Evidence map›Paper›PMID 41140643›Full record

SynthesisFrontiers in neuroimaging2025

Aberrant cortical-subcortical-cerebellar connectivity in resting-state fMRI as an imaging marker of schizophrenia and psychosis: a systematic review of data-driven whole-brain functional connectivity analyses.

Kyle M Jensen, Tricia Z King, Pablo Andrés-Camazón, Vince D Calhoun, Armin Iraji

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neuroimaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Kyle M JensenDepartment of Psychology, Georgia State University, Atlanta, GA, United States.
Tricia Z KingNell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, United States.
Pablo Andrés-CamazónInstitute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, ISCIII, School of Medicine, Universidad Complutense, Madrid, Spain.
Vince D CalhounDepartment of Computer Science, Georgia State University, Atlanta, GA, United States.
Armin IrajiDepartment of Computer Science, Georgia State University, Atlanta, GA, United States.

Funding

Data-driven solutions for temporal, spatial, and spatiotemporal dynamic functional connectivityR01MH123610 · NIMH · GEORGIA STATE UNIVERSITY · PI ADALI, TULAY, CALHOUN, VINCE D · 2021 to 2025
$3.1M
Sex-Specific Psychosis Biotypes: Informed Data-driven Neurobiological and Genomic Markers for Early Risk DetectionR01MH136665 · NIMH · GEORGIA STATE UNIVERSITY · PI Jiayu Chen, Armin Iraji · 2025 to 2026
$998k
NIMH NIH HHS R01 MH123610NIMH NIH HHS R01 MH136665
6 · The paper itself

Abstract

Introduction: Schizophrenia is extremely heterogenous, and the underlying brain mechanisms are not fully understood. Many attempts have been made to substantiate and delineate the relationship between schizophrenia and the brain through unbiased exploratory investigations of resting-state functional magnetic resonance imaging (rs-fMRI). The results of numerous data-driven rs-fMRI studies have converged in support of the disconnection hypothesis framework, reporting aberrant connectivity in cortical-subcortical-cerebellar circuitry. However, this model is vague and underspecified, encompassing a vast array of findings across studies. It is necessary to further refine this model to identify consistent patterns and establish stable imaging markers of schizophrenia and psychosis. The organizational structure of the NeuroMark atlas is especially well-equipped for describing functional units derived through independent component analysis (ICA) and uniting findings across studies utilizing data-driven whole-brain functional connectivity (FC) to characterize schizophrenia and psychosis. Methods: Toward this goal, a systematic literature review was conducted on primary empirical articles published in English in peer-reviewed journals between January 2019-February 2025 which utilized cortical-subcortical-cerebellar terminology to describe schizophrenia-control comparisons of whole-brain FC in human rs-fMRI. The electronic databases utilized included Google scholar, PubMed, and APA PsycInfo, and search terms included ("schizophrenia" OR "psychosis") AND "resting-state fMRI" AND ("cortical-subcortical-cerebellar" OR "cerebello-thalamo-cortical"). Results: Ten studies were identified and NeuroMark nomenclature was utilized to describe findings within a common reference space. The most consistent patterns included cerebellar-thalamic hypoconnectivity, cerebellar-cortical (sensorimotor & insular-temporal) hyperconnectivity, subcortical (basal ganglia and thalamic)-cortical (sensorimotor, temporoparietal, insular-temporal, occipitotemporal, and occipital) hyperconnectivity, and cortical-cortical (insular-temporal and occipitotemporal) hypoconnectivity. Discussion: Patterns implicating prefrontal cortex are largely inconsistent across studies and may not be effective targets for establishing stable imaging markers based on static FC in rs-fMRI. Instead, adapting new analytical strategies, or focusing on nodes in the cerebellum, thalamus, and primary motor and sensory cortex may prove to be a more effective approach.

Indexed as

cerebello-thalamo-corticalcortical–subcortical-cerebellardata-drivenfunctional connectivitypsychosisresting-state fMRIschizophreniawhole-brain

Identifiers

PMID41140643
PMCPMC12549315

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.