Functional connectivity of the default mode network is associated with prospection in schizophrenia patients and individuals with social anhedonia

Exploring mechanisms of anhedonia in depression through neuroimaging and data-driven approaches

BACKGROUND

Anhedonia is a core symptom of depression that is closely related to prognosis and treatment outcomes. However, accurate and efficient treatments for anhedonia are lacking, mandating a deeper understanding of the underlying mechanisms.

METHODS

A total of 303 patients diagnosed with depression and anhedonia were assessed by the Snaith-Hamilton Pleasure Scale (SHAPS) and magnetic resonance imaging (MRI). The patients were categorized into a low-anhedonia group and a high-anhedonia group using the K-means algorithm. A data-driven approach was used to explore the differences in brain structure and function with different degrees of anhedonia based on MATLAB. A random forest model was used exploratorily to test the predictive ability of differences in brain structure and function on anhedonia in depression.

RESULTS

Structural and functional differences were apparent in several brain regions of patients with depression and high-level anhedonia, including in the temporal lobe, paracingulate gyrus, superior frontal gyrus, inferior occipital gyrus, right insular gyrus, and superior parietal lobule. And changes in these brain regions were significantly correlated with scores of SHAPS.

CONCLUSIONS

These brain regions may be useful as biomarkers that provide a more objective assessment of anhedonia in depression, laying the foundation for precision medicine in this treatment-resistant, relatively poor prognosis group.

Anhedonia Across and Beyond the Schizophrenia Spectrum

Anhedonia refers to the diminished ability to experience pleasure, and is a core feature of schizophrenia (SCZ). The neurocognitive and neural correlates of anhedonia remain elusive. Based on several influential theoretical models for negative symptoms, this selective review proposed four important neurocognitive domains, which may unveil the neurobiological mechanisms of anhedonia. The authors critically reviewed the current evidence regarding value representation of reward, prospection, emotion-behavior decoupling, and belief updating in the Chinese setting, covering both behavioral and neuroimaging research. We observed a limited application of the transdiagnostic approach in previous studies on the four domains, and the lack of adequate measures to tap into the expressivity deficit in SCZ. Despite many behavioral paradigms for these four domains utilized both social and non-social stimuli, previous studies seldom focused on the social-versus-non-social differentiation. We further advocated several important directions for future research.

Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade

BACKGROUND AND HYPOTHESIS

Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, distinguish SZ from healthy conditions or other mental disorders, and explore biotypes within SZ or across SZ and other mental disorders, which aim to promote the accurate diagnosis of SZ. In China, research on SZ using MRI has grown considerably in recent years.

STUDY DESIGN

The article reviews advanced neuroimaging and artificial intelligence (AI) methods using single-modal or multimodal MRI to reveal the mechanism of SZ and promote accurate diagnosis of SZ, with a particular emphasis on the achievements made by Chinese scholars around the past decade.

STUDY RESULTS

Our article focuses on the methods for capturing subtle brain functional and structural properties from the high-dimensional MRI data, the multimodal fusion and feature selection methods for obtaining important and sparse neuroimaging features, the supervised statistical analysis and classification for distinguishing disorders, and the unsupervised clustering and semi-supervised learning methods for identifying neuroimage-based biotypes. Crucially, our article highlights the characteristics of each method and underscores the interconnections among various approaches regarding biomarker extraction and neuroimage-based diagnosis, which is beneficial not only for comprehending SZ but also for exploring other mental disorders.

CONCLUSIONS

We offer a valuable review of advanced neuroimage analysis and AI methods primarily focused on SZ research by Chinese scholars, aiming to promote the diagnosis, treatment, and prevention of SZ, as well as other mental disorders, both within China and internationally.

The Future-oriented Repetitive Thought (FoRT) scale: Validation in Chinese samples and application in the schizophrenia spectrum

BACKGROUND

Repetitive thoughts are usually associated with psychopathology. The Future-oriented Repetitive Thought (FoRT) Scale is a measure designed to capture frequency of repetitive thought about positive and negative future events. However, the validity of the scale in Chinese population and its application in the schizophrenia spectrum have not been examined.

METHODS

The current study aimed to examine the psychometric properties of the Chinese version of the FoRT scale and to apply it to the schizophrenia spectrum. In Study 1, three samples (total N = 1875) of university students were recruited for exploratory factor analysis, confirmatory factor analysis, and validity test, respectively. In Study 2, we identified subsamples with high schizotypal traits (N = 89) and low schizotypal traits (N = 89), and recruited 36 inpatients with schizophrenia and 41 matched healthy controls.

RESULTS

The three-factor (pessimistic repetitive future thinking, repetitive thinking about future goals, and positive indulging about the future) structure of the FoRT scale with one item deleted, fitted the Chinese samples. And the scale could distinguish patients with schizophrenia and individuals with high schizotypal traits from controls.

CONCLUSION

These findings support that the Chinese version of the FoRT scale is a valid tool and provide evidence for the potential applications in the schizophrenia spectrum.

Uncovering the Neural Correlates of Anhedonia Subtypes in Major Depressive Disorder: Implications for Intervention Strategies

Major depressive disorder (MDD) represents a serious public health concern, negatively affecting individuals' quality of life and making a substantial contribution to the global burden of disease. Anhedonia is a core symptom of MDD and is associated with poor treatment outcomes. Variability in anhedonia components within MDD has been observed, suggesting heterogeneity in psychopathology across subgroups. However, little is known about anhedonia subgroups in MDD and their underlying neural correlates across subgroups. To address this question, we employed a hierarchical cluster analysis based on Temporal Experience of Pleasure Scale subscales in 60 first-episode, drug-naive MDD patients and 32 healthy controls. Then we conducted a connectome-wide association study and whole-brain voxel-wise functional analyses for identified subgroups. There were three main findings: (1) three subgroups with different anhedonia profiles were identified using a data mining approach; (2) several parts of the reward network (especially pallidum and dorsal striatum) were associated with anticipatory and consummatory pleasure; (3) different patterns of within- and between-network connectivity contributed to the disparities of anhedonia profiles across three MDD subgroups. Here, we show that anhedonia in MDD is not uniform and can be categorized into distinct subgroups, and our research contributes to the understanding of neural underpinnings, offering potential treatment directions. This work emphasizes the need for tailored approaches in the complex landscape of MDD. The identification of homogeneous, stable, and neurobiologically valid MDD subtypes could significantly enhance our comprehension and management of this multifaceted condition.

Altered brain functional networks in schizophrenia with persistent negative symptoms: an activation likelihood estimation meta-analysis

Objective

To investigate brain structural and functional characteristics of three brain functional networks including default mode network (DMN), central executive network (CEN), and salience network (SN) in persistent negative symptoms (PNS) patients.

Methods

We performed an activation likelihood estimation (ALE) meta-analysis of functional connectivity (FC) studies and voxel-based morphometry (VBM) studies to detect specific structural and functional alterations of brain networks between PNS patients and healthy controls.

Results

Seventeen VBM studies and twenty FC studies were included. In the DMN, PNS patients showed decreased gray matter in the bilateral medial frontal gyrus and left anterior cingulate gyrus and a significant reduction of FC in the right precuneus. Also, PNS patients had a decrease of gray matter in the left inferior parietal lobules and medial frontal gyrus, and a significant reduction of FC in the bilateral superior frontal gyrus in the CEN. In comparison with healthy controls, PNS patients exhibited reduced gray matter in the bilateral insula, anterior cingulate gyrus, left precentral gyrus and right claustrum and lower FC in these brain areas in the SN, including the left insula, claustrum, inferior frontal gyrus and extra-nuclear.

Conclusion

This meta-analysis reveals brain structural and functional imaging alterations in the three networks and the interaction among these networks in PNS patients, which provides neuroscientific evidence for more personalized treatment.Systematic Review RegistrationThe PROSPERO (https://www.crd.york.ac.uk/PROSPERO/, registration number: CRD42022335962).

Resting-State Functional Connectivity Explained Psychotic-like Experiences in the General Population and Partially Generalized to Patients and Relatives

Background

Psychotic-like experiences (PLEs) are considered the subclinical portion of the psychosis continuum. Research suggests that there are resting-state functional connectivity (rsFC) substrates of PLEs, yet it is unclear if the same substrates underlie more severe psychosis. Here, to our knowledge, we report the first study to build a cross-validated rsFC model of PLEs in a large community sample and directly test its ability to explain psychosis in an independent sample of patients with psychosis and their relatives.

Methods

Resting-state FC of 855 healthy young adults from the WU-Minn Human Connectome Project (HCP) was used to predict PLEs with elastic net. An rsFC composite score based on the resulting model was correlated with psychotic traits and symptoms in 118 patients with psychosis, 71 nonpsychotic first-degree relatives, and 45 healthy control subjects from the psychosis HCP.

Results

In the HCP, the cross-validated model explained 3.3% of variance in PLEs. Predictive connections spread primarily across the default, frontoparietal, cingulo-opercular, and dorsal attention networks. The model partially generalized to a younger, but not older, subsample in the psychosis HCP, explaining two measures of positive/disorganized psychotic traits (the Structured Interview for Schizotypy: β = 0.25, pone-tailed = .027; the Schizotypy Personality Questionnaire positive factor: β = 0.14, pone-tailed = .041). However, it did not differentiate patients from relatives and control subjects or explain psychotic symptoms in patients.

Conclusions

Some rsFC substrates of PLEs are shared across the psychosis continuum. However, explanatory power was modest, and generalization was partial. It is equally important to understand shared versus distinct rsFC variances across the psychosis continuum.

Mental time travel in psychiatric disorders

Mental time travel (MTT) refers to the ability to mentally re-experience the past and pre-experience the future. Here we briefly review impairments in MTT, its underlying cognitive and neural mechanisms, and ways to improve MTT in psychiatric patients. Future research directions on MTT are discussed.

Mental time travel for self and others in individuals with a high level of schizotypy

Mental time travel (MTT) is the ability to project oneself to the past or future through mental simulation. Moreover, MTT can involve self-related or other-related information. This study aimed to compare MTT in individuals with high levels of schizotypy and that in their counterparts with low levels of schizotypy. Participants with high (n = 37) and low (n = 37) levels of schizotypy completed an MTT task with four conditions [2 (Condition: self vs. other) × 2 (Time orientation: past vs. future)]. They were required to recall past events that had happened to themselves or to a non-intimate person, and to imagine possible future events that might happen to themselves or to a non-intimate person, related to cue words. Outcome measures included specificity, vividness, sense of experience, emotional valence, emotional intensity, proportion of first-person visual perspective in events, and difficulty in event generation. A 2 (Group: high vs. low levels of schizotypy) × 2 (Condition) × 2 (Time orientation) mixed analysis of variance was conducted on each index. Results showed that self-related MTT was more specific than other-related MTT in low levels of schizotypy participants but not in high levels of schizotypy participants. Participants with a high level of schizotypy reported fewer specific events, and reported events with lower vividness and positive emotion than did those with a low level of schizotypy. Self-related MTT showed higher levels of phenomenological characteristics than did other-related MTT. In conclusion, individuals with a high level of schizotypy have altered MTT, and cannot benefit from the self-advantage effect on the specificity of MTT.

Neuronal dysfunction in individuals at early stage of schizophrenia, A resting-state fMRI study

Schizophrenia has been associated with abnormal intrinsic brain activity, involving various cognitive impairments. Qualitatively similar abnormalities are seen in individuals at ultra-high risk (UHR) for psychosis. In this study, resting-state fMRI (rs-fMRI) data were collected from 44 drug-naïve first-episode schizophrenia (Dn-FES) patients, 48 UHR individuals, and 40 healthy controls (HCs). The fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and functional connectivity (FC), were performed to evaluate resting brain function. A support vector machine (SVM) was applied for classification analysis. Compared to HCs, both clinical groups showed increased fALFF in the central executive network (CEN), decreased ReHo in the ventral visual pathway (VVP) and decreased FC in temporal-sensorimotor regions. Excellent performance was achieved by using fALFF value in distinguishing both FES (sensitivity=83.21%, specificity=80.58%, accuracy=81.37%, p=0.009) and UHR (sensitivity=75.88%, specificity=85.72%, accuracy=80.72%, p<0.001) from HC group. Moreover, the study highlighted the importance of frontal and temporal alteration in the pathogenesis of schizophrenia. However, no fMRI features were observed that could well distinguish Dn-FES from UHR group. To conclude, fALFF in the CEN may provide potential power for identifying individuals at the early stage of schizophrenia and the alteration in the frontal and temporal lobe may be important to these individuals.

Aberrant interhemispheric functional connectivity in major depressive disorder with and without anhedonia

OBJECTIVE

Anhedonia is a core feature of major depressive disorder (MDD), and as a subtype of depression, MDD with anhedonia may have exceptional neurobiological mechanisms. However, the neuropathology of anhedonia in MDD remains unclear. Thus, this study aimed to investigate the brain functional differences between MDD with and without anhedonia.

METHODS

A total of 62 individuals including 22 MDD patients with anhedonia, 20 MDD patients without anhedonia, and 20 healthy controls (HCs) were recruited for this study. All participants underwent 3.0-T functional magnetic resonance imaging scan. Voxel-mirrored homotopic connectivity (VMHC) was employed to quantitatively describe bilateral functional connectivity. Analyses of variance (ANOVA) were performed to obtain brain regions with significant differences among three groups and then post hoc tests were calculated for inter-group comparisons.

RESULTS

The ANOVA revealed significant VMHC differences among three groups in the bilateral middle temporal gyrus (MTG), superior frontal gyrus (SFG), and inferior parietal lobule (IPL) (F = 10.47 ~ 15.09, p &lt; 0.05, AlphaSim corrected). Relative to HCs, MDD with anhedonia showed significantly decreased VMHC in the bilateral MTG (t = -5.368, p &lt; 0.05, AlphaSim corrected), as well as increased VMHC in the bilateral SFG (t = -4.696, p &lt; 0.05, AlphaSim corrected). Compared to MDD without anhedonia, MDD with anhedonia showed significantly decreased VMHC in the bilateral MTG and IPL (t = -5.629 ~ -4.330, p &lt; 0.05, AlphaSim corrected), while increased VMHC in the bilateral SFG (t = 3.926, p &lt; 0.05, AlphaSim corrected). However, no significant difference was found between MDD without anhedonia and HCs.

CONCLUSION

The present findings suggest that MDD with and without anhedonia exhibit different patterns of interhemispheric connectivity. Anhedonia in MDD is related to aberrant interhemispheric connectivity within brain regions involved in the frontal-temporal-parietal circuit.

Decoupling between hub-connected functional connectivity of the social brain network and real-world social network in individuals with social anhedonia

Altered hub regions in brain network have been consistently reported in patients with schizophrenia. However, it is unclear whether similar altered hub regions of the brain would be exhibited in individuals with subclinical features of schizophrenia such as social anhedonia (SA). In this study, we examined the hub regions of resting-state social brain network (SBN) of 35 participants with SA and 50 healthy controls (HC). We further examined the prediction effect of hub-connected FCs with SBN on the real-life social network characteristics. Our findings showed that the right amygdala, left temporal lobe and right media superior frontal gyrus were the hub regions of SBN both in SA and HC groups. In the SA group, the left temporal lobe connected functional connectivity (FC) did not predict social network characteristics, while the other FCs strengthened the association with social network characteristics. These findings were replicated in an independent sample of 33 SA and 32 HC. These findings suggested that the left temporal lobe as one of the hub regions of SBN exhibited the abnormality of their connected FCs in the association with social network characteristics in individuals with SA.

Functional disconnection between subsystems of the default mode network in schizophrenia

BACKGROUND

A dysfunctional default mode network (DMN) has been reported in patients with schizophrenia. However, the stability of the deficits has not been determined across different stages of the disorder.

METHODS

We examined the functional connectivity of the DMN subsystems of 125 patients with first-episode schizophrenia (FES) or recurrent schizophrenia (RES), compared to that of 82 healthy controls. We tested the robustness of the findings in an independent cohort of 158 patients and 39 healthy controls. We performed resting-state functional connectivity analysis, and examined the strength of the connections within and between the three subsystems of the DMN (core, dorsal medial prefrontal cortex [dMPFC], and medial temporal lobe [MTL]). We also analyzed the connectivity correlations to symptoms and illness duration.

RESULTS

We found reduced connectivity strength between the core and MTL subsystems in schizophrenia patients compared to controls, with no differences between the FES and RES patient groups; these findings were validated in the second sample. Schizophrenia patients also showed a significant reduction in connectivity within the MTL and between the dMPFC-MTL subsystems, similarly between FES and RES groups. The connectivity strength within the core subsystem was negatively correlated with clinical symptoms in schizophrenia. There was no significant correlation between the DMN subsystem connectivity and illness duration.

CONCLUSIONS

DMN subsystem connectivity deficits are present in schizophrenia, and the homochronicity of their appearance indicates the trait-like nature of these alterations. The DMN deficit may be useful for early diagnosis, and MTL dysfunction may be a crucial mechanism underlying schizophrenia.

Alterations in Spontaneous Brain Activity in Drug-Naïve First-Episode Schizophrenia: An Anatomical/Activation Likelihood Estimation Meta-Analysis

OBJECTIVE

The etiology of schizophrenia is unknown and is associated with abnormal spontaneous brain activity. There are no consistent results regarding the change in spontaneous brain activity of people with schizophrenia. In this study, we determined the specific changes in the amplitude of low-frequency fluctuation/fractional amplitude of low-frequency fluctuation (ALFF/fALFF) and regional homogeneity (ReHo) in patients with drug-naïve first-episode schizophrenia (Dn-FES).

METHODS

A comprehensive search of databases such as PubMed, Web of Science, and Embase was conducted to find articles on resting-state functional magnetic resonance imaging using ALFF/fALFF and ReHo in schizophrenia patients compared to healthy controls (HCs) and then, anatomical/activation likelihood estimation was performed.

RESULTS

Eighteen eligible studies were included in this meta-analysis. Compared to the spontaneous brain activity of HCs, we found changes in spontaneous brain activity in Dn-FES based on these two methods, mainly including the frontal lobe, putamen, lateral globus pallidus, insula, cerebellum, and posterior cingulate cortex.

CONCLUSION

We found that widespread abnormalities of spontaneous brain activity occur in the early stages of the onset of schizophrenia and may provide a reference for the early intervention of schizophrenia.

Subclinical psychopathology and affective forecasting: Role of in-the-moment feelings

It is important for positive well-being and social engagement to understand how people predict future emotions, an ability known as affective forecasting. However, mechanisms underpinning the change to affective forecasting are not well understood in people with subclinical psychiatric symptoms. The current study differentiated components that comprise affective forecasting and investigated how non-clinical features relate to these. We recruited 319 participants to complete the social affective forecasting task and respond to questionnaires that captured schizotypal and autistic traits as well as depressive symptoms. Associations between affective forecasting and subclinical features were investigated using correlations, regression, and structure equation modeling. Results showed that interpersonal features of schizotypal traits negatively predicted anticipated emotions in positive social conditions via in-the-moment feelings but not via mental simulation. Findings highlight that in-the-moment feelings may be an intervention target to help people who have difficulties with social interactions to anticipate more pleasure for future social events.

Anhedonia in Depression and Schizophrenia: Brain Reward and Aversion Circuits

Anhedonia, which is defined as markedly diminished interest or pleasure, is a prominent symptom of psychiatric disorders, most notably major depressive disorder (MDD) and schizophrenia. Anhedonia is considered a transdiagnostic symptom that is associated with deficits in neural reward and aversion functions. Here, we review the characteristics of anhedonia in depression and schizophrenia as well as shared or disorder-specific anhedonia-related alterations in reward and aversion pathways of the brain. In particular, we highlight that anhedonia is characterized by impairments in anticipatory pleasure and integration of reward-related information in MDD, whereas anhedonia in schizophrenia is associated with neurocognitive deficits in representing the value of rewards. Dysregulation of the frontostriatal circuit and mesocortical and mesolimbic circuit systems may be the transdiagnostic neurobiological basis of reward and aversion impairments underlying anhedonia in these two disorders. Blunted aversion processing in depression and relatively strong aversion in schizophrenia are primarily attributed to the dysfunction of the habenula, insula, amygdala, and anterior cingulate cortex. Furthermore, patients with schizophrenia appear to exhibit greater abnormal activation and extended functional coupling than those with depression. From a transdiagnostic perspective, understanding the neural mechanisms underlying anhedonia in patients with psychiatric disorders may help in the development of more targeted and efficacious treatment and intervention strategies.

Social brain network predicts real-world social network in individuals with social anhedonia

Social anhedonia (SA) impairs social functioning in schizophrenia. Previous evidence suggested that certain brain regions predict longitudinal change of real-world social outcomes, yet previous study designs have failed to capture the corresponding functional connectivity among the brain regions involved. This study measured the real-world social network in 22 pairs of individuals with high and low levels of SA, and followed up them for 21 months. We further explored whether resting-state social brain network characteristics could predict the longitudinal variations of real-world social network. Our results showed that social brain network characteristics could predict the change of real-world social networks in both the high SA and low SA groups. However, the results differed between the two groups, i.e., the topological characteristics of the social brain network predicted real-world social network change in the high SA group; whereas the functional connectivity within the social brain network predicted real-world social network change in the low SA group. Principal component analysis and linear regression analysis on the entire sample showed that the functional connectivity component centered at the right orbital inferior frontal gyrus could best predict social network change. Our findings support the notion that social brain network characteristics could predict social network development.

Changes in Default-Mode Network Associated With Childhood Trauma in Schizophrenia

BACKGROUND

There is considerable evidence of dysconnectivity within the default-mode network (DMN) in schizophrenia, as measured during resting-state functional MRI (rs-fMRI). History of childhood trauma (CT) is observed at a higher frequency in schizophrenia than in the general population, but its relationship to DMN functional connectivity has yet to be investigated.

METHODS

CT history and rs-fMRI data were collected in 65 individuals with schizophrenia and 132 healthy controls. Seed-based functional connectivity between each of 4 a priori defined seeds of the DMN (medial prefrontal cortex, right and left lateral parietal lobes, and the posterior cingulate cortex) and all other voxels of the brain were compared across groups. Effects of CT on functional connectivity were examined using multiple regression analyses. Where significant associations were observed, regression analyses were further used to determine whether variance in behavioral measures of Theory of Mind (ToM), previously associated with DMN recruitment, were explained by these associations.

RESULTS

Seed-based analyses revealed evidence of widespread reductions in functional connectivity in patients vs controls, including between the left/right parietal lobe (LP) and multiple other regions, including the parietal operculum bilaterally. Across all subjects, increased CT scores were associated with reduced prefrontal-parietal connectivity and, in patients, with increased prefrontal-cerebellar connectivity also. These CT-associated differences in DMN connectivity also predicted variation in behavioral measures of ToM.

CONCLUSIONS

These findings suggest that CT history is associated with variation in DMN connectivity during rs-fMRI in patients with schizophrenia and healthy participants, which may partly mediate associations observed between early life adversity and cognitive performance.

Anhedonia Relates to the Altered Global and Local Grey Matter Network Properties in Schizophrenia

Anhedonia is one of the major negative symptoms in schizophrenia and defined as the loss of hedonic experience to various stimuli in real life. Although structural magnetic resonance imaging has provided a deeper understanding of anhedonia-related abnormalities in schizophrenia, network analysis of the grey matter focusing on this symptom is lacking. In this study, single-subject grey matter networks were constructed in 123 patients with schizophrenia and 160 healthy controls. The small-world property of the grey matter network and its correlations with the level of physical and social anhedonia were evaluated using graph theory analysis. In the global scale whole-brain analysis, the patients showed reduced small-world property of the grey matter network. The local-scale analysis further revealed reduced small-world property in the default mode network, salience/ventral attention network, and visual network. The regional-level analysis showed an altered relationship between the small-world properties and the social anhedonia scale scores in the cerebellar lobule in patients with schizophrenia. These results indicate that anhedonia in schizophrenia may be related to abnormalities in the grey matter network at both the global whole-brain scale and local-regional scale.

Behavioral, neuroanatomical, and molecular correlates of resilience and susceptibility to maternal immune activation

Infectious or noninfectious maternal immune activation (MIA) is an environmental risk factor for psychiatric and neurological disorders with neurodevelopmental etiologies. Whilst there is increasing evidence for significant health consequences, the effects of MIA on the offspring appear to be variable. Here, we aimed to identify and characterize subgroups of isogenic mouse offspring exposed to identical MIA, which was induced in C57BL6/N mice by administration of the viral mimetic, poly(I:C), on gestation day 12. Cluster analysis of behavioral data obtained from a first cohort containing >150 MIA and control offspring revealed that MIA offspring could be stratified into distinct subgroups that were characterized by the presence or absence of multiple behavioral dysfunctions. The two subgroups also differed in terms of their transcriptional profiles in cortical and subcortical brain regions and brain networks of structural covariance, as measured by ex vivo structural magnetic resonance imaging (MRI). In a second, independent cohort containing 50 MIA and control offspring, we identified a subgroup of MIA offspring that displayed elevated peripheral production of innate inflammatory cytokines, including IL-1β, IL-6, and TNF-α, in adulthood. This subgroup also showed significant impairments in social approach behavior and sensorimotor gating, whereas MIA offspring with a low inflammatory cytokine status did not. Taken together, our results highlight the existence of subgroups of MIA-exposed offspring that show dissociable behavioral, transcriptional, brain network, and immunological profiles even under conditions of genetic homogeneity. These data have relevance for advancing our understanding of the variable neurodevelopmental effects induced by MIA and for biomarker-guided approaches in preclinical psychiatric research.

Association of rs1059004 polymorphism in the OLIG2 locus with functional brain network in first-episode negative schizophrenia

Schizophrenia has often been viewed as a disorder of connectivity. The single nucleotide polymorphism rs1059004 in the oligodendrocyte lineage transcription factor 2 gene locus has been reported to be associated with schizophrenia. We measured the functional connectivity and functional brain network topology properties in 49 schizophrenic patients and 47 healthy controls. We compared the strength and diversity of the functional connectivity and topological properties of functional networks between different genotypes. The correlations among functional connectivity, topological properties and behavioral performances were also investigated in this study. We found that the connectivity strength of schizophrenic patients carrying the risk A allele was generally decreased whereas connectivity diversity was increased. Regarding topological properties, all groups showed small-world properties, the nodal efficiency showed significant differences in the right precuneus and left middle temporal pole between different genotypes in schizophrenic patients. Moreover, the nodal efficiency in the left middle temporal pole was positively correlated with the neuropsychological assessment battery results of the schizophrenic patients who were homozygous for the C allele. Our results elucidate the contribution of rs1059004 to the functional brain network, and may help enhance the present understanding of the role of risk gene in the functional dysconnectivity of schizophrenia.

Neural correlates of prospection impairments in schizophrenia: Evidence from voxel-based morphometry analysis

Prospection, which has a close relationship with motivation and goal-directed behavior, could be a potential target for alleviating negative symptoms. The present study aimed to examine the structural neural correlates of prospection impairments and the involvement of working memory in prospection in schizophrenia patients. Thirty-seven patients with schizophrenia and 28 healthy controls were recruited and all of them completed a prospection task. Working memory was assessed with the Letter Number Span test. In addition, all participants underwent a structural MRI scan. Voxel-based morphometry (VBM) analysis was used to measure grey matter (GM) volume. We found that in schizophrenia patients, GM loss in the right lateral prefrontal cortex (PFC) and the right ventral medial PFC was correlated with decreased internal details in the prospection task. Moreover, GM volume of the right lateral PFC was found to mediate the relationship between working memory and internal details in these patients. In conclusion, GM loss in the PFC is associated with prospection impairments in schizophrenia patients. Working memory deficits may partially account for prospection impairments in schizophrenia patients.