizers (fLoc). First, we conduct a rigorous group- and subject-level replication of stimulus-dependent pRF eccentricity shifts (words and false fonts versus checkers) observed in previous research. To overcome known barriers to individual parameter stability, we systematically manipulate and evaluate stimulus Frequency, bar Width, and element Size (FWS) across eight sessions per subject to isolate the precise factors driving test-retest reliability. Second, we design and validate a novel Word-Center (WC) paradigm acquired across one/two sessions per participant. This hybrid paradigm was designed to decouple moving spatial mapping carriers (checkerboard bars) from central reading processes (word or false-font streams in the central fixation location). Functional data were denoised with NORDIC, preprocessed via fMRIPrep, and projected to the cortical surface for analysis via Nilearn GLMs to model word-responsive regions and mrVista to obtain pRF estimates. Individual-level spatial maps replicated previous results in approximately 70% of subjects. The lack of replication in the remaining subjects, whether driven by methodological factors or inherent individual differences, highlights ongoing baseline mapping challenges. Optimizing this mapping is sensitive to stimulus carrier type and specific FWS configurations. Furthermore, the hybrid WC paradigm successfully demonstrates stimulus equivalence, concurrently yielding robust reading-selective functional localization and reliable retinotopic estimates. By breaking the spatial-lexical confound of traditional mapping protocols, this paradigm provides an innovative framework to separate bottom-up sensory sweeps from top-down central linguistic processing. This vision-centric framework serves as a methodological baseline toward a comprehensive, multi-signal understanding of the human reading hierarchy.

neuroscience↗

bioRxiv2026

Tractometry reproducibility and generalizability across scanners, scanner models, and acquisition protocols

Diffusion-weighted magnetic resonance imaging (dMRI)-based tractometry enables the quantification of white matter tissue properties in living humans while preserving anatomical specificity. Although tractometry is highly reproducible when the same scanner and acquisition protocol are used, its generalizability across scanners and protocols remains unclear. To address this gap, we performed a traveling-head experiment involving five subjects to evaluate tractometry across progressively different acquisition conditions, including multiple scanners, different scanner models, and two distinct protocols. Tractometry was performed for 20 major white matter tracts using diffusion tensor imaging metrics, neurite orientation dispersion and density imaging (NODDI) metrics, and a semi-quantitative ratio metric (T1w/b0). Generalizability across dataset pairs was quantified using the intraclass correlation coefficient (ICC). Tractometry showed consistently high ICCs when the scanner and protocol were identical; however, ICCs declined as differences in scanner model and acquisition protocol increased. Fractional anisotropy and orientation dispersion index retained relatively high ICCs across these comparisons, whereas other metrics showed marked declines when scanners or protocols differed. ComBat harmonization partially mitigated these declines, but ICCs did not reach the levels observed for datasets acquired using identical scanners and protocols. Finally, the minimum detectable change (MDC) for tractometry in datasets pooled across scanners and protocols varied by tract; for example, the optic radiation showed a lower MDC than the cingulum hippocampus. These findings highlight both the strengths and limitations of tractometry in multisite studies and highlight the importance of quantifying scanner- and protocol-dependent effects for specific metrics and tracts when interpreting measurements from heterogeneous datasets.

neuroscience↗

bioRxiv2025

Language comprehension functionally modulates first-order relay thalamic nuclei

Language, a uniquely human higher-order cognitive function, has traditionally been attributed to cortical mechanisms with limited attention given to subcortical contributions. Recent advances in non-invasive neuroimaging have revealed that thalamic activity can be modulated by attention and task demands. Moreover, lesion studies have hinted at the thalamuss potential role in language processing. Nevertheless, the precise involvement of this structure in language remains unclear. Here, we ask whether language- related modulations can be detected as early as the sensory thalamic stage. Using functional MRI to image 40 human participants (both female and male) while processing linguistic and non-linguistic stimuli of three main language systems (reading, speech comprehension, and speech production), we demonstrate specific activation of first-order nuclei during targeted language system tasks: lateral geniculate (LGN) for reading, medial geniculate (MGN) for speech comprehension and ventrolateral (VLN) for speech production. Notably, we show linguistic versus non-linguistic stimuli exhibit functional modulations during comprehension tasks (reading and speech) of left MGN and, to a lesser extent, left LGN--in line with prior studies of lateralization of language processes. Multi-voxel classification analysis confirmed left-lateralized linguistic modulation in the MGN, but not in the LGN. Given the complexity of thalamic connectivity and its potential role in integrating sensory and cognitive processes, this work offers a comprehensive characterization of first-order thalamic engagement across reading, speech comprehension, and speech production within the same participants, advancing our understanding of thalamic involvement and thalamocortical interactions in language function.

neuroscience↗

bioRxiv2024

Biases in volumetric versus surface analyses in population receptive field mapping

Population receptive field (pRF) mapping is a quantitative fMRI analysis method that links visual field positions with specific locations in the visual cortex. A common preprocessing step in pRF analyses involves projecting volumetric fMRI data onto the cortical surface, often leading to upsampling of the data. This process may introduce biases in the resulting pRF parameters. To investigate this, we present CON-pRF, a fully containerized pipeline for pRF mapping analysis that is designed to maximize reproducibility in pRF mapping studies. Using this pipeline, we compared pRF maps generated from original volumetric with those from upsampled surface data. Our results show substantial increases in pRF coverage in the central visual field of upsampled data sets. These effects were consistent across early visual cortex areas V1-3. Further analysis indicates that this bias is primarily driven by the non-linear relationship between cortical distance and visual field eccentricity, known as cortical magnification. Our results demonstrate that reproducible analysis pipelines enable the detection of potential biases introduced by varying processing steps, particularly when comparing across differently processed datasets. Key PointsO_LISpatial upsampling increases pRF coverage in the fovea due to enhanced CNR and cortical magnification. C_LIO_LIThe study highlights the need for careful consideration of data processing steps. C_LIO_LICON-pRF is a containerized pipeline for enhanced reproducibility in pRF analysis. C_LI

neuroscience↗

bioRxiv2023

Characterizing spatiotemporal population receptive fields in human visual cortex with fMRI

The use of fMRI and computational modeling has advanced understanding of spatial characteristics of population receptive fields (pRFs) in human visual cortex. However, we know relatively little about the spatiotemporal characteristics of pRFs because neurons temporal properties are one to two orders of magnitude faster than fMRI BOLD responses. Here, we developed an image-computable framework to estimate spatiotemporal pRFs from fMRI data. First, we developed a simulation software that predicts fMRI responses to a time varying visual input given a spatiotemporal pRF model and solves the model parameters. The simulator revealed that ground-truth spatiotemporal parameters can be accurately recovered at the millisecond resolution from synthesized fMRI responses. Then, using fMRI and a novel stimulus paradigm, we mapped spatiotemporal pRFs in individual voxels across human visual cortex in 10 participants. We find that a compressive spatiotemporal (CST) pRF model better explains fMRI responses than a conventional spatial pRF model across visual areas spanning the dorsal, lateral, and ventral streams. Further, we find three organizational principles of spatiotemporal pRFs: (i) from early to later areas within a visual stream, spatial and temporal integration windows of pRFs progressively increase in size and show greater compressive nonlinearities, (ii) later visual areas show diverging spatial and temporal integration windows across streams, and (iii) within early visual areas (V1-V3), both spatial and temporal integration windows systematically increase with eccentricity. Together, this computational framework and empirical results open exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses in the human brain using fMRI. Significance StatementWe developed a computational framework for estimating spatiotemporal receptive fields of neural populations using fMRI. This framework pushes the boundary of fMRI measurements, enabling quantitative evaluation of neural spatial and temporal processing windows at the resolution of visual degrees and milliseconds, which was thought to be unattainable with fMRI. We not only replicate well-established visual field and pRF size maps, but also estimates of temporal summation windows from electrophysiology. Notably, we find that spatial and temporal windows as well as compressive nonlinearities progressively increase from early to later visual areas in multiple visual processing streams. Together, this framework opens exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses in the human brain using fMRI.

neuroscience↗

bioRxiv2022

Reproducible Tract Profiles (RTP2): from diffusion MRI acquisition to clinical practice and research

Diffusion MRI is a complex technique, where new discoveries and implementations occur at a fast pace. The expertise needed for data analyses and accurate and reproducible results is increasingly demanding and requires multidisciplinary collaborations. In the present work we introduce Reproducible Tract Profiles (RTP2): a set of flexible and automated methods to analyze anatomical MRI and diffusion weighted imaging (DWI) data for reproducible tractography. The tools read structural MRI data and process them through a succession of serialized containerized analyses. We describe the DWI algorithms used to identify white-matter tracts and their summary metrics, the flexible architecture of the platform, and the tools to programmatically access and control the computations. The combination of these three components provides an easy-to-use automatized tool developed and tested over 20 years, to obtain usable and reliable state-of-the-art diffusion metrics at the individual and group levels for basic research and clinical practice. HighlightsO_LIAutomated, flexible and reproducible protocol for white-matter tractography and tractometry. C_LIO_LIHigh computational (same data, different computations) and test-retest reproducibility (data from different sessions, different computations). C_LIO_LIOpen-source code and publicly available containers. C_LI

neuroscience↗

bioRxiv2021

Interpreting sensory and cognitive signals in the cortical reading network

Voxels in the visual cortex contain neurons that are responsive to small regions of the visual field; these regions can be quantified using population receptive field (pRF) analysis. We measured pRFs using several types of patterns: words, visually matched false-fonts, and visually dissimilar checker patterns. In visual field maps pRF estimates using words and false-fonts are similar, but pRF estimates using checkers differ substantially. The pattern of results in the contiguous ventral occipito-temporal reading circuitry is different: word pRF estimates differ from false-fonts and checkers. These findings were replicated at two research sites. We explain these results with a qualitative model, where the response differences in the visual field maps arise from sensory signals, and the differences in the reading circuitry arise from the integration of sensory and cognitive signals.

neuroscience↗

bioRxiv2020

Population receptive field shapes in early visual cortex are nearly circular

The visual field region where a stimulus evokes a neural response is called the receptive field (RF). Analytical tools combined with functional MRI can estimate the receptive field of the population of neurons within a voxel. Circular population RF (pRF) methods accurately specify the central position of the pRF and provide some information about the spatial extent (diameter) of the receptive field. A number of investigators developed methods to further estimate the shape of the pRF, for example whether the shape is more circular or elliptical. There is a report that there are many pRFs with highly elliptical pRFs in early visual cortex (V1-V3; Silson et al., 2018). Large aspect ratios (>2) are difficult to reconcile with the spatial scale of orientation columns or visual field map properties in early visual cortex. We started to replicate the experiments and found that the software used in the publication does not accurately estimate RF shape: it produces elliptical fits to circular ground-truth data. We analyzed an independent data set with a different software package that was validated over a specific range of measurement conditions, to show that in early visual cortex the aspect ratios are less than 2. Furthermore, current empirical and theoretical methods do not have enough precision to discriminate ellipses with aspect ratios of 1.5 from circles. Through simulation we identify methods for improving sensitivity that may estimate ellipses with smaller aspect ratios. The results we present are quantitatively consistent with prior assessments using other methodologies. Significance StatementWe evaluated whether the shape of many population receptive fields in early visual cortex is elliptical and differs substantially from circular. We evaluated two tools for estimating elliptical models of the pRF; one tool was valid over the measured compliance range. Using the validated tool, we found no evidence that confidently rejects circular fits to the pRF in visual field maps V1, V2 and V3. The new measurements and analyses are consistent with prior theoretical and experimental assessments in the literature.

neuroscience↗

bioRxiv2020

A validation framework for neuroimagingsoftware: the case of populationreceptive fields

Neuroimaging software methods are complex, making it a near certainty that some implementations will contain errors. Modern computational techniques (i.e., public code and data repositories, continuous integration, containerization) enable the reproducibility of the analyses and reduce coding errors, but they do not guarantee the scientific validity of the results. It is difficult, nay impossible, for researchers to check the accuracy of software by reading the source code; ground truth test datasets are needed. Computational reproducibility means providing software so that for the same input anyone obtains the same result, right or wrong. Computational validity means obtaining the right result for the ground-truth test data. We describe a framework for validating and sharing software implementations. We apply the framework to an application: population receptive field (pRF) methods for functional MRI data. The framework is composed of three main components implemented with containerization methods to guarantee computational reproducibility: (1) synthesis of fMRI time series from ground-truth pRF parameters, (2) implementation of four public pRF analysis tools and standardization of inputs and outputs, and (3) report creation to compare the results with the ground truth parameters. We identified realistic conditions that lead to imperfect parameter recovery in all four implementations, and we provide means to reduce this problem. The computational validity framework supports scientific rigor and creativity, as opposed to the oft-repeated suggestion that investigators rely upon a few agreed upon packages. The framework and methods can be extended to other critical neuroimaging algorithms. Having validation frameworks help (1) developers to build new software, (2) research scientists to verify the softwares accuracy, and (3) reviewers to evaluate the methods used in publications and grants. Author SummaryComputer science provides powerful tools and techniques for implementing and deploying software. These techniques support software collaboration, reduce coding errors and enable reproducibility of the analyses. A further question is whether the software estimates are correct (valid). We describe a framework for validating and sharing software implementations based on ground-truth testing. We applied the framework to four separate applications that implemented population receptive field (pRF) estimates for functional MRI data. We quantified the validity, and we also documented limitations with these applications. Finally, we provide ways to mitigate these limitations. Implementing a software validation framework along with sharing and reproducibility is an important step for the complex methods used in neuroscience. Validation will help developers to build new software, researchers verify that the results are valid, and reviewers to evaluate the precision of methods in publications and grants.

neuroscience↗

bioRxiv2019

Reproducible Tract Profiles (RTP): from diffusion MRI acquisition to publication

Reproducible Tract Profiles (RTP) comprises a set of methods to manage and analyze diffusion weighted imaging (DWI) data for reproducible tractography. The tools take MRI data from the scanner and process them through a series of analysis implemented as Docker containers that are integrated into a modern neuroinformatics platform (Flywheel). The platform guarantees that the entire pipeline can be re-executed, using the same data and computational parameters. In this paper, we describe (1) a cloud based neuroinformatics platform, (2) a tool to programmatically access and control the platform from a client, and (3) the DWI analysis tools that are used to identify the positions of 22 tracts and their diffusion profiles. The combination of these three components defines a system that transforms raw data into reproducible tract profiles for publication.\n\nGraphical abstractReproducible Tract Profiles (RTP) comprises a set of methods to manage and analyze diffusion weighted imaging (DWI) data for reproducible tractography. The RTP methods comprise two main parts. O_LIServer side software tools for storing data and metadata and managing containerized computations.\nC_LIO_LIClient side software tools that enable the researcher to read data and metadata and manage server-side computations.\nC_LI\n\nThe server-side computational tools are embedded in containers that are linked to a JSON file with a complete specification of the computational parameters. The data and computational infrastructure on the server is fully reproducible.

neuroscience↗