Resting-state functional hypoconnectivity of amygdala in clinical high risk state and first-episode schizophrenia

Spontaneous Brain Activity Alterations in First-Episode Psychosis: A Meta-analysis of Functional Magnetic Resonance Imaging Studies

BACKGROUND AND HYPOTHESIS

Several studies have shown that spontaneous brain activity, including the total and fractional amplitude of low-frequency fluctuations (LFF) and regional homogeneity (ReHo), is altered in psychosis. Nonetheless, neuroimaging results show a high heterogeneity. For this reason, we gathered the extant literature on spontaneous brain activity in first-episode psychosis (FEP), where the effects of long-term treatment and chronic disease are minimal.

STUDY DESIGN

A systematic research was conducted on PubMed, Scopus, and Web of Science to identify studies exploring spontaneous brain activity and local connectivity in FEP estimated using functional magnetic resonance imaging. 20 LFF and 15 ReHo studies were included. Coordinate-Based Activation Likelihood Estimation Meta-Analyses stratified by brain measures, age (adolescent vs adult), and drug-naïve status were performed to identify spatially-convergent alterations in spontaneous brain activity in FEP.

STUDY RESULTS

We found a significant increase in LFF in FEP compared to healthy controls (HC) in the right striatum and in ReHo in the left striatum. When pooling together all studies on LFF and ReHo, spontaneous brain activity was increased in the bilateral striatum and superior and middle frontal gyri and decreased in the right precentral gyrus and the right inferior frontal gyrus compared to HC. These results were also replicated in the adult and drug-naïve samples.

CONCLUSIONS

Abnormalities in the frontostriatal circuit are present in early psychosis independently of treatment status. Our findings support the view that altered frontostriatal can represent a core neural alteration of the disorder and could be a target of treatment.

Anatomical variations in the insular cortex in individuals at a clinical high-risk state for psychosis and patients with schizophrenia

Introduction

Since the number of insular gyri is higher in schizophrenia patients, it has potential as a marker of early neurodevelopmental deviations. However, it currently remains unknown whether the features of the insular gross anatomy are similar between schizophrenia patients and individuals at risk of psychosis. Furthermore, the relationship between anatomical variations in the insular cortex and cognitive function has not yet been clarified.

Methods

The gross anatomical features (i.e., the number of gyri and development pattern of each gyrus) of the insular cortex were examined using magnetic resonance imaging, and their relationships with clinical characteristics were investigated in 57 subjects with an at-risk mental state (ARMS) and 63 schizophrenia patients in comparison with 61 healthy controls.

Results

The number of insular gyri bilaterally in the anterior subdivision was higher in the ARMS and schizophrenia groups than in the control group. The schizophrenia group was also characterized by a higher number of insular gyri in the left posterior subdivision. A well-developed right middle short insular gyrus was associated with symptom severity in first-episode schizophrenia patients, whereas chronic schizophrenia patients with a well-developed left accessory gyrus were characterized by less severe cognitive impairments in motor and executive functions. The features of the insular gross anatomy were not associated with clinical characteristics in the ARMS group.

Discussion

The features of the insular gross anatomy that were shared in the ARMS and schizophrenia groups may reflect a vulnerability to psychosis that may be attributed to anomalies in the early stages of neurodevelopment. However, the contribution of the insular gross anatomy to the clinical characteristics of schizophrenia may differ according to illness stages.

Amygdala signal abnormality and cognitive impairment in drug-naïve schizophrenia

BACKGROUND

Recently studies had showed that the amygdala may take part in the cognitive impairment in schizophrenia (SC). However, the mechanism is still unclear, so we explored the relationship between the amygdala resting state magnetic resonance imaging (rsMRI) signal and cognitive function, to provide a reference for the follow-up study.

METHODS

We collected 59 drug-naïve SCs and 46 healthy controls (HCs) from the Third People's Hospital of Foshan. The rsMRI technique and automatic segmentation tool were used to extract the volume and functional indicators of the SC's amygdala. The Positive and Negative Syndrome Scale (PANSS) was used to assess the severity of the disease, and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was used to assess cognitive function. Pearson correlation analysis was used to compare the relationship between the structural and functional indicators of the amygdala and PANSS and RBANS.

RESULTS

(1) There was no significant difference between SC and HC in age, gender and years of education. Compared with HC, the PANSS score of SC increased and the RBANS score decreased significantly. Meanwhile, the left amygdala volume decreased (t=-3.675, p < 0.001), and the Fractional amplitude of low-frequency fluctuations (FALFF) values of bilateral amygdala increased (t_L=3.916, p < 0.001; t_R=3.131, p = 0.002). (2) The volumes of the left amygdala were negatively correlated with the PANSS score (r_L=-0.243, p = 0.039). While the FALFF values of the bilateral amygdala were positively correlated with the PANSS score (r_L=0.257, p = 0.026; r_R=0.259, p = 0.026). Bilateral amygdala volumes and FALFF values were positively correlated (r_L=0.445, p < 0.001; r_R=0.326, p = 0.006) and negatively correlated with RBANS score (r_L=-0.284, p = 0.014; r_R=-0.272, p = 0.020), respectively.

CONCLUSION

The abnormal volume and function of the amygdala play important roles in the disease process of SC, and are closely related to cognitive impairment.

Abnormal amygdala functional connectivity and deep learning classification in multifrequency bands in autism spectrum disorder: A multisite functional magnetic resonance imaging study

Previous studies have explored resting-state functional connectivity (rs-FC) of the amygdala in patients with autism spectrum disorder (ASD). However, it remains unclear whether there are frequency-specific FC alterations of the amygdala in ASD and whether FC in specific frequency bands can be used to distinguish patients with ASD from typical controls (TCs). Data from 306 patients with ASD and 314 age-matched and sex-matched TCs were collected from 28 sites in the Autism Brain Imaging Data Exchange database. The bilateral amygdala, defined as the seed regions, was used to perform seed-based FC analyses in the conventional, slow-5, and slow-4 frequency bands at each site. Image-based meta-analyses were used to obtain consistent brain regions across 28 sites in the three frequency bands. By combining generative adversarial networks and deep neural networks, a deep learning approach was applied to distinguish patients with ASD from TCs. The meta-analysis results showed frequency band specificity of FC in ASD, which was reflected in the slow-5 frequency band instead of the conventional and slow-4 frequency bands. The deep learning results showed that, compared with the conventional and slow-4 frequency bands, the slow-5 frequency band exhibited a higher accuracy of 74.73%, precision of 74.58%, recall of 75.05%, and area under the curve of 0.811 to distinguish patients with ASD from TCs. These findings may help us to understand the pathological mechanisms of ASD and provide preliminary guidance for the clinical diagnosis of ASD.

Prefrontal modulation of frustration-related physiology in preschool children ranging from low to severe irritability

Limbic-prefrontal connectivity during negative emotional challenges underpins a wide range of psychiatric disorders, yet the early development of this system is largely unknown due to difficulties imaging young children. Functional Near-Infrared Spectroscopy (fNIRS) has advanced an understanding of early emotion-related prefrontal activation and psychopathology, but cannot detect activation below the outer cortex. Galvanic skin response (GSR) is a sensitive index of autonomic arousal strongly influenced by numerous limbic structures. We recorded simultaneous lateral prefrontal cortex (lPFC) activation via fNIRS and GSR in 73 3- to 5-year-old children, who ranged from low to severe levels of irritability, during a frustration task. The goal of the study was to test how frustration-related PFC activation modulated psychophysiology in preschool children, and whether associations were moderated by irritability severity. Results showed lPFC activation significantly increased, and GSR levels significantly decreased, as children moved from frustration to rest, such that preschoolers with the highest activation had the steepest recovery. Further, this relation was moderated by irritability such that children with severe irritability showed no association between lPFC activation and GSR. Results suggest functional connections between prefrontal and autonomic nervous systems are in place early in life, with evidence of lPFC down-regulation of frustration-based stress that is altered in early psychopathology. Combining fNIRS and GSR may be a promising novel approach for inferring limbic-PFC processes that drive early emotion regulation and psychopathology.

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Low to high irritable preschoolers tolerated simultaneous fNIRS and GSR recording.

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Frustration-related lPFC activation predicted steeper GSR recovery.

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Irritability moderated the association between lPFC activation and GSR recovery.

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Preschoolers with high irritability showed no lPFC-GSR association.

Baseline global brain structural and functional alterations at the time of symptom onset can predict subsequent cognitive deterioration in drug-naïve first-episode schizophrenia patients: Evidence from a follow-up study

Alterations in the global brain gray matter volume (gGMV) and global functional connectivity density (gFCD) play a pivotal role in the cognitive impairment and further deterioration in schizophrenia. This study aimed to assess the correlation between alterations in the gGMV and gFCD at baseline (ΔgGMV and ΔgFCD), and the subsequent alterations of cognitive function in schizophrenia patients after 2-year antipsychotic treatment. Global-brain magnetic resonance imaging scans were acquired from 877 drug-naïve, first-episode schizophrenia patients at baseline and after two years of antipsychotic treatment with adequate dosage and duration, and 200 healthy controls. According to ΔgGMV at baseline, schizophrenia patients were divided into mild, moderate, and severe alteration groups. The MATRICS consensus cognitive battery and Global Deficit Score (GDS) were used to assess cognitive impairment. We found that ΔgGMV and ΔgFCD at baseline were significantly correlated with the severity of the cognitive deterioration (ΔGDS). The correlation coefficient indicated a significant positive correlation between baseline ΔgFCD and subsequent cognitive deterioration, with a relatively stronger relation in the mild alteration group (r = 0.31). In addition, there was a significant positive correlation between baseline ΔgGMV and subsequent cognitive deterioration, with a stronger relation in the moderate and severe alteration groups (r = 0.303; r = 0.302, respectively). Our results showed that ΔgGMV and ΔgFCD are correlated with the severity of cognitive deterioration after completion of a 2-year antipsychotic treatment in schizophrenia patients. These findings suggest that baseline alterations in gGMV and gFCD hold potential for predicting subsequent cognitive decline in schizophrenia.

Effective Connectivity between Major Nodes of the Limbic System, Salience and Frontoparietal Networks Differentiates Schizophrenia and Mood Disorders from Healthy Controls

This study was conducted to examine whether there are quantitative or qualitative differences in the connectome between psychiatric patients and healthy controls and to delineate the connectome features of major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BD), as well as the severity of these disorders. Toward this end, we performed an effective connectivity analysis of resting state functional MRI data in these three patient groups and healthy controls. We used spectral Dynamic Causal Modeling (spDCM), and the derived connectome features were further subjected to machine learning. The results outlined a model of five connections, which discriminated patients from controls, comprising major nodes of the limbic system (amygdala (AMY), hippocampus (HPC) and anterior cingulate cortex (ACC)), the salience network (anterior insula (AI), and the frontoparietal and dorsal attention network (middle frontal gyrus (MFG), corresponding to the dorsolateral prefrontal cortex, and frontal eye field (FEF)). Notably, the alterations in the self-inhibitory connection of the anterior insula emerged as a feature of both mood disorders and SCZ. Moreover, four out of the five connectome features that discriminate mental illness from controls are features of mood disorders (both MDD and BD), namely the MFG→FEF, HPC→FEF, AI→AMY, and MFG→AMY connections, whereas one connection is a feature of SCZ, namely the AMY→SPL connectivity. A large part of the variance in the severity of depression (31.6%) and SCZ (40.6%) was explained by connectivity features. In conclusion, dysfunctions in the self-regulation of the salience network may underpin major mental disorders, while other key connectome features shape differences between mood disorders and SCZ, and can be used as potential imaging biomarkers.

Hypothesis of subcortical visual pathway impairment in schizophrenia

Schizophrenia is a severe mental disease involving both neurological and psychiatric abnormalities. Previous studies mainly focus on damage to high-order cognitive dysfunction, which is related to high-level cortical regions such as the prefrontal and temporal lobes. Recent research reveals that impairment of low-level sensory processing occurs in the early stage of schizophrenia, which may be due to impairment of the subcortical magnocellular visual pathway. Moreover, the structure and function of some important nuclei in a subcortical visual pathway are reported to be abnormal in patients with schizophrenia. Inspired by the above evidence, we propose a hypothesis that impairment of the Superior Colliculus-Pulvinar-Amygdala subcortical visual pathway may be involved in the pathological mechanisms of early stages of schizophrenia. And we propose a possible method to detect dysfunction of this subcortical pathway through examining topological processing, which may help early diagnosis of schizophrenia.

Disrupted Intersubject Variability Architecture in Functional Connectomes in Schizophrenia

Schizophrenia (SCZ) is a highly heterogeneous disorder with remarkable intersubject variability in clinical presentations. Previous neuroimaging studies in SCZ have primarily focused on identifying group-averaged differences in the brain connectome between patients and healthy controls (HCs), largely neglecting the intersubject differences among patients. We acquired whole-brain resting-state functional MRI data from 121 SCZ patients and 183 HCs and examined the intersubject variability of the functional connectome (IVFC) in SCZ patients and HCs. Between-group differences were determined using permutation analysis. Then, we evaluated the relationship between IVFC and clinical variables in SCZ. Finally, we used datasets of patients with bipolar disorder (BD) and major depressive disorder (MDD) to assess the specificity of IVFC alteration in SCZ. The whole-brain IVFC pattern in the SCZ group was generally similar to that in HCs. Compared with the HC group, the SCZ group exhibited higher IVFC in the bilateral sensorimotor, visual, auditory, and subcortical regions. Moreover, altered IVFC was negatively correlated with age of onset, illness duration, and Brief Psychiatric Rating Scale scores and positively correlated with clinical heterogeneity. Although the SCZ shared altered IVFC in the visual cortex with BD and MDD, the alterations of IVFC in the sensorimotor, auditory, and subcortical cortices were specific to SCZ. The alterations of whole-brain IVFC in SCZ have potential implications for the understanding of the high clinical heterogeneity of SCZ and the future individualized clinical diagnosis and treatment of this disease.