Through exploring the abnormalities of EEG microstates in FE-SCH, we found that, compared with HCs, the occurrence, duration, and contribution of microstate class C significantly increased, and the occurrence and contribution of microstate class D significantly decreased in patients with FE-SCH. For the relationship between clinical symptoms and EEG microstates, we found that the score of PANSS positive symptoms was negatively correlated with the occurrence of microstate class D.
Our study found increased microstate class C and decreased microstate class D in patients with FE-SCH, which is consistent with some previous studies [19, 26, 31]. Such abnormalities of microstate class C and D have been identified in patients with chronic schizophrenia [21, 32], individuals with ultra-high risk for psychosis [33, 34], and even siblings of patients with schizophrenia [26]. Two meta-analyses [25, 26] published in recent years showed similar results that the occurrence of microstate class C increased and the occurrence of microstate class D decreased in patients with schizophrenia. Furthermore, some researchers have proposed the dynamics of resting-state EEG microstates, especially for microstate classes C and D, as the potential endophenotype of schizophrenia [25, 26].
Studies combining functional Magnetic Resonance Imaging (fMRI) and EEG showed that the characteristics of microstates overlapped with those of resting-state networks identified using fMRI [35–37], indicating that microstates might be closely related to resting-state functional networks. It has been found that microstate class C is closely related to the default mode network [35], which consists of the medial prefrontal, parietal, and temporal cortices [38]. Default mode network is the neural basis of ego [39]; it was found to be activated during internally-oriented mental processes and to play an important role in self-referential thoughts and episodic memory extraction [16, 40]. The microstate class C might be generated at the bilateral medial temporal gyrus and the lateral parietal lobe [32], which were found to be associated with self-experience in fMRI studies [41, 42]. It was also considered that microstate class C was associated with the activation of the default mode network [16, 35], the abnormal activation of which has been repeatedly demonstrated in schizophrenia [43, 44]. Therefore, the increase of microstate class C might explain the abnormalities in self-focus and the self-experience in schizophrenia.
Microstate class D was found to be associated with the dorsal attention network [35]. The source of microstate class D was located in the frontoparietal area [45], which was associated with the successful execution of attention-related tasks [46] and was extensively interconnected with both default mode and dorsal attention networks [47]. Attention deficit has been regarded as one of the prominent symptoms of schizophrenia. Numerous studies revealed that patients with schizophrenia had obvious deficits in information processing under conditions of high processing load and distraction [46, 48]. In fact, patients with schizophrenia demonstrated frontal lobe dysfunction [49], as well as reduced interaction and functional integration between the prefrontal cortex and other cortical and subcortical brain structures [9], which might result in the imbalance of neural activities of different sites. Therefore, the decrease of microstate class D might suggest impaired function of the frontoparietal and dorsal attention networks in schizophrenia.
Some studies on event-related potential found that microstates were associated with specific functions of information processing [50, 51]. Microstate class C and D were found to be associated with higher and lower attention levels, respectively. Therefore, we may infer that increased microstate class C and decreased microstate class D in patients with FE-SCH in this study might indicate an abnormal state of attention distribution. These microstate abnormalities has been explained in a meta-analysis as an imbalance between processes involving saliency and processes that integrate contextual information [25]. Moreover, Kikuchi et al.[20] found that successful antipsychotic treatment not only mitigated attention and executive control impairments in schizophrenia, but also regulated the patterns of microstate class C and D.
No difference was found in microstates class A and B between the two groups. Although some studies found abnormalities of these two microstate classes [31, 46], conclusion cannot be reached with the existing literature due to the heterogeneity of studies. Two meta-analyses [25, 26] showed consistent results that there was no significant difference in the parameters of microstate A and B between patients with schizophrenia and HCs. Therefore, these two microstate classes might be of limited significance in the identification of FE-SCH.
Regarding the relationship between clinical symptoms and EEG microstates, we found that the score of PANSS positive symptoms was negatively correlated with the occurrence of microstate class D. To date, there have been consistent findings about the relationship between microstate class D and positive psychotic symptoms [18, 19, 25]. A study found that the duration of microstate class D was negatively correlated with the score of paranoid-hallucinatory syndromes [46]. Compared with HCs, the duration of microstate class D was shorter in those with schizophrenia [19], and this effect was particularly significant in patients with acute experience of hallucinations [18]. Apart from microstate class D, microstate classes C and A were also demonstrated to be associated with positive symptoms in several studies. A study involving individuals with high risk for schizophrenia found positive association between microstate class C and positive psychotic symptoms [34], but this result has not been reproduced in studies of FE-SCH. As for microstate class A, a study found that it was positively associated with the score of PANSS positive symptoms in patients with first-episode psychosis [27], but in another study, positive association was present with negative symptoms [23].
Microstate class D was found to be associated with the reduction of positive symptoms. A study found that the indication of its occurrence was similar to the adjustment of strategy when erroneous processing occurred [18, 52]. The positive symptoms might be related to the attribution of internally-generated speech error to external source, and decreased occurrence of microstate class D might be associated with decreased ability to correct such errors. In addition, decreased occurrence of microstate class D might also be related to decreased activation of dorsal attention network in patients, leading to focal attention impairments and the co-activation of functionally incompatible networks [18], thereby resulting in positive symptoms.
Some limitations need to be mentioned in this study. First, this is a cross-sectional study, which precluded us to assess the severity and progression of the disease. Second, our study still shares the common shortcoming of a small sample size with many previous studies. Due to possible sampling error and disease heterogeneity, a small sample might produce insignificance or even opposite effects, thereby leading to inaccurate conclusions. Therefore, the sample needs to be expanded in future works. Third, this study only included the four main microstate classes, which could not cover the overall variance; thus, more microstate classes need to be included in future works for better explanation of the total variance. However, the analysis of the four major microstate classes allows us to compare our findings with previous evidence directly. With 79% of the overall variance explained by the four microstate classes, our this method is proper to produce relatively objective results.