Biology subjects

Fernandez-Ruiz, J.

Publications and source records attributed to Fernandez-Ruiz, J..

7 recordsLinked to original sources

bioRxiv2026

Longitudinal Reorganization of Cortical and Cerebellar Functional Networks in Spinocerebellar Ataxia Type 7

Spinocerebellar ataxia type 7 (SCA7) is a rare neurodegenerative disorder characterized by progressive cerebellar ataxia and visual impairment. We investigated longitudinal changes in resting-state functional connectivity and their clinical associations. Resting-state functional MRI was acquired from 16 individuals with SCA7 and 16 age- and sex-matched healthy controls across three visits over 24 months. Network-to-network functional connectivity was quantified, and machine-learning models were trained using functional connectivity features. SCA7 showed lower MoCA (p = 0.045) and MMSE (p = 0.025) scores and progressive worsening of ataxia (SARA, p < 0.001). Significant Group x Visit interactions were observed for Visual-Default Mode (p = 0.012) and Somatomotor-Cerebellar Dorsal Attention connectivity (p = 0.038). Functional connectivity abnormalities involved cortical, cortico-cerebellar, and cerebellar networks that became more widespread at the final follow-up assessment, with the visual network emerging as the most consistently affected system across analyses. Functional connectivity abnormalities were associated with cognitive performance (MMSE: r = -0.62, p = 0.01) and disease severity (SARA: r = 0.589, p = 0.016). Functional connectivity features accurately classified SCA7 and healthy controls (accuracy = 96.4%, F1 = 0.969). These findings support resting-state functional connectivity as a candidate biomarker warranting further validation in larger, independent cohorts.

neuroscience↗

bioRxiv2026

Neuroanatomical subtypes of Long COVID reveal distinct cognitive profiles alongside longitudinal brain changes

BackgroundLong COVID is characterized by persistent symptoms following SARS-CoV-2 infection, including cognitive deficits among its most disabling manifestations. However, their neurobiological basis is poorly understood. Previous neuroimaging studies reported structural brain alterations, but few have integrated cognitive assessment, network-based analyses, and longitudinal imaging to identify neurobiological subtypes. MethodsWe studied 42 individuals with persistent post-COVID cognitive symptoms and 14 matched healthy controls using cognitive assessment and structural MRI. Multilayer brain networks were constructed from regional morphometric measures, and hierarchical clustering identified patient subgroups. Cross-sectional and longitudinal comparisons of brain structure, cognition, and function were performed, with exploratory brain-behavior correlations over six months. ResultsClustering identified two subgroups with distinct structural patterns. Compared with controls, one subgroup showed reduced gray matter density in cerebellar lobules VIIIa/VIIIb and the putamen (p < 0.05, TFCE-corrected), whereas the other showed no significant alterations. Cognitive differences between clusters did not survive multiple-comparison correction; however, several measures showed medium-to-large effect sizes (d = 0.70-1.01), suggesting meaningful cognitive differences requiring confirmation in larger cohorts. Longitudinal analyses revealed increased medial frontal gray matter density (p < 0.05) associated with visuospatial/executive performance. ConclusionsThese exploratory findings suggest that post-COVID cognitive symptoms are associated with heterogeneous neurobiological profiles rather than a uniform pattern of impairment. Structural alterations involving cerebellar, striatal, and frontal regions may reflect distinct neuroanatomical phenotypes. Longitudinal findings suggest medial frontal structural reorganization with functional relevance. These findings support data-driven stratification for characterizing neurobiological heterogeneity in Long COVID and provide a foundation for future hypothesis-driven studies.

neuroscience↗

bioRxiv2026

Dissecting heterogeneous brain development and aging using voxelwise normative models

Brain disorders are often characterized by biological heterogeneity that is poorly captured by group-average analyses. Normative modeling has emerged as a promising tool to parse out such heterogeneity, yet existing lifespan reference models rely on coarse parcellations, which may obscure individual variability. Using an aggregated reference sample (n=58,597 scans from n=51,107 participants), we provide openly available normative models of brain morphometry at the voxel level across the lifespan, and we illustrate their potential utility with two complementary applications. First, we investigated long-term brain development after preterm birth across two independent cohorts (n=284; n=304) and found individualized, replicable and persistent brain alterations. Second, we extracted high-resolution patient-level morphometric deviations in two samples with rare, genetic neurodegenerative disorders (spinocerebellar ataxia type 1 and 3; n=29, n=15), which showed marked heterogeneity. Together, our findings highlight that voxelwise normative modeling can detect clinically relevant, individualized deviations from a reference model with high spatial precision.

neuroscience↗

bioRxiv2025

A Core Pattern of Cerebellar and Brainstem Degeneration and Reduced Cerebrocerebellar Structural Covariance in Spinocerebellar Ataxia Type 3 (SCA3): MRI Volumetrics from ENIGMA-Ataxia

ObjectiveSpinocerebellar ataxia type 3 (SCA3) is a rare, inherited neurodegenerative disease. Here, we profile the spatial spread of atrophy across the whole brain, determine whether brain degeneration preferentially maps onto specific functional networks, and investigate the relationship between cerebellar and cerebral anatomical changes. MethodsWhole-brain grey and white matter (GM and WM) voxel-based morphometry was performed on 408 individuals with SCA3 (82 pre-ataxic) and 293 controls. The SCA3 cohort was stratified by ataxia severity to investigate disease progression, with cerebellar GM atrophy mapped onto a task-based functional atlas. Volume was correlated with disease duration and intensity. Cerebrocerebellar volumetric covariance was assessed to determine whether atrophy was coupled between infra- and supratentorial regions. ResultsThe pattern of atrophy is spatially consistent but progressive in magnitude across the disease course. The greatest atrophy was found in the pons, cerebellar WM, and cerebellar peduncles; correlations with disease severity and duration were also strongest in these regions. Cerebellar GM atrophy was greatest in functional regions associated with motor execution and planning, attention, and emotional processing. Sparse cerebral cortical atrophy appears only in the most severe disease subgroup, while striatal atrophy begins in the earliest stages. Reduced cerebrocerebellar structural covariance is observed in SCA3 participants versus controls. InterpretationWhile cerebellar and brainstem atrophy become more severe, the pattern of atrophy remains largely consistent as SCA3 progresses. Cerebellar GM degeneration occurs in regions associated with motor, cognitive, and affective control, in line with clinical presentation. Cerebellar atrophy is not directly mirrored by cerebral changes.

neuroscience↗

bioRxiv2025

Functional Connectivity Alterations in Spinocerebellar Ataxia Type 10: Insights from Gray Matter Atrophy

Spinocerebellar ataxia type 10 (SCA10) is a rare, inherited neurological disorder caused by an expansion of the non-coding ATTCT pentanucleotide repeat in the ATAXIN 10 gene. It is characterized by cerebellar ataxia and epilepsy. Previous research has demonstrated extensive white and gray matter degeneration, particularly in the cerebellum. However, the impact of the SCA10 mutation on functional connectivity (FC) remains unexplored. This study aimed to characterize intrinsic FC changes in SCA10 patients and their relationship to clinical manifestations. Structural and resting-state MRIs were obtained from 26 SCA10 patients and 26 control subjects. Voxel-based morphometry (VBM) and seed-ROI and Independent Components Analysis (ICA) were performed to identify cerebral atrophy and FC changes respectively. Additionally, correlation analyses were conducted between FC changes and scores from the Scale for the Assessment and Rating of Ataxia (SARA) and the Montreal Cognitive Assessment (MoCA). In SCA10 patients, VBM analysis revealed extensive gray matter loss in motor cortices and the cerebellum. FC analysis identified significant FC changes originating from seed-ROIs in the right cerebellar VI and left precentral gyrus. Furthermore, group comparison using ICA components showed that SCA10 patients exhibited higher FC in the sensorimotor and cerebellar functional networks. Moreover, the average BOLD signal within the cerebellar network negatively correlated with MoCA scores. In summary, SCA10 patients exhibited enhanced FC in brain regions that displayed gray matter atrophy, underscoring the impact of SCA10 degeneration on resting state networks and induction of potential maladaptive FC compensatory mechanisms.

neuroscience↗

bioRxiv2024

The Pattern and Staging of Brain Atrophy in Spinocerebellar Ataxia Type 2 (SCA2): MRI Volumetrics from ENIGMA-Ataxia

ObjectiveSpinocerebellar ataxia type 2 (SCA2) is a rare, inherited neurodegenerative disease characterised by progressive deterioration in both motor coordination and cognitive function. Atrophy of the cerebellum, brainstem, and spinal cord are core features of SCA2, however the evolution and pattern of whole-brain atrophy in SCA2 remain unclear. We undertook a multi-site, structural magnetic resonance imaging (MRI) study to comprehensively characterize the neurodegeneration profile of SCA2. MethodsVoxel-based morphometry analyses of 110 participants with SCA2 and 128 controls were undertaken to assess groupwise differences in whole-brain volume. Correlations with clinical severity and genotype, and cross-sectional profiling of atrophy patterns at different disease stages, were also performed. ResultsAtrophy in SCA2 relative to controls was greatest (Cohens d>2.5) in the cerebellar white matter (WM), middle cerebellar peduncle, pons, and corticospinal tract. Very large effects (d>1.5) were also evident in the superior cerebellar, inferior cerebellar, and cerebral peduncles. In cerebellar grey matter (GM), large effects (d>0.8) mapped to areas related to both motor coordination and cognitive tasks. Strong correlations (|r|>0.4) between volume and disease severity largely mirrored these groupwise outcomes. Stratification by disease severity showed a degeneration pattern beginning in cerebellar and pontine WM in pre-clinical subjects; spreading to the cerebellar GM and cerebro-cerebellar/corticospinal WM tracts; then finally involving the thalamus, striatum, and cortex in severe stages. InterpretationThe magnitude and pattern of brain atrophy evolves over the course of SCA2, with widespread, non-uniform involvement across the brainstem, cerebellar tracts, and cerebellar cortex; and late involvement of the cerebral cortex and striatum.

neuroscience↗

bioRxiv2017

Hemispheric lateralization of Heschl’s gyrus and amygdala subdivisions are involved in differentiating happy and sad acoustic emotion

Emotion is known to activate different areas of the cortex; nevertheless, how activation represents the variety of emotion is unknown. We asked whether functional activation in Heschls gyrus and amygdala subdivisions could differentiate happy and sad acoustic stimuli. A sparse sampling fMRI paradigm assessing hemispheric laterality by subdivision was employed to investigate this question. Differences between left Heschls gyrus subdivisions Te1.1 and Te1.0 compared to Te1.2 were significant for sad acoustic stimuli and right Heschls gyrus subdivisions Te1.0 different than Te1.1 and Te1.2 for sad acoustic stimuli, with no subdivision specificity for happy greater than sad. A prominent right greater than left difference was notable for centromedial, laterobasal, and superficial amygdala subdivisions for sad, while happy was more bilaterally activated. Activation and deactivation profiles of Heschls gyrus and amygdala subdivisions added to the explanation of left/right asymmetry by emotion with activation profiles significant for Heschls gyrus and amygdala response to sad.

neuroscience↗