Relationships between abnormal neural activities and cognitive impairments in patients with drug-naive first-episode schizophrenia

Abstract

Background: Prior resting state functional magnetic resonance imaging studies via the regional homogeneity (ReHo) method have demonstrated inconsistent and conflicting results because of several confounding factors, such as small sample size, medicinal influence, and illness duration.Relationships between ReHo measures and cognitive impairments in patients with drug-naive firstepisode schizophrenia (dn-FES) are rarely reported. This study was conducted to explore the correlations between ReHo measures, cognitive deficits, and clinical symptoms in patients with dn- FES.Methods: A total of 69 patients with dn-FES and 74 healthy controls were recruited. MATRICS Consensus Cognitive Battery (MCCB), Wechsler Adult Intelligence Scale (WAIS), and Positive and Negative Syndrome Scale (PANSS) were used to assess cognitive function, intelligence quotient (IQ), and clinical symptoms, respectively. The correlations between ReHo map and cognitive deficits, the severity of symptoms were examined using strict correlation analyses within brain areas. Results:The ReHo values in the right middle frontal gyrus (MFG) and the superior frontal gyrus (SFG) increased in the dn-FES group, whereas the ReHo values in the right cuneus decreased. Correlation analysis showed that the ReHo values in the right MFG were positively correlated with attention/vigilance impairments, social cognition deficits, the severity of clinical manifestations. Conclusions:These findings suggested that abnormal spontaneous activities in the right MFG reflect the illness severity and cognitive deficits, which serves as a basis for establishing the objective diagnostic markers and might be a clinical intervention target for patients with schizophrenia.

Neuroimaging biomarkers for detecting schizophrenia: A resting-state functional MRI-based radiomics analysis

“…Previous studies have mostly used group-level comparison analysis ( Lu et al., 2021 ; Xue et al., 2019 ; Yan et al., 2020 ; Zhao et al., 2018b ) or machine learning ( Bohaterewicz et al., 2020 ; Li et al., 2019a , 2020 ) to evaluate the spontaneous neural activity abnormalities of SZ patients. This study was the first that we are aware of to apply a radiomics-based machine learning method with DC and VMHC metrics to detect SZ potential biomarkers and explore the potential biological mechanism of SZ.…”

“…In this study, many brain regions showing abnormalities in VMHC belong to the default mode network (DMN), such as MTG and MFG. Recently, a growing body of literature has assessed the crucial roles of disrupted DMN connectivity and abnormal brain activity in the neural mechanisms underlying SZ and DMN disturbances are closely associated with SZ psychopathology and cognitive impairment ( Gong et al., 2020 ; Hu et al., 2017 ; Mingoia et al., 2012 ; Schneider et al., 2011 ; Shan et al., 2021 ; Wen et al., 2021 ; Yan et al., 2020 ; Zhao et al., 2018b , 2019 ). The amygdala, hippocampus, FuG, and PhG are important parts of the limbic system, which regulates instinctive, cognitive, and emotional behavior.…”