Disrupted resting-state functional connectivity in minimally treated chronic schizophrenia

The impact of indirect structure on functional connectivity in schizophrenia using a multiplex brain network

It is known that abnormal functional connectivity (FC) in schizophrenia (SZ) is closely related to structural connectivity (SC). We speculate that indirect SC also have an impact on FC in SZ patients. Conventional single-layer network has limitations for studying the relationship between indirect SC and FC. Thus, this study constructed a multiplex network based on structural connectivity and functional connectivity (SC-FC). The SC-FC bandwidth and SC-FC cost are used to analyze the impact of indirect SC on FC. Moreover, this paper proposed mediation ability, mediation cost, mediated strength and mediated cost to quantify the effects of mediator nodes and mediated nodes on indirect SC. The results show that SZ patients exhibit lower SC-FC bandwidth and SC-FC cost compared to healthy controls (HC), which could be caused by the limbic and subcortical network (LSN), default mode network (DMN) and visual network (VN). The mediator and mediated nodes in indirect SC of SZ patients also showed diminished effects. These findings suggest that functional communication ability and cost in SZ patients are influenced by indirect SC. This study provides new perspectives for understanding the relationship between indirect SC and FC, and provides strong evidence for interpreting the physiological mechanisms of SZ patients.

Neurostructural, Neurofunctional, and Clinical Features of Chronic, Untreated Schizophrenia: A Narrative Review

Studies of individuals with chronic, untreated schizophrenia (CUS) can provide important insights into the natural course of schizophrenia and how antipsychotic pharmacotherapy affects neurobiological aspects of illness course and progression. We systematically review 17 studies on the neuroimaging, cognitive, and epidemiological aspects of CUS individuals. These studies were conducted at the Shanghai Mental Health Center, Institute of Mental Health at Peking University, and Huaxi MR Research Center between 2013 and 2021. CUS is associated with cognitive impairment, severe symptoms, and specific demographic characteristics and is different significantly from those observed in antipsychotic-treated individuals. Furthermore, CUS individuals have neurostructural and neurofunctional alterations in frontal and temporal regions, corpus callosum, subcortical, and visual processing areas, as well as default-mode and somatomotor networks. As the disease progresses, significant structural deteriorations occur, such as accelerated cortical thinning in frontal and temporal lobes, greater reduction in fractional anisotropy in the genu of corpus callosum, and decline in nodal metrics of gray mater network in thalamus, correlating with worsening cognitive deficits and clinical outcomes. In addition, striatal hypertrophy also occurs, independent of antipsychotic treatment. Contrasting with the negative neurostructural and neurofunctional effects of short-term antipsychotic treatment, long-term therapy frequently results in significant improvements. It notably enhances white matter integrity and the functions of key subcortical regions such as the amygdala, hippocampus, and striatum, potentially improving cognitive functions. This narrative review highlights the progressive neurobiological sequelae of CUS, the importance of early detection, and long-term treatment of schizophrenia, particularly because treatment may attenuate neurobiological deterioration and improve clinical outcomes.

A connectome-wide association study of altered functional connectivity in schizophrenia based on resting-state fMRI

BACKGROUND

Aberrant resting-state functional connectivity is a neuropathological feature of schizophrenia (SCZ). Prior investigations into functional connectivity abnormalities have primarily employed seed-based connectivity analysis, necessitating predefined seed locations. To address this limitation, a data-driven multivariate method known as connectome-wide association study (CWAS) has been proposed for exploring whole-brain functional connectivity.

METHODS

We conducted a CWAS analysis involving 46 patients with SCZ and 40 age- and sex-matched healthy controls. Multivariate distance matrix regression (MDMR) was utilized to identify key nodes in the brain. Subsequently, we conducted a follow-up seed-based connectivity analysis to elucidate specific connectivity patterns between regions of interest (ROIs). Additionally, we explored the spatial correlation between changes in functional connectivity and underlying molecular architectures by examining correlations between neurotransmitter/transporter distribution densities and functional connectivity.

RESULTS

MDMR revealed the right medial frontal gyrus and the left calcarine sulcus as two key nodes. Follow-up analysis unveiled hypoconnectivity between the right medial frontal superior gyrus and the right fusiform gyrus, as well as hypoconnectivity between the left calcarine sulcus and the right lingual gyrus in SCZ. Notably, a significant association between functional connectivity strength and positive symptom severity was identified. Furthermore, altered functional connectivity patterns suggested potential dysfunctions in the dopamine, serotonin, and gamma-aminobutyric acid systems.

CONCLUSIONS

This study elucidated reduced functional connectivity both within and between the medial frontal regions and the occipital cortex in patients with SCZ. Moreover, it indicated potential alterations in molecular architecture, thereby expanding current knowledge regarding neurobiological changes associated with SCZ.

Right superior frontal gyrus: A potential neuroimaging biomarker for predicting short-term efficacy in schizophrenia

Antipsychotic drug treatment for schizophrenia (SZ) can alter brain structure and function, but it is unclear if specific regional changes are associated with treatment outcome. Therefore, we examined the effects of antipsychotic drug treatment on regional grey matter (GM) density, white matter (WM) density, and functional connectivity (FC) as well as associations between regional changes and treatment efficacy. SZ patients (n = 163) and health controls (HCs) (n = 131) were examined by structural magnetic resonance imaging (sMRI) at baseline, and a subset of SZ patients (n = 77) were re-examined after 8 weeks of second-generation antipsychotic treatment to assess changes in regional GM and WM density. In addition, 88 SZ patients and 81 HCs were examined by resting-state functional MRI (rs-fMRI) at baseline and the patients were re-examined post-treatment to examine FC changes. The Positive and Negative Syndrome Scale (PANSS) and MATRICS Consensus Cognitive Battery (MCCB) were applied to measure psychiatric symptoms and cognitive impairments in SZ. SZ patients were then stratified into response and non-response groups according to PANSS score change (≥50 % decrease or <50 % decrease, respectively). The GM density of the right cingulate gyrus, WM density of the right superior frontal gyrus (SFG) plus 5 other WM tracts were reduced in the response group compared to the non-response group. The FC values between the right anterior cingulate and paracingulate gyrus and left thalamus were reduced in the entire SZ group (n = 88) after treatment, while FC between the right inferior temporal gyrus (ITG) and right medial superior frontal gyrus (SFGmed) was increased in the response group. There were no significant changes in regional FC among the non-response group after treatment and no correlations with symptom or cognition test scores. These findings suggest that the right SFG is a critical target of antipsychotic drugs and that WM density and FC alterations within this region could be used as potential indicators in predicting the treatment outcome of antipsychotics of SZ.

Impaired large-scale cortico-hippocampal network connectivity, including the anterior temporal and posterior medial systems, and its associations with cognition in patients with first-episode schizophrenia

Background and objective

The cortico-hippocampal network is an emerging neural framework with striking evidence that it supports cognition in humans, especially memory; this network includes the anterior temporal (AT) system, the posterior medial (PM) system, the anterior hippocampus (aHIPPO), and the posterior hippocampus (pHIPPO). This study aimed to detect aberrant patterns of functional connectivity within and between large-scale cortico-hippocampal networks in first-episode schizophrenia patients compared with a healthy control group via resting-state functional magnetic resonance imaging (rs-fMRI) and to explore the correlations of these aberrant patterns with cognition.

Methods

A total of 86 first-episode, drug-naïve schizophrenia patients and 102 healthy controls (HC) were recruited to undergo rs-fMRI examinations and clinical evaluations. We conducted large-scale edge-based network analysis to characterize the functional architecture of the cortico-hippocampus network and investigate between-group differences in within/between-network functional connectivity. Additionally, we explored the associations of functional connectivity (FC) abnormalities with clinical characteristics, including scores on the Positive and Negative Syndrome Scale (PANSS) and cognitive scores.

Results

Compared with the HC group, schizophrenia patients exhibited widespread alterations to within-network FC of the cortico-hippocampal network, with decreases in FC involving the precuneus (PREC), amygdala (AMYG), parahippocampal cortex (PHC), orbitofrontal cortex (OFC), perirhinal cortex (PRC), retrosplenial cortex (RSC), posterior cingulate cortex (PCC), angular gyrus (ANG), aHIPPO, and pHIPPO. Schizophrenia patients also showed abnormalities in large-scale between-network FC of the cortico-hippocampal network, in the form of significantly decreased FC between the AT and the PM, the AT and the aHIPPO, the PM and the aHIPPO, and the aHIPPO and the pHIPPO. A number of these signatures of aberrant FC were correlated with PANSS score (positive, negative, and total score) and with scores on cognitive test battery items, including attention/vigilance (AV), working memory (WM), verbal learning and memory (Verb_Lrng), visual learning and memory (Vis_Lrng), reasoning and problem-solving (RPS), and social cognition (SC).

Conclusion

Schizophrenia patients show distinct patterns of functional integration and separation both within and between large-scale cortico-hippocampal networks, reflecting a network imbalance of the hippocampal long axis with the AT and PM systems, which regulate cognitive domains (mainly Vis_Lrng, Verb_Lrng, WM, and RPS), and particularly involving alterations to FC of the AT system and the aHIPPO. These findings provide new insights into the neurofunctional markers of schizophrenia.

Sparse non-convex regularization based explainable DBN in the analysis of brain abnormalities in schizophrenia

Deep belief networks have been widely used in medical image analysis. However, the high-dimensional but small-sample-size characteristic of medical image data makes the model prone to dimensional disaster and overfitting. Meanwhile, the traditional DBN is driven by performance and ignores the explainability which is important for medical image analysis. In this paper, a sparse non-convex based explainable deep belief network is proposed by combining DBN with non-convex sparsity learning. For sparsity, the non-convex regularization and Kullback-Leibler divergence penalty are embedded into DBN to obtain the sparse connection and sparse response representation of the network. It effectively reduces the complexity of the model and improves the generalization ability of the model. Considering explainability, the crucial features for decision-making are selected through the feature back-selection based on the row norm of each layer's weight after network training. We apply the model to schizophrenia data and demonstrate it achieves the best performance among several typical feature selection models. It reveals 28 functional connections highly correlated with schizophrenia, which provides an effective foundation for the treatment and prevention of schizophrenia and methodological assurance for similar brain disorders.

Severity-dependent functional connectome and the association with glucose metabolism in the sensorimotor cortex of Parkinson's disease

Functional MRI studies have achieved promising outcomes in revealing abnormal functional connectivity in Parkinson's disease (PD). The primary sensorimotor area (PSMA) received a large amount of attention because it closely correlates with motor deficits. While functional connectivity represents signaling between PSMA and other brain regions, the metabolic mechanism behind PSMA connectivity has rarely been well established. By introducing hybrid PET/MRI scanning, the current study enrolled 33 advanced PD patients during medication-off condition and 25 age-and-sex-matched healthy controls (HCs), aiming to not only identify the abnormal functional connectome pattern of the PSMA, but also to simultaneously investigate how PSMA functional connectome correlates with glucose metabolism. We calculated degree centrality (DC) and the ratio of standard uptake value (SUVr) using resting state fMRI and ¹⁸F-FDG-PET data. A two-sample t-test revealed significantly decreased PSMA DC (P_FWE < 0.014) in PD patients. The PSMA DC also correlated negatively with H-Y stage (P = 0.031). We found a widespread reduction of H-Y stage associated (P-values < 0.041) functional connectivity between PSMA and the visual network, attention network, somatomotor network, limbic network, frontoparietal network as well as the default mode network. The PSMA DC correlated positively with FDG-uptake in the HCs (P = 0.039) but not in the PD patients (P > 0.44). In summary, we identified disease severity-dependent PSMA functional connectome which in addition uncoupled with glucose metabolism in PD patients. The current study highlighted the critical role of simultaneous PET/fMRI in revealing the functional-metabolic mechanism in the PSMA of PD patients.

Atypical frontotemporal cortical activity in first-episode adolescent-onset schizophrenia during verbal fluency task: A functional near-infrared spectroscopy study

Background

Frontotemporal cortex dysfunction has been found to be associated with cognitive impairment in patients with schizophrenia (SCZ). In patients with adolescent-onset SCZ, a more serious type of SCZ with poorer functional outcome, cognitive impairment appeared to occur at an early stage of the disease. However, the characteristics of frontotemporal cortex involvement in adolescent patients with cognitive impairment are still unclear. In the present study, we aimed to illustrate the frontotemporal hemodynamic response during a cognitive task in adolescents with first-episode SCZ.

Methods

Adolescents with first-episode SCZ who were aged 12-17 and demographically matched healthy controls (HCs) were recruited. We used a 48-channel functional near-infrared spectroscopy (fNIRS) system to record the concentration of oxygenated hemoglobin (oxy-Hb) in the participants' frontotemporal area during a verbal fluency task (VFT) and analyzed its correlation with clinical characteristics.

Results

Data from 36 adolescents with SCZ and 38 HCs were included in the analyses. Significant differences were found between patients with SCZ and HCs in 24 channels, mainly covering the dorsolateral prefrontal cortex, superior and middle temporal gyrus and frontopolar area. Adolescents with SCZ showed no increase of oxy-Hb concentration in most channels, while the VFT performance was comparable between the two groups. In SCZ, the intensity of activation was not associated with the severity of symptoms. Finally, receiver operating characteristic analysis indicated that the changes in oxy-Hb concentration could help distinguish the two groups.

Conclusion

Adolescents with first-episode SCZ showed atypical cortical activity in the frontotemporal area during the VFT, and fNIRS features might be more sensitive indicators in cognitive assessment, indicating that the characteristic hemodynamic response pattern might be potential imaging biomarkers for this population.

Abnormal long- and short-range functional connectivity in patients with first-episode drug-naïve melancholic and non-melancholic major depressive disorder

BACKGROUND

We attempted to explore the common and distinct long- and short-range functional connectivity (FC) patterns of melancholic and non-melancholic major depressive disorder (MDD) and their associations with clinical characteristics.

METHODS

Fifty-nine patients with first-episode drug-naïve MDD, including 31 patients with melancholic features and 28 patients with non-melancholic features, underwent resting-state functional magnetic resonance imaging (fMRI) scanning to examine long- and short-range FC. Thirty-two healthy volunteers were recruited as controls. The support vector machines (SVM) was applied to distinguish the melancholic patients from the non-melancholic patients by using the FC of abnormal brain regions.

RESULTS

Compared to healthy volunteers, patients with MDD showed increased long-range positive FC (lpFC) in the right insula/inferior frontal gyrus and left insula. Relative to non-melancholic patients, melancholic patients displayed decreased lpFC in the right lingual gyrus, decreased short-range positive FC (spFC) in the right middle temporal gyrus and right superior parietal lobule, increased lpFC in the left inferior parietal lobule, and increased spFC in the left middle occipital gyrus/inferior occipital gyrus, left cerebellum VII/IX, and bilateral cerebellum CrusII. Increased lpFC in the left inferior parietal lobule in melancholic patients was correlated with the TEPS abstract anticipatory scores. SVM results showed that FCs of five combinations within different brain regions could distinguish melancholic patients from non-melancholic patients.

CONCLUSIONS

FC abnormalities in the default mode network and parietal-occipital brain regions may underlie the neurobiology of melancholic MDD. An increased lpFC in the left inferior parietal lobule correlated with anhedonia may be a distinctive neurobiological feature of melancholic MDD.

Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRI

Brain network interactions are commonly assessed via functional (network) connectivity, captured as an undirected matrix of Pearson correlation coefficients. Functional connectivity can represent static and dynamic relations, but often these are modeled using a fixed choice for the data window Alternatively, deep learning models may flexibly learn various representations from the same data based on the model architecture and the training task. However, the representations produced by deep learning models are often difficult to interpret and require additional posthoc methods, e.g., saliency maps. In this work, we integrate the strengths of deep learning and functional connectivity methods while also mitigating their weaknesses. With interpretability in mind, we present a deep learning architecture that exposes a directed graph layer that represents what the model has learned about relevant brain connectivity. A surprising benefit of this architectural interpretability is significantly improved accuracy in discriminating controls and patients with schizophrenia, autism, and dementia, as well as age and gender prediction from functional MRI data. We also resolve the window size selection problem for dynamic directed connectivity estimation as we estimate windowing functions from the data, capturing what is needed to estimate the graph at each time-point. We demonstrate efficacy of our method in comparison with multiple existing models that focus on classification accuracy, unlike our interpretability-focused architecture. Using the same data but training different models on their own discriminative tasks we are able to estimate task-specific directed connectivity matrices for each subject. Results show that the proposed approach is also more robust to confounding factors compared to standard dynamic functional connectivity models. The dynamic patterns captured by our model are naturally interpretable since they highlight the intervals in the signal that are most important for the prediction. The proposed approach reveals that differences in connectivity among sensorimotor networks relative to default-mode networks are an important indicator of dementia and gender. Dysconnectivity between networks, specially sensorimotor and visual, is linked with schizophrenic patients, however schizophrenic patients show increased intra-network default-mode connectivity compared to healthy controls. Sensorimotor connectivity was important for both dementia and schizophrenia prediction, but schizophrenia is more related to dysconnectivity between networks whereas, dementia bio-markers were mostly intra-network connectivity.

Anatomical distance affects functional connectivity at rest in medicine-free obsessive-compulsive disorder

BACKGROUND

Brain functional abnormalities at rest have been observed in obsessive-compulsive disorder (OCD). However, whether and how anatomical distance influences functional connectivity (FC) at rest is ambiguous in OCD.

METHODS

Using resting-state functional magnetic resonance imaging data, we calculated the FC of each voxel in the whole-brain and divided FC into short- and long-range FCs in 40 medicine-free patients with OCD and 40 healthy controls (HCs). A support vector machine (SVM) was used to determine whether the altered short- and long-range FCs could be utilized to distinguish OCD from HCs.

RESULTS

Patients had lower short-range positive FC (spFC) and long-range positive FC (lpFC) in the left precentral/postcentral gyrus (t = -5.57 and -5.43; P < 0.05, GRF corrected) and higher lpFC in the right thalamus/caudate, left thalamus, left inferior parietal lobule (IPL) and left cerebellum CrusI/VI (t = 4.59, 4.61, 4.41, and 5.93; P < 0.05, GRF corrected). Furthermore, lower spFC in the left precentral/postcentral gyrus might be used to distinguish OCD from HCs with an accuracy of 80.77%, a specificity of 81.58%, and a sensitivity of 80.00%.

CONCLUSION

These findings highlight that anatomical distance has an effect on the whole-brain FC patterns at rest in OCD. Meanwhile, lower spFC in the left precentral/postcentral gyrus might be applied in distinguishing OCD from HCs.

Increased Excursions to Functional Networks in Schizophrenia in the Absence of Task

Schizophrenia is a chronic psychotic disorder characterized by the disruption of thought processes, perception, cognition, and behaviors, for which there is still a lack of objective and quantitative biomarkers in brain activity. Using functional magnetic resonance imaging (fMRI) data from an open-source database, this study investigated differences between the dynamic exploration of resting-state networks in 71 schizophrenia patients and 74 healthy controls. Focusing on recurrent states of phase coherence in fMRI signals, brain activity was examined for intergroup differences through the lens of dynamical systems theory. Results showed reduced fractional occupancy and dwell time of a globally synchronized state in schizophrenia. Conversely, patients exhibited increased fractional occupancy, dwell time and limiting probability of being in states during which canonical functional networks—i.e., Limbic, Dorsal Attention and Somatomotor—synchronized in anti-phase with respect to the rest of the brain. In terms of state-to-state transitions, patients exhibited increased probability of switching to Limbic, Somatomotor and Visual networks, and reduced probability of remaining in states related to the Default Mode network, the Orbitofrontal network and the globally synchronized state. All results revealed medium to large effect sizes. Combined, these findings expose pronounced differences in the temporal expression of resting-state networks in schizophrenia patients, which may relate to the pathophysiology of this disorder. Overall, these results reinforce the utility of dynamical systems theory to extend current knowledge regarding disrupted brain dynamics in psychiatric disorders.

Present and future antipsychotic drugs: a systematic review of the putative mechanisms of action for efficacy and a critical appraisal under a translational perspective

Antipsychotics represent the mainstay of schizophrenia pharmacological therapy, and their role has been expanded in the last years to mood disorders treatment. Although introduced in 1952, many years of research were required before an accurate picture of how antipsychotics work began to emerge. Despite the well-recognized characterization of antipsychotics in typical and atypical based on their liability to induce motor adverse events, their main action at dopamine D2R to elicit the "anti-psychotic" effect, as well as the multimodal action at other classes of receptors, their effects on intracellular mechanisms starting with receptor occupancy is still not completely understood. Significant lines of evidence converge on the impact of these compounds on multiple molecular signaling pathways implicated in the regulation of early genes and growth factors, dendritic spine shape, brain inflammation, and immune response, tuning overall the function and architecture of the synapse. Here we present, based on PRISMA approach, a comprehensive and systematic review of the above mechanisms under a translational perspective to disentangle those intracellular actions and signaling that may underline clinically relevant effects and represent potential targets for further innovative strategies in antipsychotic therapy.

Alterations of dynamic functional connectivity between visual and executive-control networks in schizophrenia

Schizophrenia is a chronic mental disorder characterized by continuous or relapsing episodes of psychosis. While previous studies have detected functional network connectivity alterations in patients with schizophrenia, and most have focused on static functional connectivity. However, brain activity is believed to change dynamically over time. Therefore, we computed dynamic functional network connectivity using the sliding window method in 38 patients with schizophrenia and 31 healthy controls. We found that patients with schizophrenia exhibited higher occurrences in the weakly and sparsely connected state (state 3) than healthy controls, positively correlated with negative symptoms. In addition, patients exhibited fewer occurrences in a strongly connected state (state 4) than healthy controls. Lastly, the dynamic functional network connectivity between the right executive-control network and the medial visual network was decreased in schizophrenia patients compared to healthy controls. Our results further prove that brain activity is dynamic, and that alterations of dynamic functional network connectivity features might be a fundamental neural mechanism in schizophrenia.

The alterations of degree centrality in the frontal lobe of patients with panic disorder

Objective: The brain network in panic disorder (PD) is still an intriguing issue for research. In this study, we hoped to investigate the role of DC (degree centrality) for the pathophysiology of PD, especially for the fear network. Methods: We enrolled 60 patients with PD and 60 controls in the current study. The gender and age were matched for two groups. All participants received the resting-state functional magnetic resonance imaging to survey the baseline brain activity. Then the DC values of all participants were using REST toolbox. We also compared the DC values between PD and controls. The statistical threshold was set as FDR (false discovery rate) < 0.05. Results: The DC values were significantly lower in the right superior frontal gyrus of PD patients compared to controls (FDR < 0.05). In addition, a negative correlation between the DC values and panic severity was observed in the right superior frontal gyrus and left inferior frontal gyrus. However, there was no significant association between the DC values and illness duration. Conclusion: The DC seemed significantly altered in the frontal lobe of PD patients. The role of the frontal lobe might be more emphasized in the pathophysiology research for PD.

Anomalous neurovascular coupling in patients with generalized anxiety disorder evaluated by combining cerebral blood flow and functional connectivity strength

Coupling between neuronal activity and blood perfusion is termed neurovascular coupling, and it provides a new mechanistic perspective into understanding numerous brain diseases. Although abnormal brain activity and blood supply have been separately reported in generalized anxiety disorder (GAD), whether anomalous neurovascular coupling would still be presented in such disease is hitherto unknown. In this study, the neuronal activity and blood supply were measured using the functional connectivity strength (FCS) and cerebral blood flow (CBF). The voxel-wise CBF-FCS correlations and CBF/FCS ratio were separately used to assess global and local neurovascular coupling in participants. Patients with GAD showed decreased voxel-wise CBF-FCS correlation, implicating global neurovascular decoupling. They also exhibited increased CBF/FCS ratio in the right superior parietal gyrus (SPG), and the enhanced CBF/FCS ratio in this region was negatively correlated with the self-esteem scores of GAD. The abnormal neurovascular coupling of GAD may indicate the disrupted balance between the intrinsic functional organization of the brain and corresponding blood perfusion of patients, and the abnormally increased local neurovascular coupling of the right SPG may be correlated with the abnormal self in GAD. These findings provide new information in understanding the brain dysfunction and abnormal cognition of GAD from the perspective of neurovascular coupling.

Dynamic patterns within the default mode network in schizophrenia subgroups

In this study, resting-state functional magnetic resonance imaging (rs-fMRI) data of 125 schizophrenia (SZ) subjects were analyzed. Based on SZ demographic information and cognitive scores and using an unsupervised clustering method, we identified subgroups of patients and compared DMN dynamic functional connectivity (dFC) between the groups. We captured seven independent subnodes, including anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and precuneus (PCu), in the DMN by applying group independent component analysis (group-ICA) and estimated dFC between component time courses using a sliding window approach. By using k-means clustering, we separated the dFCs into three reoccurring brain states. Using the statistical method, we compared the state-specific DMN connectivity pattern between two SZ subgroups. In addition, we used a transition probability matrix of a hidden Markov model (HMM) and occupancy rate (OCR) of each state between two SZ subgroups. We found SZ subjects with higher positive and negative syndrome scale (PNASS) showed lower within ACC and lower ACC and PCC connectivity (or ACC/PCC). In addition, we found the transition from state1 to same state is significantly different between two groups, while this result was not significant after multiple comparison tests.

Alterations in resting-state global brain connectivity in bipolar I disorder patients with prior suicide attempt

BACKGROUND

Bipolar I disorder (BD-I) is associated with a high risk of suicide attempt; however, the neural circuit dysfunction that confers suicidal vulnerability in individuals with this disorder remains largely unknown. Resting-state functional magnetic resonance imaging (rs-fMRI) allows non-invasive mapping of brain functional connectivity. The current study used an unbiased voxel-based graph theory analysis of rs-fMRI to investigate the intrinsic brain networks of BD-I patients with and without suicide attempt.

METHODS

A total of 30 BD-I patients with suicide attempt (attempter group), 82 patients without suicide attempt (non-attempter group), and 67 healthy controls underwent rs-fMRI scan, and then global brain connectivity (GBC) was computed as the sum of connections of each voxel with all other gray matter voxels in the brain.

RESULTS

Compared with the non-attempter group, we found regional differences in GBC values in emotion-encoding circuits, including the left superior temporal gyrus, bilateral insula/rolandic operculum, and right precuneus (PCu)/cuneus in the bipolar disorder (BD) attempter group, and these disrupted hub-like regions displayed fair to good power in distinguishing attempters from non-attempters among BD-I patients. GBC values of the right PCu/cuneus were positively correlated with illness duration and education in the attempter group.

CONCLUSIONS

Our results indicate that abnormal connectivity patterns in emotion-encoding circuits are associated with the increasing risk of vulnerability to suicide attempt in BD patients, and global dysconnectivity across these emotion-encoding circuits might serve as potential biomarkers for classification of suicide attempt in BD patients.

A systematic review of neuroimaging and acute cannabis exposure in age-of-risk for psychosis

Acute exposure to cannabis has been associated with an array of cognitive alterations, increased risk for neuropsychiatric illness, and other neuropsychiatric sequelae including the emergence of acute psychotic symptoms. However, the brain alterations associating cannabis use and these behavioral and clinical phenotypes remains disputed. To this end, neuroimaging can be a powerful technique to non-invasively study the impact of cannabis exposure on brain structure and function in both humans and animal models. While chronic exposure studies provide insight into how use may be related to long-term outcomes, acute exposure may reveal interesting information regarding the immediate impact of use and abuse on brain circuits. Understanding these alterations could reveal the connection with symptom dimensions in neuropsychiatric disorders and, more specifically with psychosis. The purpose of the present review is to: 1) provide an update on the findings of pharmacological neuroimaging studies examining the effects of administered cannabinoids and 2) focus the discussion on studies that examine the sensitive window for the emergence of psychosis. Current literature indicates that cannabis exposure has varied effects on the brain, with the principal compounds in cannabis (delta-9-tetrahydrocannabinol and cannabidiol) altering activity across different brain regions. Importantly, we also discovered critical gaps in the literature, particularly regarding sex-dependent responses and long-term effects of chronic exposure. Certain networks often characterized as dysregulated in psychosis, like the default mode network and limbic system, were also impacted by THC exposure, identifying areas of particular interest for future work investigating the potential relationship between the two.

Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized. Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects. Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity. Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

Altered hippocampal-prefrontal communication during anxiety-related avoidance in mice deficient for the autism-associated gene Pogz

Many genes have been linked to autism. However, it remains unclear what long-term changes in neural circuitry result from disruptions in these genes, and how these circuit changes might contribute to abnormal behaviors. To address these questions, we studied behavior and physiology in mice heterozygous for Pogz, a high confidence autism gene. Pogz+/- mice exhibit reduced anxiety-related avoidance in the elevated plus maze (EPM). Theta-frequency communication between the ventral hippocampus (vHPC) and medial prefrontal cortex (mPFC) is known to be necessary for normal avoidance in the EPM. We found deficient theta-frequency synchronization between the vHPC and mPFC in vivo. When we examined vHPC-mPFC communication at higher resolution, vHPC input onto prefrontal GABAergic interneurons was specifically disrupted, whereas input onto pyramidal neurons remained intact. These findings illustrate how the loss of a high confidence autism gene can impair long-range communication by causing inhibitory circuit dysfunction within pathways important for specific behaviors.

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.

Dynamic Neural Network Changes Revealed by Voxel-Based Functional Connectivity Strength in Left Basal Ganglia Ischemic Stroke

Objective

This study intends to track whole-brain functional connectivity strength (FCS) changes and the lateralization index (LI) in left basal ganglia (BG) ischemic stroke patients.

Methods

Twenty-five patients (N = 25; aged 52.73 ± 10.51 years) with five visits at <7, 14, 30, 90, and 180 days and 26 healthy controls (HCs; N = 26; 51.84 ± 8.06 years) were examined with resting-state functional magnetic resonance imaging (rs-fMRI) and motor function testing. FCS and LI were calculated through constructing the voxel-based brain functional network. One-way analysis of covariance (ANOVA) was first performed to obtain longitudinal FCS and LI changes in patients among the five visits (Bonferroni corrected, P < 0.05). Then, pairwise comparisons of FCS and LI were obtained during the five visits, and the two-sample t test was used to examine between-group differences in FCS [family-wise error (FWE) corrected, P < 0.05] and LI. Correlations between connectivity metrics (FCS and LI) and motor function were further assessed.

Results

Compared to HCs, decreased FCS in the patients localized in the calcarine and inferior occipital gyrus (IOG), while increased FCS gathered in the middle prefrontal cortex (MPFC), middle frontal gyrus, and insula (P < 0.05). The LI and FCS of patients first decreased and then increased, which showed significant differences compared with HCs (P < 0.05) and demonstrated a transition at the 30-day visit. Additionally, LI at the third visit was significantly different from those at the other visits (P < 0.05). No significant longitudinal correlations were observed between motor function and FCS or LI (P > 0.05).

Conclusion

Focal ischemic stroke in the left BG leads to extensive alterations in the FCS. Strong plasticity in the functional networks could be reorganized in different temporal dynamics to facilitate motor recovery after BG stroke, contribute to diagnosing the disease course, and estimate the intervention treatment.

Intrinsic non-hub connectivity predicts human inter-temporal decision-making

Inter-temporal decision-making is ubiquitous in daily life and has been considered as a critical characteristic associated with an individual's success. Such decisions require us to tradeoff between short-term and long-term benefits. Prior studies have indicated that inter-temporal decision involves various brain regions that tend to occupy the central hubs. However, it is unclear whether the functional connectivities among hub as well as non-hub regions can predict discounting behaviors. Here, we combined with graph-theoretical algorithm and multivariate pattern analysis to explore whether voxel-wise functional connectivity strength in the whole brain could predict discounting rates (indexed as logk, based on the adaptive delay-discounting task) in a relatively large sample (n = 429) of young adults. Results revealed that short- and long-distance as well as all-range non-hub functional connectivity strength in the limbic system (i.e., medial orbitofrontal cortex and parahippocampus) were inversely associated with discounting rates. Furthermore, these results were robust and did not appear to be due to potential confounding factors. Above weight-based degree metric is commonly indicative of the communication pattern of local and global parallel information processing, and it therefore provides novel insights into the neural mechanisms underlying inter-temporal decision-making from the perspective of human brain topological organizations.

Discriminative Analysis of Symptom Severity and Ultra-High Risk of Schizophrenia Using Intrinsic Functional Connectivity

Past studies have consistently shown functional dysconnectivity of large-scale brain networks in schizophrenia. In this study, we aimed to further assess whether multivariate pattern analysis (MVPA) could yield a sensitive predictor of patient symptoms, as well as identify ultra-high risk (UHR) stage of schizophrenia from intrinsic functional connectivity of whole-brain networks. We first combined rank-based feature selection and support vector machine methods to distinguish between 43 schizophrenia patients and 52 healthy controls. The constructed classifier was then applied to examine functional connectivity profiles of 18 UHR individuals. The classifier indicated reliable relationship between MVPA measures and symptom severity, with higher classification accuracy in more severely affected schizophrenia patients. The UHR subjects had classification scores falling between those of healthy controls and patients, suggesting an intermediate level of functional brain abnormalities. Moreover, UHR individuals with schizophrenia-like connectivity profiles at baseline presented higher rate of conversion to full-blown illness in the follow-up visits. Spatial maps of discriminative brain regions implicated increases of functional connectivity in the default mode network, whereas decreases of functional connectivity in the cerebellum, thalamus and visual areas in schizophrenia. The findings may have potential utility in the early diagnosis and intervention of schizophrenia.

Influence of More Than 5 Years of Continuous Exposure to Antipsychotics on Cerebral Functional Connectivity of Chronic Schizophrenia

OBJECTIVE

To explore the effect of long-term antipsychotics use on the strength of functional connectivity (FC) in the brains of patients with chronic schizophrenia.

METHOD

We collected resting-state functional magnetic resonance imaging from 15 patients with continuously treated chronic schizophrenia (TCS), 19 patients with minimally TCS (MTCS), and 20 healthy controls (HCs). Then, we evaluated and compared the whole-brain FC strength (FCS; including full-range, short-range, and long-range FCS) among patients with TCS, MTCS, and HCs.

RESULTS

Patients with TCS and MTCS showed reduced full-/short-range FC compared with the HCs. No significant differences in the whole-brain FCS (including full-range, short-range, and long-range FCS) or clinical characteristics were identified between patients with TCS and MTCS. Additionally, the FCS in the right fusiform gyrus, right inferior temporal gyrus, and right inferior occipital gyrus negatively correlated with the duration of illness and positively correlated with onset age across all patients with chronic schizophrenia.

CONCLUSIONS

Regardless of the long-term use of antipsychotics, patients with chronic schizophrenia show decreased FC compared with healthy individuals. For some patients with chronic schizophrenia, the influence of long-term and minimal/short-term antipsychotic exposure on resting-state FC was similar. The decreased full- and short-range FCS in the right fusiform gyrus, right inferior temporal gyrus, and right inferior occipital gyrus may be an ongoing pathological process that is not altered by antipsychotic interventions in patients with chronic schizophrenia. Large-sample, long-term follow-up studies are still needed for further exploration.

Sign-Consistency Based Variable Importance for Machine Learning in Brain Imaging

An important problem that hinders the use of supervised classification algorithms for brain imaging is that the number of variables per single subject far exceeds the number of training subjects available. Deriving multivariate measures of variable importance becomes a challenge in such scenarios. This paper proposes a new measure of variable importance termed sign-consistency bagging (SCB). The SCB captures variable importance by analyzing the sign consistency of the corresponding weights in an ensemble of linear support vector machine (SVM) classifiers. Further, the SCB variable importances are enhanced by means of transductive conformal analysis. This extra step is important when the data can be assumed to be heterogeneous. Finally, the proposal of these SCB variable importance measures is completed with the derivation of a parametric hypothesis test of variable importance. The new importance measures were compared with a t-test based univariate and an SVM-based multivariate variable importances using anatomical and functional magnetic resonance imaging data. The obtained results demonstrated that the new SCB based importance measures were superior to the compared methods in terms of reproducibility and classification accuracy.

Relationship between resting-state theta phase-gamma amplitude coupling and neurocognitive functioning in patients with first-episode psychosis

BACKGROUND

Although cognitive dysfunction is a core element of schizophrenia, the neurobiological underpinnings of the pathophysiology are not yet sufficiently understood. Because the resting state is crucial for cognitive functioning and electroencephalography (EEG) can reflect instantaneous neural activity, we investigated theta phase-gamma amplitude coupling (TGC) of resting-state EEG and its relationship with cognitive function in patients with first-episode psychosis (FEP) to reveal the neural correlates of cognitive dysfunction.

METHODS

A total of 59 FEP patients and 50 healthy controls (HCs) underwent resting-state, eyes-closed EEG recordings and performed the Trail Making Test Part A (TMT-A) and Part B (TMT-B) and California Verbal Learning Test (CVLT). TGC from the source signal of the resting-state EEG in default mode network (DMN)-related brain regions was compared between groups. Correlation analyses were performed between TGC and cognitive function test performance in FEP patients.

RESULTS

Mean resting-state TGC was larger for the FEP patients than for the HCs. Patients with FEP showed increased TGC in the left posterior cingulate cortex, which was correlated with better performance on the TMT-A and TMT-B and on immediate and delayed recall in the CVLT.

CONCLUSIONS

These results suggest that patients with FEP show compensatory hyperactivation of resting-state TGC in DMN-related brain regions, which may be related to the reallocation of cognitive resources to prepare for successful cognitive execution. This study not only highlights the neural underpinnings of cognitive dysfunction in FEP patients but also provides useful background to support the development of treatments for cognitive dysfunction in schizophrenia.

Network functional connectivity analysis in individuals at ultrahigh risk for psychosis and patients with schizophrenia

Schizophrenia is a severe mental disorder, and the onset of which is preceded by a stage of ultrahigh risk (UHR) for developing psychosis. Therefore, analyzing individuals with UHR is essential for identifying predictive biomarkers for the onset of schizophrenia. The current study aimed to identify such biomarkers based on a voxelwise whole-brain functional degree centrality (FDC) analysis. Conjunction analysis showed that, compared with healthy controls, both UHR subjects and patients with schizophrenia showed significantly increased FDC at the medial prefrontal cortex (MPFC) and significantly decreased FDC at the right fusiform gyrus (FG). The subsequent partial correlation analysis showed significant correlations between the disorganization symptoms and FDCs at the MPFC and the right FG for both UHR subjects and patients with schizophrenia. These findings suggest that FDC within the MPFC and the right FG could be candidate biomarkers for the onset of schizophrenia.

Abnormalities in hubs location and nodes centrality predict cognitive slowing and increased performance variability in first-episode schizophrenia patients

Introducing the Minimum Spanning Tree (MST) algorithms to neural networks science eliminated the problem of arbitrary setting of the threshold for connectivity strength. Despite these advantages, MST has been rarely used to study network abnormalities in schizophrenia. An MST graph mapping a network structure is its simplification, therefore, it is important to verify whether the reconfigured network is significantly related to the behavioural dimensions of the clinical picture of schizophrenia. 35 first-episode schizophrenia patients and 35 matched healthy controls underwent an assessment of information processing speed, cognitive inter-trial variability modelled with ex-Gaussian distributional analysis of reaction times and resting-state EEG recordings to obtain frequency-specific functional connectivity matrices from which MST graphs were computed. The patients’ network had a more random structure and star-like arrangement with overloaded hubs positioned more posteriorly than it was in the case of the control group. Deficient processing speed in the group of patients was predicted by increased maximal betweenness centrality in beta and gamma bands, while decreased consistency in cognitive processing was predicted by the betweenness centrality of posterior nodes in the gamma band, together with duration of illness. The betweenness centrality of posterior nodes in the gamma band was also significantly correlated with positive psychotic symptoms in the clinical group.

Dual-process theory, conflict processing, and delusional belief

Many reasoning biases that may contribute to delusion formation and/or maintenance are common in healthy individuals. Research indicating that reasoning in the general population proceeds via analytic processes (which depend upon working memory and support hypothetical thought) and intuitive processes (which are autonomous and independent of working memory) may therefore help uncover the source of these biases. Consistent with this possibility, recent studies imply that impaired conflict processing might reduce engagement in analytic reasoning, thereby producing reasoning biases and promoting delusions in individuals with schizophrenia. Progress toward understanding this potential pathway to delusions is currently impeded by ambiguity about whether any of these deficits or biases is necessary or sufficient for the formation and maintenance of delusions. Resolving this ambiguity requires consideration of whether particular cognitive deficits or biases in this putative pathway have causal primacy over other processes that may also participate in the causation of delusions. Accordingly, the present manuscript critically evaluates whether impaired conflict processing is the primary initiating deficit in the generation of reasoning biases that may promote the development and/or maintenance of delusions. Suggestions for future research that may elucidate mechanistic pathways by which reasoning deficits might engender and maintain delusions are subsequently offered.

Altered resting-state functional connectivity of the cerebellum in schizophrenia

Structural and functional abnormalities of the cerebellum in schizophrenia have been reported. Most previous studies investigating resting-state functional connectivity (rsFC) have relied on a priori restrictions on seed regions or specific networks, which may bias observations. In this study, we aimed to elicit the connectivity alterations of the cerebellum in schizophrenia in a hypothesis-free approach. Ninety-five schizophrenia patients and 93 sex- and age-matched healthy controls underwent resting-state functional magnetic resonance imaging (fMRI). A voxel-wise data-driven method, resting-state functional connectivity density (rsFCD), was used to investigate cerebellar connectivity changes in schizophrenia patients. Regions with altered rsFCD were chosen as seeds to perform seed-based resting-state functional connectivity (rsFC) analyses. We found that schizophrenia patients exhibited decreased rsFCD in the right hemispheric VI; moreover, this cerebellar region showed increased rsFC with the prefrontal cortex and subcortical nuclei and decreased rsFC with the visual cortex and sensorimotor cortex. In addition, some rsFC changes were associated with positive symptoms. These findings suggest that abnormalities of the cerebellar hub and cerebellar-subcortical-cortical loop may be the underlying mechanisms of schizophrenia.

Disrupted functional connectivity within the default mode network and salience network in unmedicated bipolar II disorder

BACKGROUND

Recent studies demonstrate that functional disruption in resting-state networks contributes to cognitive and affective symptoms of bipolar disorder (BD), however, the functional connectivity (FC) pattern underlying BD II depression within the default mode network (DMN), salience network (SN), and frontoparietal network (FPN) is still not well understood. The primary aim of this study was to explore whether the pathophysiology of BD II derived from the pattern of FC within the DMN, SN, and FPN by using seed-based FC approach of resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

Ninety-six BD II patients and 100 HCs underwent rs-fMRI and three-dimensional structural data acquisition. All patients were either drug naive or unmedicated for at least 6 months. The following four regions of interest were used to conduct seed-based FC: the left posterior cingulate cortex (PCC) seed to probe the DMN, the left subgenual anterior cingulate cortex (sgACC) and amygdala seeds to probe the SN, the left dorsal lateral prefrontal cortex (dlPFC) seed to probe the FPN.

RESULTS

Compared with HCs, patients with BD II demonstrated hypoconnectivity of the left PCC to the bilateral medial prefrontal cortex (mPFC) and bilateral precuneus/PCC, and of the left sgACC to the right inferior temporal gyrus (ITG); nevertheless, the left amygdala and dlPFC had no within-network hypo- or hyperconnectivity to any other SN and FPN regions.

CONCLUSION

Our findings suggest that disrupted FC is located in the DMN and SN, especially in the PCC-mPFC and precuneus/PCC, and sgACC-ITG connectivity in BD II patients.

Altered spatial and temporal concordance among intrinsic brain activity measures in schizophrenia

Various data-driven voxel-wise measures derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been developed to characterize spontaneous brain activity. These measures have been widely applied to explore brain functional changes in schizophrenia and have enjoyed significant success in unraveling the neural mechanisms of this disorder. However, their spatial and temporal coupling alterations in schizophrenia remain largely unknown. To address this issue, 88 schizophrenia patients and 116 gender- and age-matched healthy controls underwent rs-fMRI examinations. Kendall's W was used to calculate volume-wise (across voxels) and voxel-wise (across time windows) concordance among multiple commonly used measures, including fractional amplitude of low frequency fluctuations, regional homogeneity, voxel-mirrored homotopic connectivity, degree centrality and global signal connectivity. Inter-group differences in the concordance were investigated. Results revealed that whole gray matter volume-wise concordance was reduced in schizophrenia patients relative to healthy controls. Although two groups showed similar spatial distributions of the voxel-wise concordance, quantitative comparison analysis revealed that schizophrenia patients exhibited decreased voxel-wise concordance in gray matter areas spanning the bilateral frontal, parietal, occipital, temporal and insular cortices. In addition, these concordance changes were negatively correlated with onset age in schizophrenia patients. Our findings suggest that the concordance approaches may provide new insights into the neural mechanisms of schizophrenia and have the potential to be extended to neuropsychiatric disorders.

Enhancing the representation of functional connectivity networks by fusing multi-view information for autism spectrum disorder diagnosis

Functional connectivity network provides novel insights on how distributed brain regions are functionally integrated, and its deviations from healthy brain have recently been employed to identify biomarkers for neuropsychiatric disorders. However, most of brain network analysis methods utilized features extracted only from one functional connectivity network for brain disease detection and cannot provide a comprehensive representation on the subtle disruptions of brain functional organization induced by neuropsychiatric disorders. Inspired by the principles of multi-view learning which utilizes information from multiple views to enhance object representation, we propose a novel multiple network based framework to enhance the representation of functional connectivity networks by fusing the common and complementary information conveyed in multiple networks. Specifically, four functional connectivity networks corresponding to the four adjacent values of regularization parameter are generated via a sparse regression model with group constraint ( l_2,1 -norm), to enhance the common intrinsic topological structure and limit the error rate caused by different views. To obtain a set of more meaningful and discriminative features, we propose using a modified version of weighted clustering coefficients to quantify the subtle differences of each group-sparse network at local level. We then linearly fuse the selected features from each individual network via a multi-kernel support vector machine for autism spectrum disorder (ASD) diagnosis. The proposed framework achieves an accuracy of 79.35%, outperforming all the compared single network methods for at least 7% improvement. Moreover, compared with other multiple network methods, our method also achieves the best performance, that is, with at least 11% improvement in accuracy.

Association between resting-state brain functional connectivity and cortisol levels in unmedicated major depressive disorder

Disturbed hypothalamus-pituitary-adrenal axis function, which leads to excessive and prolonged hypercortisolemia, is a core feature of major depressive disorder (MDD). However, the relationships between depression, brain structure and function, and cortisol levels are unclear. The current study examined the whole-brain functional connectivity pattern of patients with MDD and evaluated the association between functional connectivity and serum cortisol levels in MDD. A total of 93 unmedicated patients with MDD and 139 healthy control subjects underwent resting-state functional magnetic resonance imaging. Voxel-wise whole-brain connectivity was analyzed by using a graph theory approach: functional connectivity strength (FCS). A seed-based resting-state functional connectivity analysis was further performed to investigate abnormal functional connectivity patterns of those regions with changed FCS. Morning blood samples were drawn for cortisol measurements in some subjects (including 53 MDD patients and 30 controls). The MDD patients had a significantly lower FCS in the left posterior lobes of the cerebellum (mainly lobule Crus II) (p < 0.05, TFCE corrected). The seed-based functional connectivity analysis revealed decreased functional connectivity between the left posterior cerebellum and the left medial orbitofrontal cortex (OFC) (p < 0.05, TFCE corrected). Moreover, the functional connectivity between the left posterior cerebellum and the left medial OFC were significantly positively correlated with the serum cortisol levels in MDD patients. Our results suggest that cerebellar dysconnectivity, in particular distributed cerebellar-OFC functional connectivity, may be associated with serum cortisol levels in MDD patients.

Altered cerebellar functional connectivity in remitted bipolar disorder: A resting-state functional magnetic resonance imaging study

OBJECTIVES

Several recent studies have reported a strong association between the cerebellar structural and functional abnormalities and psychiatric disorders. However, there are no studies to investigate possible changes in cerebellar functional connectivity in bipolar disorder. This study aimed to examine the whole-brain functional connectivity pattern of patients with remitted bipolar disorder II, in particular in the cerebellum.

METHODS

A total of 25 patients with remitted bipolar disorder II and 25 controls underwent resting-state functional magnetic resonance imaging and neuropsychological tests. Voxel-wise whole-brain connectivity was analyzed using a graph theory approach: functional connectivity strength. A seed-based resting-state functional connectivity analysis was further performed to investigate abnormal functional connectivity pattern of those regions with changed functional connectivity strength.

RESULTS

Remitted bipolar disorder II patients had significantly decreased functional connectivity strength in the bilateral posterior lobes of cerebellum (mainly lobules VIIb/VIIIa). The seed-based functional connectivity analyses revealed decreased functional connectivity between the right posterior cerebellum and the default mode network (i.e. right posterior cingulate cortex/precuneus and right superior temporal gyrus), bilateral hippocampus, right putamen, left paracentral lobule and bilateral posterior cerebellum and decreased functional connectivity between the left posterior cerebellum and the right inferior parietal lobule and bilateral posterior cerebellum in patients with remitted bipolar disorder II.

CONCLUSION

Our results suggest that cerebellar dysconnectivity, in particular distributed cerebellar-cerebral functional connectivity, might be associated with the pathogenesis of bipolar disorder.

Disturbed functional connectivity within the left prefrontal cortex and sensorimotor areas predicts impaired cognitive speed in patients with first-episode schizophrenia

This study aimed at identifying abnormal cortico-cortical functional connectivity patterns that could predict cognitive slowing in patients with schizophrenia. A group of thirty-two patients with the first-episode schizophrenia and comparable healthy controls underwent resting-state qEEG and cognitive assessment. Phase Lag Index (PLI) was applied as a connectivity index and the synchronizations were analyzed in six frequencies. Pairs of electrodes were grouped to separately cover frontal, temporal, central, parietal and occipital regions. PLI was calculated for intra-regional connectivity and between-regions connectivity. Computer version processing speed tests were applied to control for possible fluctuations in cognitive efficiency during the performance of the tasks. In the group of patients, in comparison to healthy controls, significantly higher PLI values were recorded in theta frequency, especially in the posterior areas and decreased PLI in low-alpha frequency within the frontal regions. Mean PLI in gamma frequency was also lower in the patients group. Regression analysis showed that lower intra-regional PLI for left frontal cortex and higher PLI within somatosensory cortex in theta band, together with the duration of untreated psychosis, proved to be significant predictors of impaired processing speed in first-episode patients. Our investigation confirmed that disrupted cortico-cortical synchronization contributes to cognitive slowing in schizophrenia.

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI

BACKGROUND

A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia.

METHODS

A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls.

FINDINGS

Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks.

INTERPRETATION

The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the "disconnectivity" model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites.

Brain functional and perfusional alterations in schizophrenia: an arterial spin labeling study

Schizophrenia is a severe mental disorder that affects the anatomy and function of the brain, with an impact on one's thoughts, feelings, and behavior. The purpose of the study was to investigate cerebral blood flow (CBF) and brain connectivity in a group of patients with schizophrenia. Pseudo-continuous arterial spin labeling (pCASL) images were acquired from 28 patients in treatment and 28 age-matched healthy controls. Mean CBF and connectivity patterns were assessed. Schizophrenia patients had decreased CBF in the bilateral frontal pole and superior frontal gyrus, right medial frontal gyrus, triangular and opercular parts of the inferior frontal gyrus, posterior division of the left supramarginal gyrus, superior and inferior divisions of the left lateral occipital cortex, and bilateral occipital pole. Moreover, through different methods to assess connectivity, our results showed abnormal connectivity patterns in regions involved in motor, sensorial, and cognitive functions. Using pCASL, a non-invasive technique, we found CBF deficits and altered functional organization of the brain in schizophrenia patients that are associated with the symptoms and characteristics of the disorder.

Abnormal long- and short-range functional connectivity in adolescent-onset schizophrenia patients: A resting-state fMRI study

BACKGROUND

Human brain is a topologically complex network embedded in anatomical space, and anatomical distance may affect functional connectivity (FC) in schizophrenia. However, little is known if and how this effect occurs in adolescent-onset schizophrenia (AOS).

METHODS

We explored long- and short-range FC through resting-state functional magnetic resonance imaging in 48 first-episode, drug-naive AOS patients and 31 healthy controls, and we examined if these abnormalities could be utilized to separate patients from controls using receiver operating characteristic curves and support vector machines (SVM).

RESULTS

Patients had increased long-range positive FC (lpFC) and short-range positive FC (spFC) in the right middle frontal gyrus and right superior medial prefrontal cortex within the anterior default mode network (DMN), decreased lpFC and spFC in several regions of the posterior DMN, and decreased lpFC within the important hubs of salience network (SN). The decreased lpFC in the left superior temporal gyrus was positively correlated with cognitive impairment. We found that SVM has high accuracy (up to 92.4%) in classifying patients and control.

CONCLUSION

Disrupted anatomical distance would underlie network-level dysconnectivity, highlighting the importance of the DMN and SN in the neurodevelopment of schizophrenia. Abnormalities of long- and short-range FC in brain regions could discriminate patients from controls with high accuracy.

Impact of previous episodes of hepatic encephalopathy on short-term brain function recovery after liver transplantation: a functional connectivity strength study

Neuropsychological studies have documented an incomplete reversal of pre-existing cognitive dysfunction in cirrhotic patients after liver transplantation (LT) and have found this is more severe in patients with hepatic encephalopathy (HE). In this study, we aimed to investigate the impact of prior HE episodes on post-transplantation brain function recovery. Resting-state functional magnetic resonance imaging data was collected from 30 healthy controls and 33 cirrhotic patients (HE, n = 15 and noHE, n = 18) before and one month after LT. Long- and short-range functional connectivity strength (FCS) analysis indicated that before transplantation both noHE and HE groups showed diffuse FCS abnormalities relative to healthy controls. For the noHE group, the abnormal FCS found before LT largely returned to normal levels after LT, except for in the cerebellum, precuneus, and orbital middle frontal gyrus. However, the abnormal FCS prior to LT was largely preserved in the HE group, including high-level cognition-related (frontal and parietal lobes) and vision-related areas (occipital lobe, cuneus, and precuneus). In addition, comparisons between HE and noHE groups revealed that weaker FCS in default mode network (DMN) in HE group persisted from pre- to post- LT. Correlation analysis showed that changes in FCS in the left postcentral and right middle frontal gyrus correlated with alterations in neuropsychological performance and ammonia levels. In conclusion, the findings in this study demonstrate potential adverse effects of pre-LT episode of HE on post-LT brain function recovery, and reveal that DMN may be the most affected brain region by HE episodes, which can't be reversed by LT.

Social affective context reveals altered network dynamics in schizophrenia patients

Impairments in social cognition and interactions are core psychopathologies in schizophrenia, often manifesting as an inability to appropriately relate to the intentions and feelings of others. Neuroimaging has helped to demarcate the dynamics of two distinct functional connectivity circuits underlying the social-affective processes related to mentalization (known as Theory of Mind, ToM) and somatic-affiliation (known as Embodied Simulation, ES). While evidence points to abnormal activation patterns within these networks among those suffering from schizophrenia, it is yet unclear however, if these patients exhibit this abnormal functional connectivity in the context of social-affective experiences. The current fMRI study, investigated functional connectivity dynamics within ToM and ES networks as subjects experienced evolving cinematic portrayals of fear. During scanning, schizophrenia patients and healthy controls passively watched a cinematic scene in which a mother and her son face various threatening events. Participants then provided a continuous and retrospective report of their fear intensity during a second viewing outside the scanner. Using network cohesion index (NCI) analysis, we examined modulations of ES-related and ToM-related functional connectivity dynamics and their relation to symptom severity and the continuous emotional ratings of the induced cinematic fear. Compared to patients, healthy controls showed higher ES-NCI and marginally lower ToM-NCI during emotional peaks. Cross-correlation analysis revealed an intriguing dynamic between NCI and the inter-group difference of reported fear. Schizophrenia patients rated their fear as lower relative to healthy controls, shortly after exhibiting lower ES connectivity. This increased difference in rating was also followed by higher ToM connectivity among schizophrenia patients. The clinical relevance of these findings is further highlighted by the following two results: (a) ToM-NCI was found to have a strong correlation with the severity of general symptoms during one of the two main emotional peaks (Spearman R = 0.77); and (b) k-mean clustering demonstrated that the networks' NCI dynamic during the social-affective context reliably differentiated between patients and controls. Together, these findings point to a possible neural marker for abnormal social-affective processing in schizophrenia, manifested as the disturbed balance between two functional networks involved in social-affective affiliation. This in turn suggests that exaggerated mentalization over somatic-affiliative processing, in response to another's' distress may underlie social-affective deficits in schizophrenia.

Distance-dependent alterations in local functional connectivity in drug-naive major depressive disorder

Previous studies using resting-state functional magnetic resonance imaging (fMRI) have found abnormal functional connectivity in patients with major depressive disorder (MDD). Yet, effect of distance thresholds on local functional connectivity changes in MDD is largely unknown. Here, we used resting-state fMRI data and functional connectivity strength (FCS) method to test local functional connectivity differences at different distance thresholds between 47 drug-naive patients with MDD and 47 healthy controls. For the distribution of functional brain hubs with high local FCS, the overall changing trend from distance thresholds of 10mm to 100mm was from lateral to medial. Compared to controls, MDD patients exhibited decreased local FCS independent of distance threshold in the sensorimotor system (postcentral gyrus, paracentral lobule, and supplementary motor area). MDD Patients exhibited increased local FCS in the inferior temporal gyrus at two lower distance thresholds (20mm and 30mm) and a higher distance threshold (100mm). In addition, MDD patients showed increased local FCS in the putamen at higher distance thresholds (80-100mm). These findings suggest that local functional connectivity abnormalities in MDD are dependent on distance thresholds and that future studies should take the distance thresholds into account when measuring local functional connectivity in MDD.

Effect of rs1344706 in the ZNF804A gene on the brain network

ZNF804A rs1344706 (A/C) was the first SNP that reached genome-wide significance for schizophrenia. Recent studies have linked rs1344706 to functional connectivity among specific brain regions. However, no study thus far has examined the role of this SNP in the entire functional connectome. In this study, we used degree centrality to test the role of rs1344706 in the whole-brain voxel-wise functional connectome during the resting state. 52 schizophrenia patients and 128 healthy controls were included in the final analysis. In our whole-brain analysis, we found a significant interaction effect of genotype × diagnosis at the precuneus (PCU) (cluster size = 52 voxels, peak voxel MNI coordinates: x = 9, y = − 69, z = 63, F = 32.57, FWE corrected P < 0.001). When we subdivided the degree centrality network according to anatomical distance, the whole-brain analysis also found a significant interaction effect of genotype × diagnosis at the PCU with the same peak in the short-range degree centrality network (cluster size = 72 voxels, F = 37.29, FWE corrected P < 0.001). No significant result was found in the long-range degree centrality network. Our results elucidated the contribution of rs1344706 to functional connectivity within the brain network, and may have important implications for our understanding of this risk gene's role in functional dysconnectivity in schizophrenia.

•

This study was the first to report the effect of ZNF804A rs1344706 on the property of the whole-brain network.

•

We found a significant interaction of rs1344706 genotype × diagnosis on the functional connectivity of the PCU.

Short-range connections in the developmental connectome during typical and atypical brain maturation

The human brain is remarkably complex with connectivity constituting its basic organizing principle. Although long-range connectivity has been focused on in most research, short-range connectivity is characterized by unique and spatiotemporally heterogeneous dynamics from infancy to adulthood. Alterations in the maturational dynamics of short-range connectivity has been associated with neuropsychiatric disorders, such as autism and schizophrenia. Recent advances in neuroimaging techniques, especially diffusion magnetic resonance imaging (dMRI), resting-state functional MRI (rs-fMRI), electroencephalography (EEG) and magnetoencephalography (MEG), have made quantification of short-range connectivity possible in pediatric populations. This review summarizes findings on the development of short-range functional and structural connections at the macroscale. These findings suggest an inverted U-shaped pattern of maturation from primary to higher-order brain regions, and possible "hyper-" and "hypo-" short-range connections in autism and schizophrenia, respectively. The precisely balanced short- and long-range connections contribute to the integration and segregation of the connectome during development. The mechanistic relationship among short-range connectivity maturation, the developmental connectome and emerging brain functions needs further investigation, including the refinement of methodological approaches.

Altered Coupling Between Resting-State Cerebral Blood Flow and Functional Connectivity in Schizophrenia

BACKGROUND

Respective changes in resting-state cerebral blood flow (CBF) and functional connectivity in schizophrenia have been reported. However, their coupling alterations in schizophrenia remain largely unknown.

METHODS

89 schizophrenia patients and 90 sex- and age-matched healthy controls underwent resting-state functional MRI to calculate functional connectivity strength (FCS) and arterial spin labeling imaging to compute CBF. The CBF-FCS coupling of the whole gray matter and the CBF/FCS ratio (the amount of blood supply per unit of connectivity strength) of each voxel were compared between the 2 groups.

RESULTS

Whole gray matter CBF-FCS coupling was decreased in schizophrenia patients relative to healthy controls. In schizophrenia patients, the decreased CBF/FCS ratio was predominantly located in cognitive- and emotional-related brain regions, including the dorsolateral prefrontal cortex, insula, hippocampus and thalamus, whereas an increased CBF/FCS ratio was mainly identified in the sensorimotor regions, including the putamen, and sensorimotor, mid-cingulate and visual cortices.

CONCLUSION

These findings suggest that the neurovascular decoupling in the brain may be a possible neuropathological mechanism of schizophrenia.

Anatomical distance affects cortical-subcortical connectivity in first-episode, drug-naive somatization disorder

BACKGROUND

Brain structural and functional alterations in the cortical-subcortical circuits have been observed in somatization disorder (SD). However, whether and how anatomical distance affects the cortical-subcortical connectivity in SD remain unclear. This study aims to examine whether anatomical distance affects the cortical-subcortical in first-episode, drug-naive SD.

METHODS

Twenty-five first-episode, drug-naive patients with SD and twenty-eight healthy controls were recruited for a resting-state scan. Regional functional connectivity strength (FCS) was calculated for each voxel in the brain, which was further divided into short- and long-range FCSs. Correlation analyses were conducted between abnormal FCS and clinical/cognitive variables in the patients.

RESULTS

Compared with the controls, the patients showed increased short-range positive FCS (spFCS) in the right superior frontal gyrus (SFG) and decreased spFCS in the left pallidum, and increased long-range positive FCS (lpFCS) in the left middle frontal gyrus and right inferior temporal gyrus (ITG). Positive correlations were observed between the spFCS values in the right SFG and Eysenck Personality Questionnaire psychoticism scores (r=0.441, p=0.027, uncorrected) and between the lpFCS values in the right ITG and scores of digit symbol-coding of Wechsler Adult Intelligence Scale (r=0.416, p=0.039, uncorrected) in the patients CONCLUSIONS: The patients exhibited increased spFCS/lpFCS in the cortical regions and decreased spFCS in the subcortical regions. The left pallidum is first reported here to show decreased spFCS in SD. The present results suggest that abnormal cortical-subcortical circuits may play an important role in SD neurobiology.