Frontiers in psychiatry · 2026
Cerebellar dysconnectivity in schizophrenia spectrum: task-based functional connectivity analysis and cognitive stratification.
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Rosales-Gurmendi Diana S M, Hussain Sadam, de Avila-Armenta Eduardo, Fumagal-González Gerardo A, Garza-Abdala Jorge A, Pedro-Pérez Alma A, Toscano Jasiel, Tamez-Peña Jose G
Аннотация
INTRODUCTION: Schizophrenia is conceptualized as a disorder of brain network dysconnectivity, yet relationships between neural alterations, cognitive deficits, and genetic risk remain unclear.
METHODS: We examined 86 participants: schizophrenia patients (SCZ), unaffected siblings (SCZ-SIB), healthy controls (CON), and control siblings (CON-SIB). We used a multiscale graph-theoretic analysis of task-based fMRI during N-back working memory and unsupervised clinical-cognitive clustering.
RESULTS: We found that reduced cerebellum-sensorimotor (CER-SM) and cerebellum-cingulo-opercular (CER-CO) connectivity during the 1-back condition robustly discriminated SCZ from CON (AUC = 0.89). Critically, these dysconnectivity patterns were linked to clinical state, present in SCZ vs. SCZ-SIB but absent in SCZ-SIB vs. CON-SIB, suggesting illness expression rather than familial risk. Unsupervised clustering revealed three data-driven subtypes with distinct cognitive- symptomatic profiles: subtype 1 with relative preservation of verbal abilities (predominantly controls), subtype 2 with marked fluid cognitive impairment (enriched in SCZ), and subtype 3 with intermediate performance with working memory sparing (mixed composition). Cerebellar-cortical hypoconnectivity showed graded alignment across these profiles.
DISCUSSION: These findings demonstrate that cerebellar dysconnectivity is most detectable under moderate cognitive load, tracks with clinical state, and covaries with transdiagnostic cognitive profiles, advancing circuit-based understanding of schizophrenia heterogeneity.
METHODS: We examined 86 participants: schizophrenia patients (SCZ), unaffected siblings (SCZ-SIB), healthy controls (CON), and control siblings (CON-SIB). We used a multiscale graph-theoretic analysis of task-based fMRI during N-back working memory and unsupervised clinical-cognitive clustering.
RESULTS: We found that reduced cerebellum-sensorimotor (CER-SM) and cerebellum-cingulo-opercular (CER-CO) connectivity during the 1-back condition robustly discriminated SCZ from CON (AUC = 0.89). Critically, these dysconnectivity patterns were linked to clinical state, present in SCZ vs. SCZ-SIB but absent in SCZ-SIB vs. CON-SIB, suggesting illness expression rather than familial risk. Unsupervised clustering revealed three data-driven subtypes with distinct cognitive- symptomatic profiles: subtype 1 with relative preservation of verbal abilities (predominantly controls), subtype 2 with marked fluid cognitive impairment (enriched in SCZ), and subtype 3 with intermediate performance with working memory sparing (mixed composition). Cerebellar-cortical hypoconnectivity showed graded alignment across these profiles.
DISCUSSION: These findings demonstrate that cerebellar dysconnectivity is most detectable under moderate cognitive load, tracks with clinical state, and covaries with transdiagnostic cognitive profiles, advancing circuit-based understanding of schizophrenia heterogeneity.