Abstract
BackgroundPathologies of schizophrenia and bipolar disorder have been poorly understood. Brain network analysis could help understand brain mechanisms of schizophrenia and bipolar disorder. This study investigates the source-level brain cortical networks using resting-state electroencephalography (EEG) in patients with schizophrenia and bipolar disorder.MethodsResting-state EEG was measured in 38 patients with schizophrenia, 34 patients with bipolar disorder type I, and 30 healthy controls. Graph theory based source-level weighted functional networks were evaluated: strength, clustering coefficient (CC), path length (PL), and efficiency in six frequency bands.ResultsAt the global level, patients with schizophrenia or bipolar disorder showed higher strength, CC, and efficiency, and lower PL in the theta band, compared to healthy controls. At the nodal level, patients with schizophrenia or bipolar disorder showed higher CCs, mostly in the frontal lobe for the theta band. Particularly, patients with schizophrenia showed higher nodal CCs in the left inferior frontal cortex and the left ascending ramus of the lateral sulcus compared to patients with bipolar disorder. In addition, the nodal-level theta band CC of the superior frontal gyrus and sulcus (cognition-related region) correlated with positive symptoms and social and occupational functioning scale (SOFAS) scores in the schizophrenia group, while that of the middle frontal gyrus (emotion-related region) correlated with SOFAS scores in the bipolar disorder group.ConclusionsAltered cortical networks were revealed and these alterations were significantly correlated with core pathological symptoms of schizophrenia and bipolar disorder. These source-level cortical network indices could be promising biomarkers to evaluate patients with schizophrenia and bipolar disorder.
Highlights
Schizophrenia and bipolar disorder are both major psychiatric disorders
We examined the relationships between cortical network indices and psychiatric, clinical, or cognitive measures, which would help in comprehending the pathologies of schizophrenia and bipolar disorder
The score of the Korean Auditory Verbal Learning Test (K-AVLT)-trial 5 was significantly lower in patients with schizophrenia than in those with bipolar disorder and healthy controls (K-AVLT-trial 5: 8.37 ± 2.79 vs. 10.61 ± 2.97 vs. 11.57 ± 1.75, p < 0.001)
Summary
Schizophrenia is frequently characterized by positive and negative symptoms, whereas bipolar disorder is generally characterized by mania and depression [1]. Schizophrenia and bipolar disorder have both similarities and differences with respect to neuropsychological and neurophysiological levels. They have overlapping symptoms, such as psychotic symptoms, disorganized thinking, and depressive symptoms [2,3,4]. Studies that could help in understanding the pathologies of these two diseases are needed. Pathologies of schizophrenia and bipolar disorder have been poorly understood. Brain network analysis could help understand brain mechanisms of schizophrenia and bipolar disorder. This study investigates the source-level brain cortical networks using resting-state electroencephalography (EEG) in patients with schizophrenia and bipolar disorder
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