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Longitudinal Reorganization of Large-Scale Functional Networks in SCA7

Alireza Aleali, Luis Beltrán‐ParrazaliD, Juan Fernández-RuíziD, Carlos Roberto Hernandez-CastilloiD

Abstract

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.

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02 /Specification & Classification

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