PhD Scientific Days 2024

Poster Session C - Mental Health Sciences 1.

Cerebello-Thalamo-Cortical Network Dysconnectivity in Schizophrenia: A Coordinate-Based Meta-Analysis of Neuroimaging Studies

Text of the abstract

Background:
Cerebello-thalamo-cortical (CTC) network dysfunctions have been widely reported in schizophrenia-spectrum disorders. Neuroimaging studies, however, face serious limitations and a replication crisis. Addressing this, we aimed to conduct a rigorous meta-analysis to assess the robustness of dysconnectivity and explore the etiology of CTC network abnormalities in the psychosis-spectrum.
Methods:
Our meta-analysis was preregistered on PROSPERO and followed the PRISMA guideline. A systematic search was conducted in three databases in September 2023. Included articles used seed-based resting-state fMRI in patients with schizophrenia-spectrum disorders, first-episode psychosis, clinical high-risk for psychosis, and healthy control groups. Seeds for connectivity analysis were selected within the thalamus and the cerebellum. For statistical hypothesis testing we employed two coordinate-based meta-analytic methods, Activation Likelihood Estimation (ALE) and Seed-based D Mapping (SDM) to improve the reliability and robustness of our results. Risk of Bias was evaluated rigorously using the recommendations of the OHBM Committee on Best Practice in Data Analysis and Sharing (COBIDAS).
Results:
Significant clusters of thalamic hypoconnectivity in schizophrenia were found in the prefrontal cortex, limbic lobe, thalamus, and cerebellum. Hypoconnectivity in the superior frontal gyrus and the cerebellum was confirmed by both statistical methods. Significant clusters of thalamic hyperconnectivity in schizophrenia were found with both statistical methods in the visual association and the somato-motor areas. Analyses using the cerebellum seed revealed hypoconnectivity in the prefrontal cortex, cerebellum, and thalamus, with hyperconnectivity in the motor cortex, somatosensory cortex, and orbitofrontal cortex, although significance did not survive multiple comparison corrections.
Conclusion:
Our meta-analysis provides robust evidence for CTC network dysfunctions across the psychosis spectrum, confirming reported dysconnectivity convergence with two different statistical approaches. These findings hold promise for the CTC network to be used for individual therapeutic response prediction in psychotic disorders.
Funding: G. Csukly’s work was supported by the Hungarian Research Foundation grants (OTKA FK 138385)