Increased intrinsic brain activity in the striatum reflects symptom dimensions in schizophrenia

Alterations in the volume and shape of the basal ganglia and thalamus in schizophrenia with auditory hallucinations

Different lines of evidence indicate that the structure and physiology of the basal ganglia and the thalamus is disturbed in schizophrenia. However, it is unknown whether the volume and shape of these subcortical structures are affected in schizophrenia with auditory hallucinations (AH), a core positive symptom of the disorder. We took structural MRI from 63 patients with schizophrenia, including 36 patients with AH and 27 patients who had never experienced AH (NAH), and 51 matched healthy controls. We extracted volumes for the left and right thalamus, globus pallidus, putamen, caudate and nucleus accumbens. Shape analysis was also carried out. When comparing to controls, the volume of the right globus pallidus, thalamus, and putamen, was only affected in AH patients. The volume of the left putamen was also increased in individuals with AH, whereas the left globus pallidus was affected in both groups of patients. The shapes of right and left putamen and thalamus were also affected in both groups. The shape of the left globus pallidus was only altered in patients lacking AH, both in comparison to controls and to cases with AH. Lastly, the general PANSS subscale was correlated with the volume of the right thalamus, and the right and left putamen, in patients with AH. We have found volume and shape alterations of many basal ganglia and thalamus in patients with and without AH, suggesting in some cases a possible relationship between this positive symptom and these morphometric alterations.

Improved clinical outcome prediction in depression using neurodynamics in an emotional face-matching functional MRI task

Introduction

Approximately one in six people will experience an episode of major depressive disorder (MDD) in their lifetime. Effective treatment is hindered by subjective clinical decision-making and a lack of objective prognostic biomarkers. Functional MRI (fMRI) could provide such an objective measure but the majority of MDD studies has focused on static approaches, disregarding the rapidly changing nature of the brain. In this study, we aim to predict depression severity changes at 3 and 6 months using dynamic fMRI features.

Methods

For our research, we acquired a longitudinal dataset of 32 MDD patients with fMRI scans acquired at baseline and clinical follow-ups 3 and 6 months later. Several measures were derived from an emotion face-matching fMRI dataset: activity in brain regions, static and dynamic functional connectivity between functional brain networks (FBNs) and two measures from a wavelet coherence analysis approach. All fMRI features were evaluated independently, with and without demographic and clinical parameters. Patients were divided into two classes based on changes in depression severity at both follow-ups.

Results

The number of coherence clusters (nCC) between FBNs, reflecting the total number of interactions (either synchronous, anti-synchronous or causal), resulted in the highest predictive performance. The nCC-based classifier achieved 87.5% and 77.4% accuracy for the 3- and 6-months change in severity, respectively. Furthermore, regression analyses supported the potential of nCC for predicting depression severity on a continuous scale. The posterior default mode network (DMN), dorsal attention network (DAN) and two visual networks were the most important networks in the optimal nCC models. Reduced nCC was associated with a poorer depression course, suggesting deficits in sustained attention to and coping with emotion-related faces. An ensemble of classifiers with demographic, clinical and lead coherence features, a measure of dynamic causality, resulted in a 3-months clinical outcome prediction accuracy of 81.2%.

Discussion

The dynamic wavelet features demonstrated high accuracy in predicting individual depression severity change. Features describing brain dynamics could enhance understanding of depression and support clinical decision-making. Further studies are required to evaluate their robustness and replicability in larger cohorts.

Multiple genes encoding mitochondrial ribosomes are downregulated in brain and blood samples of individuals with schizophrenia

OBJECTIVES

Schizophrenia is a chronic, debilitating mental disorder whose pathophysiology is complex and not fully understood. Numerous studies suggest mitochondrial dysfunction may contribute to the development of schizophrenia. While mitochondrial ribosomes (mitoribosomes) are essential for proper mitochondrial functioning, their gene expression levels have not been studied yet in schizophrenia.

METHODS

We performed a systematic meta-analysis of the expression of 81 mitoribosomes subunits encoding genes, integrating ten brain samples datasets of patients with schizophrenia compared to healthy controls (overall 422 samples, 211 schizophrenia, and 211 controls). We also performed a meta-analysis of their expression in blood, integrating two blood sample datasets (overall 90 samples, 53 schizophrenia, and 37 controls).

RESULTS

Multiple mitoribosomes subunits were significantly downregulated in brain samples (18 genes) and in blood samples (11 genes) of individuals with schizophrenia, where two showed significant downregulation in both brain and blood, MRPL4 and MRPS7.

CONCLUSIONS

Our results support the accumulating evidence of impaired mitochondrial activity in schizophrenia. While further research is needed to validate mitoribosomes' role as biomarkers, this direction has the potential to promote patients' stratification and personalised treatment for schizophrenia.

Resting-State Brain Activity Dysfunctions in Schizophrenia and Their Associations with Negative Symptom Domains: An fMRI Study

The aim of the present study was to examine the neurobiological correlates of the two negative symptom domains of schizophrenia, the Motivational Deficit domain (including avolition, anhedonia, and asociality) and the Expressive Deficit domain (including blunted affect and alogia), focusing on brain areas that are most commonly found to be associated with negative symptoms in previous literature. Resting-state (rs) fMRI data were analyzed in 62 subjects affected by schizophrenia (SZs) and 46 healthy controls (HCs). The SZs, compared to the HCs, showed higher rs brain activity in the right inferior parietal lobule and the right temporoparietal junction, and lower rs brain activity in the right dorsolateral prefrontal cortex, the bilateral anterior dorsal cingulate cortex, and the ventral and dorsal caudate. Furthermore, in the SZs, the rs brain activity in the left orbitofrontal cortex correlated with negative symptoms (r = -0.436, p = 0.006), in particular with the Motivational Deficit domain (r = -0.424, p = 0.002), even after controlling for confounding factors. The left ventral caudate correlated with negative symptoms (r = -0.407, p = 0.003), especially with the Expressive Deficit domain (r = -0.401, p = 0.003); however, these results seemed to be affected by confounding factors. In line with the literature, our results demonstrated that the two negative symptom domains might be underpinned by different neurobiological mechanisms.

Functional differentiation of the dorsal striatum: a coordinate-based neuroimaging meta-analysis

Background

The dorsal striatum, a nucleus in the basal ganglia, plays a key role in the execution of cognitive functions in the human brain. Recent studies have focused on how the dorsal striatum participates in a single cognitive function, whereas the specific roles of the caudate and putamen in performing multiple cognitive functions remain unclear. In this paper we conducted a meta-analysis of the relevant neuroimaging literature to understand the roles of subregions of the dorsal striatum in performing different functions.

Methods

PubMed, Web of Science, and BrainMap Functional Database were searched to find original functional magnetic resonance imaging (fMRI) studies conducted on healthy adults under reward, memory, emotion, and decision-making tasks, and relevant screening criteria were formulated. Single task activation, contrast activation, and conjunction activation analyses were performed using the activation likelihood estimation (ALE) method for the coordinate-based meta-analysis to evaluate the differences and linkages.

Results

In all, 112 studies were included in this meta-analysis. Analysis revealed that, of the 4 single activation tasks, reward, memory, and emotion tasks all activated the putamen more, whereas decision-making tasks activated the caudate body. Contrast analysis showed that the caudate body played an important role in the 2 cooperative activation tasks, but conjunction activation results found that more peaks appeared in the caudate head.

Discussion

Different subregions of the caudate and putamen assume different roles in processing complex cognitive behaviors. Functional division of the dorsal striatum identified specific roles of 15 different subregions, reflecting differences and connections between the different subregions in performing different cognitive behaviors.

The effects of AUT00206, a novel Kv3.1/3.2 potassium channel modulator, on task-based reward system activation: a test of mechanism in schizophrenia

The pathophysiology of schizophrenia involves abnormal reward processing, thought to be due to disrupted striatal and dopaminergic function. Consistent with this hypothesis, functional magnetic resonance imaging (fMRI) studies using the monetary incentive delay (MID) task report hypoactivation in the striatum during reward anticipation in schizophrenia. Dopamine neuron activity is modulated by striatal GABAergic interneurons. GABAergic interneuron firing rates, in turn, are related to conductances in voltage-gated potassium 3.1 (Kv3.1) and 3.2 (Kv3.2) channels, suggesting that targeting Kv3.1/3.2 could augment striatal function during reward processing. Here, we studied the effect of a novel potassium Kv3.1/3.2 channel modulator, AUT00206, on striatal activation in patients with schizophrenia, using the MID task. Each participant completed the MID during fMRI scanning on two occasions: once at baseline, and again following either 4 weeks of AUT00206 or placebo treatment. We found a significant inverse relationship at baseline between symptom severity and reward anticipation-related neural activation in the right associative striatum (r = -0.461, p = 0.035). Following treatment with AUT00206, there was a significant increase in reward anticipation-related activation in the left associative striatum (t₍₁₃₎ = 4.23, peak-level p(FWE) < 0.05)), but no significant effect in the ventral striatum. This provides preliminary evidence that the Kv3.1/3.2 potassium channel modulator, AUT00206, may address reward-related striatal abnormalities in schizophrenia.

Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review

Dysregulated frontostriatal circuitries are viewed as a common target for the treatment of aberrant behaviors in various psychiatric and neurological disorders. Accordingly, experimental neurofeedback paradigms have been applied to modify the frontostriatal circuitry. The human frontostriatal circuitry is topographically and functionally organized into the “limbic,” the “associative,” and the “motor” subsystems underlying a variety of affective, cognitive, and motor functions. We conducted a systematic review of the literature regarding functional magnetic resonance imaging-based neurofeedback studies that targeted brain activations within the frontostriatal circuitry. Seventy-nine published studies were included in our survey. We assessed the efficacy of these studies in terms of imaging findings of neurofeedback intervention as well as behavioral and clinical outcomes. Furthermore, we evaluated whether the neurofeedback targets of the studies could be assigned to the identifiable frontostriatal subsystems. The majority of studies that targeted frontostriatal circuitry functions focused on the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the supplementary motor area. Only a few studies (n = 14) targeted the connectivity of the frontostriatal regions. However, post-hoc analyses of connectivity changes were reported in more cases (n = 32). Neurofeedback has been frequently used to modify brain activations within the frontostriatal circuitry. Given the regulatory mechanisms within the closed loop of the frontostriatal circuitry, the connectivity-based neurofeedback paradigms should be primarily considered for modifications of this system. The anatomical and functional organization of the frontostriatal system needs to be considered in decisions pertaining to the neurofeedback targets.

Abnormal functional connectivity of the striatum in first-episode drug-naive early-onset Schizophrenia

Abnormal brain network connectivity is strongly implicated in the pathogenesis of schizophrenia. The striatum, consisting of the caudate and putamen, is the major treatment target for antipsychotics, the primary treatments for schizophrenia; however, there are few studies on the functional connectivity (FC) of striatum in drug-naive early-onset schizophrenia (EOS) patients. We examined the FC values of the caudate nucleus and putamen with whole brain by resting-state functional magnetic resonance imaging (RS-fMRI) and the associations with indices of clinical severity. Patients demonstrated abnormal FC between subregions of the putamen and both the visual network (left middle occipital gyrus) and default mode network (bilateral anterior cingulate, left superior frontal, and right middle frontal gyri). Furthermore, FC between dorsorostral putamen and left superior frontal gyrus correlated with both positive symptom subscore and total score on the Positive and Negative Syndrome Scale (PANSS). These findings demonstrate abnormal FC between the striatum and other brain areas even in the early stages of schizophrenia, supporting neurodevelopmental disruption in disease etiology and expression.

Aberrant striatal coupling with default mode and central executive network relates to self-reported avolition and anhedonia in schizophrenia

BACKGROUND

Avolition and anhedonia are common symptoms in schizophrenia and are related to poor long-term prognosis. There is evidence for aberrant cortico-striatal function and connectivity as neural substrate of avolition and anhedonia. However, it remains unclear how both relate to shared or distinct striatal coupling with large-scale intrinsic networks. Using resting state functional magnetic resonance imaging (rs-fMRI) this study investigated the association of large-scale cortico-striatal functional connectivity with self-reported and clinician-rated avolition and anhedonia in subjects with schizophrenia.

METHODS

Seventeen subjects with schizophrenia (SZ) and 28 healthy controls (HC) underwent rs-fMRI. Using Independent Component Analysis (ICA), we assessed Independent Components (ICs) reflecting intrinsic connectivity networks (ICNs), intra intrinsic functional connectivity within the ICs (intra-iFC), and intrinsic functional connectivity between different ICs (inter-iFC). Avolition and anhedonia were assessed using the Self Evaluation Scale for Negative Symptoms and the Brief Negative Symptom Scale.

RESULTS

ICA revealed three striatal components and six cortical ICNs. Both self-rated avolition and anhedonia correlated with increased inter-iFC between the caudate and posterior Default Mode Network (pDMN) and between the caudate and Central Executive Network (CEN). In contrast, clinician-rated avolition and anhedonia were not correlated with cortico-striatal connectivity. Group comparison revealed trend-wise decreased inter-iFC between the caudate and Salience Network (SN) in schizophrenia patients compared to HC.

DISCUSSION

Self-rated, but not clinician-rated, avolition and anhedonia was associated with aberrant striatal coupling with the default mode and the central executive network. These findings suggest that self-reported and clinician-rated scores might capture different aspects of motivational and hedonic deficits in schizophrenia and therefore relate to different cortico-striatal functional abnormalities.

Striatal and prefrontal D2R and SERT distributions contrastingly correlate with default-mode connectivity

Although brain research has taken important strides in recent decades, the interaction and coupling of its different physiological levels is still not elucidated. Specifically, the molecular substrates of resting-state functional connectivity (rs-FC) remain poorly understood. The aim of this study was elucidating interactions between dopamine D2 receptors (D2R) and serotonin transporter (SERT) availabilities in the striatum (CPu) and medial prefrontal cortex (mPFC), two of the main dopaminergic and serotonergic projection areas, and the default-mode network. Additionally, we delineated its interaction with two other prominent resting-state networks (RSNs), the salience network (SN) and the sensorimotor network (SMN). To this extent, we performed simultaneous PET/fMRI scans in a total of 59 healthy rats using [¹¹C]raclopride and [¹¹C]DASB, two tracers used to image quantify D2R and SERT respectively. Edge, node and network-level rs-FC metrics were calculated for each subject and potential correlations with binding potentials (BP_ND) in the CPu and mPFC were evaluated. We found widespread negative associations between CPu D2R availability and all the RSNs investigated, consistent with the postulated role of the indirect basal ganglia pathway. Correlations between D2Rs in the mPFC were weaker and largely restricted to DMN connectivity. Strikingly, medial prefrontal SERT correlated both positively with anterior DMN rs-FC and negatively with rs-FC between and within the SN, SMN and the posterior DMN, underlining the complex role of serotonergic neurotransmission in this region. Here we show direct relationships between rs-FC and molecular properties of the brain as assessed by simultaneous PET/fMRI in healthy rodents. The findings in the present study contribute to the basic understanding of rs-FC by revealing associations between inter-subject variances of rs-FC and receptor and transporter availabilities. Additionally, since current therapeutic strategies typically target neurotransmitter systems with the aim of normalizing brain function, delineating associations between molecular and network-level brain properties is essential and may enhance the understanding of neuropathologies and support future drug development.

Strategies to solve the reverse inference fallacy in future MRI studies of schizophrenia: a review

Few advances in schizophrenia research have been translated into clinical practice, despite 60 years of serum biomarkers studies and 50 years of genetic studies. During the last 30 years, neuroimaging studies on schizophrenia have gradually increased, partly due to the beautiful prospect that the pathophysiology of schizophrenia could be explained entirely by the Human Connectome Project (HCP). However, the fallacy of reverse inference has been a critical problem of the HCP. For this reason, there is a dire need for new strategies or research "bridges" to further schizophrenia at the biological level. To understand the importance of research "bridges," it is vital to examine the strengths and weaknesses of the recent literature. Hence, in this review, our team has summarized the recent literature (1995-2018) about magnetic resonance imaging (MRI) of schizophrenia in terms of regional and global structural and functional alterations. We have also provided a new proposal that may supplement the HCP for studying schizophrenia. As postulated, despite the vast number of MRI studies in schizophrenia, the lack of homogeneity between the studies, along with the relatedness of schizophrenia with other neurological disorders, has hindered the study of schizophrenia. In addition, the reverse inference cannot be used to diagnose schizophrenia, further limiting the clinical impact of findings from medical imaging studies. We believe that multidisciplinary technologies may be used to develop research "bridges" to further investigate schizophrenia at the single neuron or neuron cluster levels. We have postulated about future strategies for overcoming the current limitations and establishing the research "bridges," with an emphasis on multimodality imaging, molecular imaging, neuron cluster signals, single transmitter biomarkers, and nanotechnology. These research "bridges" may help solve the reverse inference fallacy and improve our understanding of schizophrenia for future studies.

Association between functional and structural connectivity of the corticostriatal network in people with schizophrenia and unaffected first-degree relatives

BACKGROUND

Dysfunction of the corticostriatal network has been implicated in the pathophysiology of schizophrenia, but findings are inconsistent within and across imaging modalities. We used multimodal neuroimaging to analyze functional and structural connectivity in the corticostriatal network in people with schizophrenia and unaffected first-degree relatives.

METHODS

We collected resting-state functional magnetic resonance imaging and diffusion tensor imaging scans from people with schizophrenia (n = 47), relatives (n = 30) and controls (n = 49). We compared seed-based functional and structural connectivity across groups within striatal subdivisions defined a priori.

RESULTS

Compared with controls, people with schizophrenia had altered connectivity between the subdivisions and brain regions in the frontal and temporal cortices and thalamus; relatives showed different connectivity between the subdivisions and the right anterior cingulate cortex (ACC) and the left precuneus. Post-hoc t tests revealed that people with schizophrenia had decreased functional connectivity in the ventral loop (ventral striatum-right ACC) and dorsal loop (executive striatum-right ACC and sensorimotor striatum-right ACC), accompanied by decreased structural connectivity; relatives had reduced functional connectivity in the ventral loop and the dorsal loop (right executive striatum-right ACC) and no significant difference in structural connectivity compared with the other groups. Functional connectivity among people with schizophrenia in the bilateral ventral striatum-right ACC was correlated with positive symptom severity.

LIMITATIONS

The number of relatives included was moderate. Striatal subdivisions were defined based on a relatively low threshold, and structural connectivity was measured based on fractional anisotropy alone.

CONCLUSION

Our findings provide insight into the role of hypoconnectivity of the ventral corticostriatal system in people with schizophrenia.

Altered amygdala-based functional connectivity in individuals with attenuated psychosis syndrome and first-episode schizophrenia

Altered resting-state functional connectivity (FC) of the amygdala (AMY) has been demonstrated to be implicated in schizophrenia (SZ) and attenuated psychosis syndrome (APS). Specifically, no prior work has investigated FC in individuals with APS using subregions of the AMY as seed regions of interest. The present study examined AMY subregion-based FC in individuals with APS and first-episode schizophrenia (FES) and healthy controls (HCs). The resting state FC maps of the three AMY subregions were computed and compared across the three groups. Correlation analysis was also performed to examine the relationship between the Z-values of regions showing significant group differences and symptom rating scores. Individuals with APS showed hyperconnectivity between the right centromedial AMY (CMA) and left frontal pole cortex (FPC) and between the laterobasal AMY and brain stem and right inferior lateral occipital cortex compared to HCs. Patients with FES showed hyperconnectivity between the right superficial AMY and left occipital pole cortex and between the left CMA and left thalamus compared to the APS and HCs respectively. A negative relationship was observed between the connectivity strength of the CMA with the FPC and negative-others score of the Brief Core Schema Scales in the APS group. We observed different altered FC with subregions of the AMY in individuals with APS and FES compared to HCs. These results shed light on the pathogenetic mechanisms underpinning the development of APS and SZ.

Brain changes associated with negative symptoms in clinical high risk for psychosis: A systematic review

The negative symptoms of schizophrenia are linked to poorer functional outcomes and decreases in quality of life, and are often the first to develop in individuals who are at clinical high risk (CHR) for psychosis. However, the accompanying neurobiological changes are poorly understood. Therefore, we conducted a systematic review of the studies that have examined the brain metrics associated with negative symptoms in those at CHR. Electronic databases were searched from inception to August 2019. Studies were selected if they mentioned negative symptoms in youth at CHR for psychosis, and brain imaging. Of 261 citations, 43 studies with 2144 CHR participants met inclusion criteria. Too few studies were focused on the same brain regions using similar neuroimaging methods to perform a meta-analysis, however, the results of this systematic review suggest a relationship between negative symptom increases and decreases in grey matter. The paucity of studies linking changes in brain structure and function with negative symptoms in those at CHR suggests that future work should focus on examining these relationships.

Disconnectivity between the raphe nucleus and subcortical dopamine-related regions contributes altered salience network in schizophrenia

Numerous studies strongly have suggested the significant role of serotonin in the pathomechanism of schizophrenia. However, few studies have directly explored the altered serotonin function in schizophrenia. In the current study, we explored the altered serotonin function in first-episode treatment-naive patients with schizophrenia with resting-state functional magnetic resonance imaging. A total 42 first-episode treatment-naive patients with schizophrenia and carefully matched healthy controls are included in the study. Considering that the raphe nucleus providing a substantial proportion of the serotonin innervation to the forebrain, the raphe nucleus was chosen as the seed to construct voxel-based functional connectivity (FC) maps. In the results, subcortical dopamine-related regions presented decreased FC with the raphe nucleus, such as the bilateral striatum, pallidum, and thalamus, in patients with schizophrenia. Decreased FC in these regions was significantly correlated with the total negative scores in PANSS. Furthermore, these regions presented with decreased FC connection to salience network. Our results presented that the raphe nucleus played an important role in the dysfunction of subcortical DA-related regions, and contributed to the altered salience network in schizophrenia. Our study emphasized the importance of the raphe nucleus in the pathophysiology of schizophrenia.

Symptomatic psychosis risk and physiological fluctuation in functional MRI data

BACKGROUND

Physiological brain pulsations have been shown to play a critical role in maintaining interstitial homeostasis in the glymphatic brain clearance mechanism. We investigated whether psychotic symptomatology is related to the physiological variation of the human brain using fMRI.

METHODS

The participants (N = 277) were from the Northern Finland Birth Cohort 1986. Psychotic symptoms were evaluated with the Positive Symptoms Scale of the Structured Interview for Prodromal Syndromes (SIPS). We used the coefficient of variation of BOLD signal (CV_BOLD) as a proxy for physiological brain pulsatility. The CV_BOLD-analyses were controlled for motion, age, sex, and educational level. The results were also compared with fMRI and voxel-based morphometry (VBM) meta-analyses of schizophrenia patients (data from the Brainmap database).

RESULTS

At the global level, participants with psychotic-like symptoms had higher CV_BOLD in cerebrospinal fluid (CSF) and white matter (WM), when compared to participants with no psychotic symptoms. Voxel-wise analyses revealed that CV_BOLD was increased, especially in periventricular white matter, basal ganglia, cerebellum and parts of the cortical structures. Those brain regions, which included alterations of physiological fluctuation in symptomatic psychosis risk, overlapped <6% with the regions that were found to be affected in the meta-analyses of previous fMRI and VBM studies in schizophrenia patients. Motion did not vary as a function of SIPS.

CONCLUSIONS

Psychotic-like symptoms were associated with elevated CV_BOLD in a variety of brain regions. The CV_BOLD findings may produce new information about cerebral physiological fluctuations that have been out of reach in previous fMRI and VBM studies.

Distinct striatum pathways connected to salience network predict symptoms improvement and resilient functioning in schizophrenia following risperidone monotherapy

Abnormal interactions between the striatum and salience network (SN) are considered as etiological and treatment-sensitive marker in schizophrenia. However, whether alterations in the intrinsic dynamics as reflected by resting-state functional connectivity (RSFC) between the striatum and salience network may predict treatment response to the widely used antipsychotic treatment strategies (risperidone, monotherapy) has not been examined systematically. To this end, treatment-naive first-episode schizophrenia patients (n = 41) underwent task-free resting-state fMRI assessment before (baseline) and after 8 weeks of risperidone monotherapy (n = 38). Intrinsic connectivity between striatal sub-regions and core salience processing nodes were examined and compared to carefully matched healthy controls (HC) to determine disorder-specific and treatment-predictive neural markers. Findings demonstrate hypo-connectivity of both ventral and dorsal striatal-SN pathways in patients at baseline. Importantly, specifically the dorsal striatal pathway at baseline could predict negative symptoms improvement in patients; while ventral striatal pathways could predict positive symptoms improvement. Together, results indicate that distinct striatal-SN pathways represent specific treatment-success markers for the effects of risperidone, suggesting that alterations in dorsal versus ventral striatal network markers may represent brain-based markers for specific symptomatologic improvements following risperidone mono-therapy.

Functional and Structural Connectivity of the Cerebellar Nuclei With the Striatum and Cerebral Cortex in First-Episode Psychosis

Evidence suggests that the cortico-striatal-thalamo-cortical circuitry plays an important role in schizophrenia pathophysiology. Cerebellar contribution from deep cerebellar nuclei to the circuitry has not yet been examined. The authors investigated resting-state functional connectivity (RSFC) of cerebellar output nuclei with striatal-thalamic-cortical regions in relation to white-matter integrity and regional gray-matter volumes in first-episode psychosis (FEP). Methods: Forty FEP patients and 40 age- and gender-matched healthy control subjects (HCs) participated. RSFC between cerebellar nuclei and striatal-thalamic-cortical regions was examined. Diffusion tensor imaging and volumetric scans were examined for possible structural constraints on RSFC. The authors also examined relationships between neuroimaging variables and cognitive and clinical measures. Results: FEP patients, compared with HCs, exhibited decreased RSFC between the left fastigial nucleus and right putamen, which was associated with poor letter fluency performance and lower global assessment of functioning scores. By contrast, patients showed widespread increased accumbens network connectivity in the left nucleus. The authors further observed both hypo- and hyper-RSFC between the cerebellar nuclei and fronto-parietal areas in patients, independent of striatal activity. Finally, the authors found impaired integrity of the left superior cerebellar peduncle and decreased bilateral putamen volume in patients, whereas structural-functional relationships found in HCs were absent in patients. Conclusions: This study provides evidence of disordered RSFC of cerebellar output nuclei to the striatum and neocortex at the early stage of schizophrenia. Furthermore, dysfunctional cerebellar influences on fronto-parietal areas that are independent of striatal dysfunction in patients with FEP were observed. The results suggest that cortico-striatal abnormalities in patients with FEP are produced by abnormal cerebellar influences.

Transdiagnostic modulation of brain networks by electroconvulsive therapy in schizophrenia and major depression

Major depressive disorder (MDD) and schizophrenia (SCZ) share neurobiological and clinical commonalities. Altered functional connectivity of large-scale brain networks has been associated with both disorders. Electroconvulsive therapy (ECT) has proven to be an effective treatment in severe forms of MDD and SCZ. However, the role of ECT on the modulation of the dynamics of brain networks is still unknown. In this study, we used resting state functional magnetic resonance imaging (rs-fMRI) to investigate functional connectivity in 16 pharmacoresistant patients with SCZ or MDD and a matched group of normal controls. Patients were scanned before and after right-sided unilateral ECT. Group spatial independent component analysis was carried out with a multiple analysis of covariance (MANCOVA) approach to estimate the effects of ECT treatment on intrinsic components (INs). Functional network connectivity (FNC) was calculated between pairs of INs. Patients had reduced connectivity within a striato-thalamic network in the thalamus as well as increased low frequency oscillations in a striatal network. ECT reduced low frequency oscillations (LFOs) on a striatal network along with increasing functional connectivity in the medial prefrontal cortex within the DMN. Following ECT treatment, the FNC of the executive network was reduced with the DMN and increased with the salience network, respectively. Our findings suggest transnosological effects of ECT on the connectivity of large-scale networks as well as at the level of their interplay. Furthermore, they support a transnosological approach for the investigation not only of the neural correlates of the disease but also of the brain mechanism of treatment of mental disorders.

Role of basal ganglia neurocircuitry in the pathology of psychiatric disorders

Over the last few decades, advances in human and animal-based techniques have greatly enhanced our understanding of the neural mechanisms underlying psychiatric disorders. Many of these studies have indicated connectivity between and alterations within basal ganglia structures to be particularly pertinent to the development of symptoms associated with several of these disorders. Here we summarize the connectivity, molecular composition, and function of sites within basal ganglia neurocircuits. Then we review the current literature from both human and animal studies concerning altered basal ganglia function in five common psychiatric disorders: obsessive-compulsive disorder, substance-related and addiction disorders, major depressive disorder, generalized anxiety disorder, and schizophrenia. Finally, we present a model based upon the findings of these studies that highlights the striatum as a particularly attractive target for restoring normal function to basal ganglia neurocircuits altered within psychiatric disorder patients.

Common and distinct changes of default mode and salience network in schizophrenia and major depression

Brain imaging reveals schizophrenia as a disorder of macroscopic brain networks. In particular, default mode and salience network (DMN, SN) show highly consistent alterations in both interacting brain activity and underlying brain structure. However, the same networks are also altered in major depression. This overlap in network alterations induces the question whether DMN and SN changes are different across both disorders, potentially indicating distinct underlying pathophysiological mechanisms. To address this question, we acquired T1-weighted, diffusion-weighted, and resting-state functional MRI in patients with schizophrenia, patients with major depression, and healthy controls. We measured regional gray matter volume, inter-regional structural and intrinsic functional connectivity of DMN and SN, and compared these measures across groups by generalized Wilcoxon rank tests, while controlling for symptoms and medication. When comparing patients with controls, we found in each patient group SN volume loss, impaired DMN structural connectivity, and aberrant DMN and SN functional connectivity. When comparing patient groups, SN gray matter volume loss and DMN structural connectivity reduction did not differ between groups, but in schizophrenic patients, functional hyperconnectivity between DMN and SN was less in comparison to depressed patients. Results provide evidence for distinct functional hyperconnectivity between DMN and SN in schizophrenia and major depression, while structural changes in DMN and SN were similar. Distinct hyperconnectivity suggests different pathophysiological mechanism underlying aberrant DMN-SN interactions in schizophrenia and depression.

Structural and Functional Neuroimaging of Polygenic Risk for Schizophrenia: A Recall-by-Genotype-Based Approach

Risk profile scores (RPS) derived from genome-wide association studies (GWAS) explain a considerable amount of susceptibility for schizophrenia (SCZ). However, little is known about how common genetic risk factors for SCZ influence the structure and function of the human brain, largely due to the constraints of imaging sample sizes. In the current study, we use a novel recall-by-genotype (RbG) methodological approach, where we sample young adults from a population cohort (Avon Longitudinal Study of Parents and Children: N genotyped = 8365) based on their SCZ-RPS. We compared 197 healthy individuals at extremes of low (N = 99) or high (N = 98) SCZ-RPS with behavioral tests, and structural and functional magnetic resonance imaging (fMRI). We first provide methodological details that will inform the design of future RbG studies for common SCZ genetic risk. We further provide an between group analysis of the RbG individuals (low vs high SCZ-RPS) who underwent structural neuroimaging data (T1-weighted scans) and fMRI data during a reversal learning task. While we found little evidence for morphometric differences between the low and high SCZ-RPS groups, we observed an impact of SCZ-RPS on blood oxygen level-dependent (BOLD) signal during reward processing in the ventral striatum (PFWE-VS-CORRECTED = .037), a previously investigated broader reward-related network (PFWE-ROIS-CORRECTED = .008), and across the whole brain (PFWE-WHOLE-BRAIN-CORRECTED = .013). We also describe the study strategy and discuss specific challenges of RbG for SCZ risk (such as SCZ-RPS related homoscedasticity). This study will help to elucidate the behavioral and imaging phenotypes that are associated with SCZ genetic risk.

Linked 4-Way Multimodal Brain Differences in Schizophrenia in a Large Chinese Han Population

Multimodal fusion has been regarded as a promising tool to discover covarying patterns of multiple imaging types impaired in brain diseases, such as schizophrenia (SZ). In this article, we aim to investigate the covarying abnormalities underlying SZ in a large Chinese Han population (307 SZs, 298 healthy controls [HCs]). Four types of magnetic resonance imaging (MRI) features, including regional homogeneity (ReHo) from resting-state functional MRI, gray matter volume (GM) from structural MRI, fractional anisotropy (FA) from diffusion MRI, and functional network connectivity (FNC) resulted from group independent component analysis, were jointly analyzed by a data-driven multivariate fusion method. Results suggest that a widely distributed network disruption appears in SZ patients, with synchronous changes in both functional and structural regions, especially the basal ganglia network, salience network (SAN), and the frontoparietal network. Such a multimodal coalteration was also replicated in another independent Chinese sample (40 SZs, 66 HCs). Our results on auditory verbal hallucination (AVH) also provide evidence for the hypothesis that prefrontal hypoactivation and temporal hyperactivation in SZ may lead to failure of executive control and inhibition, which is relevant to AVH. In addition, impaired working memory performance was found associated with GM reduction and FA decrease in SZ in prefrontal and superior temporal area, in both discovery and replication datasets. In summary, by leveraging multiple imaging and clinical information into one framework to observe brain in multiple views, we can integrate multiple inferences about SZ from large-scale population and offer unique perspectives regarding the missing links between the brain function and structure that may not be achieved by separate unimodal analyses.

Data-Driven Analysis of Functional Connectivity Reveals a Potential Auditory Verbal Hallucination Network

Schizophrenia is a severe global health problem, with over half of such patients experiencing auditory verbal hallucinations (AVHs). A better understanding of the neural correlates differentiating patients experiencing AVHs from patients not experiencing AVHs and healthy controls may identify targets that lead to better treatment strategies for AVHs. Employing 2 data-driven, voxel-based measure of functional connectivity, we studied 46 patients with schizophrenia or schizoaffective disorder (28 experiencing AVHs and 18 not experiencing AVHs). Twenty healthy controls matched for age, gender, ethnicity, education level, handedness, and estimated verbal intelligence were included for comparison. The intrinsic connectivity distribution (ICD) was used to model each voxel's connectivity to the rest of the brain using a Weibull distribution. To investigate lateralization of connectivity, we used cross-hemisphere ICD, a method that separates the contribution of each hemisphere to interrogate connectivity laterality. Patients with AVHs compared with patients without AVHs exhibited significantly decreased whole-brain connectivity in the medial prefrontal cortex and posterior cingulate cortex, less lateralized connectivity in left putamen, and more lateralized connectivity in left interior frontal gyrus. Correlations with Auditory Hallucination Rating Scale (AHRS) and post hoc seed connectivity analyses revealed significantly altered network connectivity. Using the results from all analyses comparing the patient groups and correlations with AHRS, we identified a potential AVH network, consisting of 25 nodes, showing substantial overlap with the default mode network and language processing networks. This network as a whole, instead of individual nodes, may represent actionable targets for interventions.

Schizophrenia, Dopamine and the Striatum: From Biology to Symptoms

The mesolimbic hypothesis has been a central dogma of schizophrenia for decades, positing that aberrant functioning of midbrain dopamine projections to limbic regions causes psychotic symptoms. Recently, however, advances in neuroimaging techniques have led to the unanticipated finding that dopaminergic dysfunction in schizophrenia is greatest within nigrostriatal pathways, implicating the dorsal striatum in the pathophysiology and calling into question the mesolimbic theory. At the same time our knowledge of striatal anatomy and function has progressed, suggesting new mechanisms via which striatal dysfunction may contribute to the symptoms of schizophrenia. This Review draws together these developments, to explore what they mean for our understanding of the pathophysiology, clinical manifestations, and treatment of the disorder.

Techniques for characterising the mesostriatal dopamine system, both in humans and animal models, have advanced significantly over the past decade.

In vivo imaging studies in schizophrenia patients demonstrate that dopaminergic dysfunction in schizophrenia is greatest in nigrostriatal as opposed to mesolimbic pathways.

Better understanding of striatal structure and function has enhanced our insight into the neurobiological basis of psychotic symptoms.

The role of other neurotransmitters in modulating striatal dopamine function merits further exploration, and modulating these neurotransmitter systems has potential to offer new therapeutic strategies.

Activation of the motivation-related ventral striatum during delusional experience

Delusion is the most characteristic symptom of psychosis, occurring in almost all first-episode psychosis patients. The motivational salience hypothesis suggests delusion to originate from the experience of abnormal motivational salience. Whether the motivation-related brain circuitries are activated during the actual delusional experience remains, however, unknown. We used a forced-choice answering tree at random intervals during functional magnetic resonance imaging to capture delusional and non-delusional spontaneous experiences in patients with first-episode psychosis (n = 31) or clinical high-risk state (n = 7). The motivation-related brain regions were identified by an automated meta-analysis of 149 studies. Thirteen first-episode patients reported both delusional and non-delusional spontaneous experiences. In these patients, delusional experiences were related to stronger activation of the ventral striatum in both hemispheres. This activation overlapped with the most strongly motivation-related brain regions. These findings provide an empirical link between the actual delusional experience and the motivational salience hypothesis. Further use and development of the present methods in localizing the neurobiological basis of the most characteristic symptoms may be useful in the search for etiopathogenic pathways that result in psychotic disorders.

Multi-echo fMRI, resting-state connectivity, and high psychometric schizotypy

Disrupted striatal functional connectivity is proposed to play a critical role in the development of psychotic symptoms. Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies typically reported disrupted striatal connectivity in patients with psychosis and in individuals at clinical and genetic high risk of the disorder relative to healthy controls. This has not been widely studied in healthy individuals with subclinical psychotic-like experiences (schizotypy). Here we applied the emerging technology of multi-echo rs-fMRI to examine corticostriatal connectivity in this group, which is thought to drastically maximize physiological noise removal and increase BOLD contrast-to-noise ratio. Multi-echo rs-fMRI data (echo times, 12, 28, 44, 60 ms) were acquired from healthy individuals with low (LS, n = 20) and high (HS, n = 19) positive schizotypy as determined with the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE). After preprocessing to ensure optimal contrast and removal of non-BOLD signal components, whole-brain functional connectivity from six striatal seeds was compared between the HS and LS groups. Effects were considered significant at cluster-level p < .05 family-wise error correction. Compared to LS, HS subjects showed lower rs-fMRI connectivity between ventromedial prefrontal regions and ventral striatal regions. Lower connectivity was also observed between the dorsal putamen and the hippocampus, occipital regions, as well as the cerebellum. These results demonstrate that subclinical positive psychotic-like experiences in healthy individuals are associated with striatal hypoconnectivity as detected using multi-echo rs-fMRI. Further application of this approach may aid in characterizing functional connectivity abnormalities across the extended psychosis phenotype.

Brain volumetric alterations accompanied with loss of striatal medium-sized spiny neurons and cortical parvalbumin expressing interneurons in Brd1+/- mice

Schizophrenia is a common and severe mental disorder arising from complex gene-environment interactions affecting brain development and functioning. While a consensus on the neuroanatomical correlates of schizophrenia is emerging, much of its fundamental pathobiology remains unknown. In this study, we explore brain morphometry in mice with genetic susceptibility and phenotypic relevance to schizophrenia (Brd1^+/− mice) using postmortem 3D MR imaging coupled with histology, immunostaining and regional mRNA marker analysis. In agreement with recent large-scale schizophrenia neuroimaging studies, Brd1^+/− mice displayed subcortical abnormalities, including volumetric reductions of amygdala and striatum. Interestingly, we demonstrate that structural alteration in striatum correlates with a general loss of striatal neurons, differentially impacting subpopulations of medium-sized spiny neurons and thus potentially striatal output. Akin to parvalbumin interneuron dysfunction in patients, a decline in parvalbumin expression was noted in the developing cortex of Brd1^+/− mice, mainly driven by neuronal loss within or near cortical layer V, which is rich in corticostriatal projection neurons. Collectively, our study highlights the translational value of the Brd1^+/− mouse as a pre-clinical tool for schizophrenia research and provides novel insight into its developmental, structural, and cellular pathology.

Using fMRI and machine learning to predict symptom improvement following cognitive behavioural therapy for psychosis

Cognitive behavioural therapy for psychosis (CBTp) involves helping patients to understand and reframe threatening appraisals of their psychotic experiences to reduce distress and increase functioning. Whilst CBTp is effective for many, it is not effective for all patients and the factors predicting a good outcome remain poorly understood. Machine learning is a powerful approach that allows new predictors to be identified in a data-driven way, which can inform understanding of the mechanisms underlying therapeutic interventions, and ultimately make predictions about symptom improvement at the individual patient level. Thirty-eight patients with a diagnosis of schizophrenia completed a social affect task during functional MRI. Multivariate pattern analysis assessed whether treatment response in those receiving CBTp (n = 22) could be predicted by pre-therapy neural responses to facial affect that was either threat-related (ambiguous ‘neutral’ faces perceived as threatening in psychosis, in addition to angry and fearful faces) or prosocial (happy faces). The models predicted improvement in psychotic (r = 0.63, p = 0.003) and affective (r = 0.31, p = 0.05) symptoms following CBTp, but not in the treatment-as-usual group (n = 16). Psychotic symptom improvement was predicted by neural responses to threat-related affect across sensorimotor and frontal-limbic regions, whereas affective symptom improvement was predicted by neural responses to fearful faces only as well as prosocial affect across sensorimotor and frontal regions. These findings suggest that CBTp most likely improves psychotic and affective symptoms in those endorsing more threatening appraisals and mood-congruent processing biases, respectively, which are explored and reframed as part of the therapy. This study improves our understanding of the neurobiology of treatment response and provides a foundation that will hopefully lead to greater precision and tailoring of the interventions offered to patients.

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Machine learning models using neuroimaging data can predict response to CBTp.

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Neural responses to social threat predicted improvement in psychotic symptoms.

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Activation related to different social stimuli predicted distinct symptom domains.

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Predictors included activity in the hippocampus, frontal, and sensorimotor regions.

Frequency specific resting state functional abnormalities in psychosis

Resting state functional magnetic resonance imaging studies of psychosis have focused primarily on the amplitude of low-frequency fluctuations in the blood oxygen level dependent (BOLD) signal ranging from .01 to 0.1 Hz. Few studies, however, have investigated the amplitude of frequency fluctuations within discrete frequency bands and higher than 0.1 Hz in patients with psychosis at different illness stages. We investigated BOLD signal within three frequency ranges including slow-4 (.027-.073 Hz), slow-3 (.074-0.198 Hz) and slow-2 (0.199-0.25 Hz) in 89 patients with either first-episode or chronic psychosis and 119 healthy volunteers. We investigated the amplitude of frequency fluctuations within three frequency bands using 47 regions-of-interest placed within 14 known resting state networks derived using group independent component analysis. There were significant group x frequency interactions for the visual and motor cortex networks, with the largest significant group differences (patients < healthy volunteers) evident in slow-4 and slow-3, respectively. Also, healthy volunteers had an overall higher amplitude of frequency fluctuations compared to patients across the three frequency ranges in the visual cortex, dorsal attention and motor cortex networks with the opposite effect (patients > healthy volunteers) evident within the salience and frontal gyrus networks. Subsequent analyses indicated that these effects were evident in both first-episode and chronic patients. Our study provides new data regarding the importance of BOLD signal fluctuations within different frequency bands in the neurobiology of psychosis.

Attention Deficit Hyperactivity Disorder Symptoms and Psychosis in 22q11.2 Deletion Syndrome

OBJECTIVE

22q11.2 Deletion Syndrome (22q11.2DS) is associated with increased risk for schizophrenia in adulthood while Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent diagnosis in childhood. Inattention symptoms are pronounced in 22q11.2DS and given that attentional impairment is a core feature of schizophrenia, inattention symptoms may reflect underlying ADHD, psychosis, or both. We investigate whether inattention is associated with psychosis in 22q11.2DS and in other groups at risk for psychosis but without the deletion (ND) (idiopathic clinical risk and first degree family members of individuals with schizophrenia).

METHODS

One hundred thirty-seven individuals with 22q11.2DS (mean age: 14.0), 84 ND individuals with subthreshold psychosis (mean age: 16.9) and 31 ND individuals with family history of psychosis (mean age: 17.0) were included in the study. Psychopathology was assessed using research diagnostic assessments.

RESULTS

ADHD total symptoms were associated with overall levels of subthreshold psychosis symptoms in 22q11.2DS (β = .8, P = .04). Inattention symptoms were specifically associated with positive (β = .5, P = .004), negative (β = .5, P = .03), and disorganized (β = .5, P < .001) symptoms, while hyperactivity-impulsivity symptoms were associated with disorganized symptoms (β = .5, P = .01). The prevalence of ADHD inattention symptoms was higher in 22q11.2DS with subthreshold psychosis compared to ND individuals with subthreshold psychosis (P < .001), even when adjusting for cognitive impairment and overall psychopathology. The pattern was similar when comparing individuals with 22q11.2DS and ND individuals with family history of psychosis.

CONCLUSIONS

This is the first study to examine the associations between ADHD symptoms and psychosis in 22q11.2DS. Our findings support a potentially important role of ADHD inattention symptoms in psychosis in 22q11.2DS.

Identifying Resting-State Multifrequency Biomarkers via Tree-Guided Group Sparse Learning for Schizophrenia Classification

The fractional amplitude of low-frequency fluctuations (fALFF) has been widely used as potential clinical biomarkers for resting-state functional-magnetic-resonance-imaging-based schizophrenia diagnosis. How-ever, previous studies usually measure the fALFF with specific bands from 0.01 to 0.08 Hz, which cannot fully delineate the complex variations of spontaneous fluctuations in the resting-state brain. In addition, fALFF data are intrinsically constrained by the brain structure, but most of the traditional methods have not consider it in feature selection. For addressing these problems, we propose a model to classify schizophrenia in multifrequency bands with tree-guided group sparse learning. In detail, we first acquire the fALFF data in multifrequency bands (i.e., slow-5: 0.01-0.027 Hz, slow-4: 0.027-0.073 Hz, slow-3: 0.073-0.198 Hz, and slow-2: 0.198-0.25 Hz). Then, we divide the whole brain into different candidate patches and select those significant patches related to schizophrenia using random forest-based important score. Moreover, we use tree-structured sparse learning method for feature selection with the above patch spatial constraint. Finally, considering biomarkers from multifrequency bands can reflect complementary information among multiple-frequency bands, we adopt the multikernel learning method to combine features of multifrequency bands for classification. Our experimental results show that these biomarkers from multifrequency bands can achieve a classification accuracy of 91.1% on 17 schizophrenia patients and 17 healthy controls, further demonstrating that the multifrequency bands analysis can better account for classification of schizophrenia.

Resting-state functional connectivity remains unaffected by preceding exposure to aversive visual stimuli

While much is known about immediate brain activity changes induced by the confrontation with emotional stimuli, the subsequent temporal unfolding of emotions has yet to be explored. To investigate whether exposure to emotionally aversive pictures affects subsequent resting-state networks differently from exposure to neutral pictures, a resting-state fMRI study implementing a two-group repeated-measures design in healthy young adults (N = 34) was conducted. We focused on investigating (i) patterns of amygdala whole-brain and hippocampus connectivity in both a seed-to-voxel and seed-to-seed approach, (ii) whole-brain resting-state networks with an independent component analysis coupled with dual regression, and (iii) the amygdala's fractional amplitude of low frequency fluctuations, all while EEG recording potential fluctuations in vigilance. In spite of the successful emotion induction, as demonstrated by stimuli rating and a memory-facilitating effect of negative emotionality, none of the resting-state measures was differentially affected by picture valence. In conclusion, resting-state networks connectivity as well as the amygdala's low frequency oscillations appear to be unaffected by preceding exposure to widely used emotionally aversive visual stimuli in healthy young adults.

Functional dysconnectivity of the limbic loop of frontostriatal circuits in first-episode, treatment-naive schizophrenia

Frontostriatal circuits dysfunction has been implicated in the etiology and psychopathology of patients with schizophrenia (SZ). However, few studies have investigated SZ-related functional connectivity (FC) alterations in discrete frontostriatal circuits and their relationship with pathopsychology in first-episode schizophrenia (FESZ). The goal of this study was to identify dysfunctions in discrete frontostriatal circuits that are associated with key features of FESZ. To this end, a case-control, cross-sectional study was conducted, wherein resting-state (RS) functional magnetic resonance (fMRI) data were collected from 37 treatment-naïve FESZ patients and 29 healthy control (HC) subjects. Seed-based FC analyses were performed by placing six bilateral pairs of seeds within a priori defined subdivisions of the striatum. We observed significantly decreased FC for the FESZ group relative to the HC group [p < .05, family-wise error (FWE)-corrected] in the limbic loop, but not in the sensorimotor or associative loops, of frontostriatal circuitry. Moreover, bilaterally decreased inferior ventral striatum/nucleus accumbens (VSi)-dorsal anterior cingulate cortex (dACC) FC within the limbic loop correlated inversely with overall FESZ symptom severity and the disorganization factor score of PANSS. These findings provide new insight into the role of frontostriatal limbic loop hypoconnectivity in early-stage schizophrenia pathology and suggest potential novel therapeutic targets.

Ventral striatal dopaminergic defect is associated with hallucinations in Parkinson's disease

BACKGROUND AND PURPOSE

Visual hallucinations (VHs) are a common complication of Parkinson's disease (PD). The pathogenesis of VHs in PD is still largely unclear. The aim of this study was to investigate the dopaminergic mechanisms of VHs and specifically whether the degree of striatal dopamine transporter (DAT) function or extrastriatal serotonin transporter (SERT) function can predict the appearance of VHs in patients with PD.

METHODS

Twenty-two PD patients scanned with [¹²³ I]FP-CIT single photon emission computed tomography at an early stage of their disease who later developed VHs were identified and compared with 48 non-hallucinating PD patients. The groups were matched for age, medication, disease duration and motor symptom severity. Clinical follow-up after the scan was a median (range) of 6.9 (3.8-9.6) years. Imaging analyses were performed with both regions-of-interest-based and voxel-based (Statistical Parametric Mapping) methods for the striatal and extrastriatal regions.

RESULTS

The median interval between the scan and the emergence of VHs was 4.8 years. Patients who developed VHs had 18.4% lower DAT binding in the right ventral striatum (P = 0.009), 16.7% lower binding in the left ventral striatum (P = 0.02) and 18.8% lower binding in the right putamen (P = 0.03) compared to patients who did not develop VHs.

CONCLUSIONS

Low striatal DAT function may predispose PD patients to VHs, and the regional distribution of the findings suggests a particular role of the ventral striatum. This is in line with non-PD research that has implicated ventral striatal dysfunction in psychosis.

Structural Basis of Large-Scale Functional Connectivity in the Mouse

Translational neuroimaging requires approaches and techniques that can bridge between multiple different species and disease states. One candidate method that offers insights into the brain's functional connectivity (FC) is resting-state fMRI (rs-fMRI). In both humans and nonhuman primates, patterns of FC (often referred to as the functional connectome) have been related to the underlying structural connectivity (SC; also called the structural connectome). Given the recent rise in preclinical neuroimaging of mouse models, it is an important question whether the mouse functional connectome conforms to the underlying SC. Here, we compared FC derived from rs-fMRI in female mice with the underlying monosynaptic structural connectome as provided by the Allen Brain Connectivity Atlas. We show that FC between interhemispheric homotopic cortical and hippocampal areas, as well as in cortico-striatal pathways, emerges primarily via monosynaptic structural connections. In particular, we demonstrate that the striatum (STR) can be segregated according to differential rs-fMRI connectivity patterns that mirror monosynaptic connectivity with isocortex. In contrast, for certain subcortical networks, FC emerges along polysynaptic pathways as shown for left and right STR, which do not share direct anatomical connections, but high FC is putatively driven by a top-down cortical control. Finally, we show that FC involving cortico-thalamic pathways is limited, possibly confounded by the effect of anesthesia, small regional size, and tracer injection volume. These findings provide a critical foundation for using rs-fMRI connectivity as a translational tool to study complex brain circuitry interactions and their pathology due to neurological or psychiatric diseases across species.SIGNIFICANCE STATEMENT A comprehensive understanding of how the anatomical architecture of the brain, often referred to as the "connectome," corresponds to its function is arguably one of the biggest challenges for understanding the brain and its pathologies. Here, we use the mouse as a model for comparing functional connectivity (FC) derived from resting-state fMRI with gold standard structural connectivity measures based on tracer injections. In particular, we demonstrate high correspondence between FC measurements of cortico-cortical and cortico-striatal regions and their anatomical underpinnings. This work provides a critical foundation for studying the pathology of these circuits across mouse models and human patients.

Functional brain networks in treatment-resistant schizophrenia

INTRODUCTION

Up to 20% of individuals with schizophrenia show minimal or no response to medication and are considered to have 'treatment-resistant' schizophrenia (TRS). Unlike early and established schizophrenia, few studies have investigated resting-state functional connectivity (rs-FC) in TRS. Here, we test for disruptions in FC and altered efficiency of functional brain networks in a well-characterized cohort of TRS patients.

METHODS

Resting-state functional magnetic resonance imaging was used to investigate functional brain networks in 42 TRS participants prescribed clozapine (30 males, mean age=41.3(10)) and 42 healthy controls (24 males, mean age=38.4(10)). Graph analysis was used to characterize between-group differences in local and global efficiency of functional brain network organization as well as the strength of FC.

RESULTS

Global brain FC was reduced in TRS patients (p=0.0001). Relative to controls, 3.4% of all functional connections showed reduced strength in TRS (p<0.001), predominantly involving fronto-temporal, fronto-occipital and temporo-occipital connections. Global efficiency was reduced in TRS (p=0.0015), whereas local efficiency was increased (p=0.0042).

CONCLUSIONS

TRS is associated with widespread reductions in rs-FC and altered network topology. Increased local functional network efficiency coupled with decreased global efficiency suggests that hub-to-hub connections are preferentially affected in TRS. These findings further our understanding of the neurobiological impairments in TRS.

Electroconvulsive therapy-induced brain functional connectivity predicts therapeutic efficacy in patients with schizophrenia: a multivariate pattern recognition study

Previous studies suggested that electroconvulsive therapy can influence regional metabolism and dopamine signaling, thereby alleviating symptoms of schizophrenia. It remains unclear what patients may benefit more from the treatment. The present study sought to identify biomarkers that predict the electroconvulsive therapy response in individual patients. Thirty-four schizophrenia patients and 34 controls were included in this study. Patients were scanned prior to treatment and after 6 weeks of treatment with antipsychotics only (n = 16) or a combination of antipsychotics and electroconvulsive therapy (n = 13). Subject-specific intrinsic connectivity networks were computed for each subject using a group information-guided independent component analysis technique. Classifiers were built to distinguish patients from controls and quantify brain states based on intrinsic connectivity networks. A general linear model was built on the classification scores of first scan (referred to as baseline classification scores) to predict treatment response. Classifiers built on the default mode network, the temporal lobe network, the language network, the corticostriatal network, the frontal-parietal network, and the cerebellum achieved a cross-validated classification accuracy of 83.82%, with specificity of 91.18% and sensitivity of 76.47%. After the electroconvulsive therapy, psychosis symptoms of the patients were relieved and classification scores of the patients were decreased. Moreover, the baseline classification scores were predictive for the treatment outcome. Schizophrenia patients exhibited functional deviations in multiple intrinsic connectivity networks which were able to distinguish patients from healthy controls at an individual level. Patients with lower classification scores prior to treatment had better treatment outcome, indicating that the baseline classification scores before treatment is a good predictor for treatment outcome.

Changes in extra-striatal functional connectivity in patients with schizophrenia in a psychotic episode

BACKGROUND

In patients with schizophrenia in a psychotic episode, intra-striatal intrinsic connectivity is increased in the putamen but not ventral striatum. Furthermore, multimodal changes have been observed in the anterior insula that interact extensively with the putamen.

AIMS

We hypothesised that during psychosis, putamen extra-striatal functional connectivity is altered with both the anterior insula and areas normally connected with the ventral striatum (i.e. altered functional connectivity distinctiveness of putamen and ventral striatum).

METHOD

We acquired resting-state functional magnetic resonance images from 21 patients with schizophrenia in a psychotic episode and 42 controls.

RESULTS

Patients had decreased functional connectivity: the putamen with right anterior insula and dorsal prefrontal cortex, the ventral striatum with left anterior insula. Decreased functional connectivity between putamen and right anterior insula was specifically associated with patients' hallucinations. Functional connectivity distinctiveness was impaired only for the putamen.

CONCLUSIONS

Results indicate aberrant extra-striatal connectivity during psychosis and a relationship between reduced putamen-right anterior insula connectivity and hallucinations. Data suggest that altered intrinsic connectivity links striatal and insular pathophysiology in psychosis.

Progressively Disrupted Intrinsic Functional Connectivity of Basolateral Amygdala in Very Early Alzheimer's Disease

Very early Alzheimer’s disease (AD) – i.e., AD at stages of mild cognitive impairment (MCI) and mild dementia – is characterized by progressive structural and neuropathologic changes, such as atrophy or tangle deposition in medial temporal lobes, including hippocampus and entorhinal cortex and also adjacent amygdala. While progressively disrupted intrinsic connectivity of hippocampus with other brain areas has been demonstrated by many studies, amygdala connectivity was rarely investigated in AD, notwithstanding its known relevance for emotion processing and mood disturbances, which are both important in early AD. Intrinsic functional connectivity (iFC) patterns of hippocampus and amygdala overlap in healthy persons. Thus, we hypothesized that increased alteration of iFC patterns along AD is not limited to the hippocampus but also concerns the amygdala, independent from atrophy. To address this hypothesis, we applied structural and functional resting-state MRI in healthy controls (CON, n = 33) and patients with AD in the stages of MCI (AD-MCI, n = 38) and mild dementia (AD-D, n = 36). Outcome measures were voxel-based morphometry (VBM) values and region-of-interest-based iFC maps of basolateral amygdala, which has extended cortical connectivity. Amygdala VBM values were progressively reduced in patients (CON > AD-MCI and AD-D). Amygdala iFC was progressively reduced along impairment severity (CON > AD-MCI > AD-D), particularly for hippocampus, temporal lobes, and fronto-parietal areas. Notably, decreased iFC was independent of amygdala atrophy. Results demonstrate progressively impaired amygdala intrinsic connectivity in temporal and fronto-parietal lobes independent from increasing amygdala atrophy in very early AD. Data suggest that early AD disrupts intrinsic connectivity of medial temporal lobe key regions, including that of amygdala.

Auditory Hallucinations and the Brain's Resting-State Networks: Findings and Methodological Observations

In recent years, there has been increasing interest in the potential for alterations to the brain's resting-state networks (RSNs) to explain various kinds of psychopathology. RSNs provide an intriguing new explanatory framework for hallucinations, which can occur in different modalities and population groups, but which remain poorly understood. This collaboration from the International Consortium on Hallucination Research (ICHR) reports on the evidence linking resting-state alterations to auditory hallucinations (AH) and provides a critical appraisal of the methodological approaches used in this area. In the report, we describe findings from resting connectivity fMRI in AH (in schizophrenia and nonclinical individuals) and compare them with findings from neurophysiological research, structural MRI, and research on visual hallucinations (VH). In AH, various studies show resting connectivity differences in left-hemisphere auditory and language regions, as well as atypical interaction of the default mode network and RSNs linked to cognitive control and salience. As the latter are also evident in studies of VH, this points to a domain-general mechanism for hallucinations alongside modality-specific changes to RSNs in different sensory regions. However, we also observed high methodological heterogeneity in the current literature, affecting the ability to make clear comparisons between studies. To address this, we provide some methodological recommendations and options for future research on the resting state and hallucinations.

Increased Nigral SLC6A3 Activity in Schizophrenia Patients: Findings From the Toronto-McLean Cohorts

SLC6A3, which encodes the primary regulator of extracellular dopamine (DA) concentration, the DA transporter, has been implicated in schizophrenia (SCZ). However, the details of its genetic effect on risk remain largely unknown. The purpose of this candidate gene study was to identify a specificSLC6A3activity associated with SCZ by using functional genetic approaches. We first examined gene activity in DA neurons isolated from case-control postmortem nigral tissue and found that the averageSLC6A3mRNA level in controls was only 0.37-fold of that in cases (P= .0034). To understand this expression difference, we examined the association of 10 genetic markers, mostly located in the promoter region, with SCZ in 1717 subjects collected from Toronto and McLean cohorts, including 881 controls and 836 cases and identified the 5' promoter SNP rs1478435 as having a significant association signal (uncorrectedPvalue: .00462; adjustedPvalue: .0319) in unrelated Caucasians. Allele T was over-represented in controls (OR = .75); T-carrier controls had decreased mRNA levels in nigral DA neurons, contributing to the reduced activity in the controls. In vitro functional analysis confirmed that T carriers displayed attenuated enhancement of promoter activity. These findings collectively suggest that increased nigralSLC6A3activity may be a risk factor for SCZ, and may help to explain high rates of comorbidity with substance abuse.

Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity

Recently, functional network connectivity (FNC, defined as the temporal correlation among spatially distant brain networks) has been used to examine the functional organization of brain networks in various psychiatric illnesses. Dynamic FNC is a recent extension of the conventional FNC analysis that takes into account FNC changes over short periods of time. While such dynamic FNC measures may be more informative about various aspects of connectivity, there has been no detailed head-to-head comparison of the ability of static and dynamic FNC to perform classification in complex mental illnesses. This paper proposes a framework for automatic classification of schizophrenia, bipolar and healthy subjects based on their static and dynamic FNC features. Also, we compare cross-validated classification performance between static and dynamic FNC. Results show that the dynamic FNC significantly outperforms the static FNC in terms of predictive accuracy, indicating that features from dynamic FNC have distinct advantages over static FNC for classification purposes. Moreover, combining static and dynamic FNC features does not significantly improve the classification performance over the dynamic FNC features alone, suggesting that static FNC does not add any significant information when combined with dynamic FNC for classification purposes. A three-way classification methodology based on static and dynamic FNC features discriminates individual subjects into appropriate diagnostic groups with high accuracy. Our proposed classification framework is potentially applicable to additional mental disorders.

Opposing effects of acute and chronic d-amphetamine on decision-making in rats

Amphetamine and other drugs of abuse have both short-term and long-lasting effects on brain function, and drug sensitization paradigms often result in chronic impairments in behavioral flexibility. Here we show that acute amphetamine administration temporarily renders rats less sensitive to reward omission, as revealed by a decrease in lose-shift responding during a binary choice task. Intracerebral infusions of amphetamine into the ventral striatum did not affect lose-shift responding but did increase impulsive behavior in which rats chose to check both reward feeders before beginning the next trial. In contrast to acute systemic and intracerebral infusions, sensitization through repeated exposure induced long-lasting increased sensitivity to reward omission. These treatments did not affect choices on trials following reward delivery (i.e. win-stay responding), and sensitization increased spine density in the sensorimotor striatum. The dichotomous effects of amphetamine on short-term and long-term loss sensitivity, and the null effect on win-stay responding, are consistent with a shift of behavioral control to the sensorimotor striatum after drug sensitization. These data provide a new demonstration of such a shift in a novel task unrelated to drug administration, and suggests that the dominance of sensorimotor control persists over many hundreds of trials after sensitization.

Multiprobe molecular imaging of an NMDA receptor hypofunction rat model for glutamatergic dysfunction

There are many indications of a connection between abnormal glutamate transmission through N-methyl-d-aspartate (NMDA) receptor hypofunction and the occurrence of schizophrenia. The importance of metabotropic glutamate receptor subtype 5 (mGluR5) became generally recognized due to its physical link through anchor proteins with NMDAR. Neuroinflammation as well as the kynurenine (tryptophan catabolite; TRYCAT) pathway are equally considered as major contributors to the pathology. We aimed to investigate this interplay between glutamate release, neuronal activation and inflammatory markers, by using small-animal positron emission tomography (PET) in a rat model known to induce schizophrenia-like symptoms. Daily intraperitoneal injection of MK801 or saline were administered to induce the model together with N-Acetyl-cysteine (NAc) or saline as the treatment in 24 male Sprague Dawley rats for one month. Biweekly in vivo [(11)C]-ABP688 microPET was performed together with mGluR5 immunohistochemistry. Simultaneously, weekly in vivo [(18)F]-FDG microPET imaging data for glucose metabolism was acquired and microglial activation was investigated with biweekly in vivo [(18)F]-PBR111 scans versus OX42 immunohistochemistry. Finally, plasma samples were analyzed for TRYCAT metabolites. We show that chronic MK801 administration (and thus elevated endogenous glutamate) causes significant tissue loss in rat brain, enhances neuroinflammatory pathways and may upregulate mGluR5 expression.

More Consistently Altered Connectivity Patterns for Cerebellum and Medial Temporal Lobes than for Amygdala and Striatum in Schizophrenia

BACKGROUND

Brain architecture can be divided into a cortico-thalamic system and modulatory "subcortical-cerebellar" systems containing key structures such as striatum, medial temporal lobes (MTLs), amygdala, and cerebellum. Subcortical-cerebellar systems are known to be altered in schizophrenia. In particular, intrinsic functional brain connectivity (iFC) between these systems has been consistently demonstrated in patients. While altered connectivity is known for each subcortical-cerebellar system separately, it is unknown whether subcortical-cerebellar systems' connectivity patterns with the cortico-thalamic system are comparably altered across systems, i.e., if separate subcortical-cerebellar systems' connectivity patterns are consistent across patients.

METHODS

To investigate this question, 18 patients with schizophrenia (3 unmedicated, 15 medicated with atypical antipsychotics) and 18 healthy controls were assessed by resting-state functional magnetic resonance imaging (fMRI). Independent component analysis of fMRI data revealed cortical intrinsic brain networks (NWs) with time courses representing proxies for cortico-thalamic system activity. Subcortical-cerebellar systems' activity was represented by fMRI-based time courses of selected regions-of-interest (ROIs; i.e., striatum, MTL, amygdala, cerebellum). Correlation analysis among ROI- and NWs-time courses yielded individual connectivity matrices [i.e., connectivity between NW and ROIs (allROIs-NW, separateROI-NW), only NWs (NWs-NWs), and only ROIs (allROIs-allROIs)] as main outcome measures, which were classified by support-vector-machine-based (SVM) leave-one-out cross-validation. Differences in classification accuracy were statistically evaluated for consistency across subjects and systems.

RESULTS

Correlation matrices based on allROIs-NWs yielded 91% classification accuracy, which was significantly superior to allROIs-allROIs and NWs-NWs (56 and 74%, respectively). Considering separate subcortical-cerebellar systems, cerebellum-NWs and MTL-NWs reached highest accuracy values with 91 and 85%, respectively, while those of striatum-NW and amygdala-NW were significantly lower with about 65% classification accuracy.

CONCLUSION

RESULTS provide initial evidence for differential consistency of altered intrinsic connectivity patterns between subcortical-cerebellar systems and the cortico-thalamic system. Data suggest that differential dysconnectivity patterns between subcortical-cerebellar and cortical systems might reflect different disease states or patient subgroups.