The overlap across psychotic disorders: A functional network connectivity analysis.
Int J Psychophysiol
; 201: 112354, 2024 Jul.
Article
in En
| MEDLINE
| ID: mdl-38670348
ABSTRACT
Functional network connectivity (FNC) has previously been shown to distinguish patient groups from healthy controls (HC). However, the overlap across psychiatric disorders such as schizophrenia (SZ), bipolar (BP), and schizoaffective disorder (SAD) is not evident yet. This study focuses on studying the overlap across these three psychotic disorders in both dynamic and static FNC (dFNC/sFNC). We used resting-state fMRI, demographics, and clinical information from the Bipolar-Schizophrenia Network on Intermediate Phenotypes cohort (BSNIP). The data includes three groups of patients with schizophrenia (SZ, N = 181), bipolar (BP, N = 163), and schizoaffective (SAD, N = 130) and HC (N = 238) groups. After estimating each individual's dFNC, we group them into three distinct states. We evaluated two dFNC features, including occupancy rate (OCR) and distance travelled over time. Finally, the extracted features, including both sFNC and dFNC, are tested statistically across patients and HC groups. In addition, we explored the link between the clinical scores and the extracted features. We evaluated the connectivity patterns and their overlap among SZ, BP, and SAD disorders (false discovery rate or FDR corrected p < 0.05). Results showed dFNC captured unique information about overlap across disorders where all disorder groups showed similar pattern of activity in state 2. Moreover, the results showed similar patterns between SZ and SAD in state 1 which was different than BP. Finally, the distance travelled feature of SZ (average R = 0.245, p < 0.01) and combined distance travelled from all disorders was predictive of the PANSS symptoms scores (average R = 0.147, p < 0.01).
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Psychotic Disorders
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Schizophrenia
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Bipolar Disorder
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Magnetic Resonance Imaging
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Connectome
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Nerve Net
Limits:
Adult
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Female
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Humans
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Male
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Middle aged
Language:
En
Journal:
Int J Psychophysiol
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Int. j. psychophysiol
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International journal of psychophysiology
Year:
2024
Document type:
Article
Affiliation country:
Country of publication: