Antipsychotic treatment and functional connectivity of the striatum in first-episode schizophrenia

Genetic deletion of GPR52 enhances the locomotor-stimulating effect of an adenosine A2A receptor antagonist in mice: A potential role of GPR52 in the function of striatopallidal neurons

G protein-coupled receptor 52 (GPR52) is largely co-expressed with dopamine D₂ receptor (DRD2) in the striatum and nucleus accumbens, and this expression pattern is similar to that of adenosine A_2A receptor (ADORA2A). GPR52 has been proposed as a therapeutic target for positive symptoms of schizophrenia, based on observations from pharmacological and transgenic mouse studies. However, the physiological role of GPR52 in dopaminergic functions in the basal ganglia remains unclear. Here, we used GPR52 knockout (KO) mice to examine the role of GPR52 in dopamine receptor-mediated and ADORA2A-mediated locomotor activity and dopamine receptor signaling. High expression of GPR52 protein in the striatum, nucleus accumbens, and lateral globus pallidus of wild type (WT) littermates was confirmed by immunohistochemical analysis. GPR52 KO and WT mice exhibited almost identical locomotor responses to the dopamine releaser methamphetamine and the N-methyl-d-aspartate antagonist MK-801. In contrast, the locomotor response to the ADORA2A antagonist istradefylline was significantly augmented in GPR52 KO mice compared to WT mice. Gene expression analysis revealed that striatal expression of DRD2, but not of dopamine D₁ receptor and ADORA2A, was significantly decreased in GPR52 KO mice. Moreover, a significant reduction in the mRNA expression of enkephalin, a marker of the activity of striatopallidal neurons, was observed in the striatum of GPR52 KO mice, suggesting that GPR52 deletion could enhance DRD2 signaling. Taken together, these results imply the physiological relevance of GPR52 in modulating the function of striatopallidal neurons, possibly by interaction of GPR52 with ADORA2A and DRD2.

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.

Brain structure, function, and neurochemistry in schizophrenia and bipolar disorder-a systematic review of the magnetic resonance neuroimaging literature

Since Emil Kraepelin's conceptualization of endogenous psychoses as dementia praecox and manic depression, the separation between primary psychotic disorders and primary affective disorders has been much debated. We conducted a systematic review of case-control studies contrasting magnetic resonance imaging studies in schizophrenia and bipolar disorder. A literature search in PubMed of studies published between January 2005 and December 2016 was conducted, and 50 structural, 29 functional, 7 magnetic resonance spectroscopy, and 8 combined imaging and genetic studies were deemed eligible for systematic review. Structural neuroimaging studies suggest white matter integrity deficits that are consistent across the illnesses, while gray matter reductions appear more widespread in schizophrenia compared to bipolar disorder. Spectroscopy studies in cortical gray matter report evidence of decreased neuronal integrity in both disorders. Functional neuroimaging studies typically report similar functional architecture of brain networks in healthy controls and patients across the psychosis spectrum, but find differential extent of alterations in task related activation and resting state connectivity between illnesses. The very limited imaging-genetic literature suggests a relationship between psychosis risk genes and brain structure, and possible gene by diagnosis interaction effects on functional imaging markers. While the existing literature suggests some shared and some distinct neural markers in schizophrenia and bipolar disorder, it will be imperative to conduct large, well designed, multi-modal neuroimaging studies in medication-naïve first episode patients that will be followed longitudinally over the course of their illness in an effort to advance our understanding of disease mechanisms.

A Network Neuroscience of Neurofeedback for Clinical Translation

In the emerging field of network neuroscience, the brain is represented as a network of discrete yet functionally and structurally interconnected areas. Mathematical and computational tools to characterize the organization of this network can provide insights into the principles guiding brain structure and function, and can pinpoint differences between healthy individuals and individuals suffering from psychiatric disease or neurological disorders. The field is now faced with the question of how to devise clinical interventions that target these network alterations. Potential solutions to this question include the combination of emerging theories of network control with cutting-edge interventions such as neurofeedback. Each of these techniques may now be mature enough to combine to obtain a theoretically-motivated framework informing viable neuropsychiatric therapies.

Effort-Based Reinforcement Processing and Functional Connectivity Underlying Amotivation in Medicated Patients with Depression and Schizophrenia

Amotivation is a common phenotype of major depressive disorder and schizophrenia, which are clinically distinct disorders. Effective treatment targets and strategies can be discovered by examining the dopaminergic reward network function underlying amotivation between these disorders. We conducted an fMRI study in healthy human participants and medicated patients with depression and schizophrenia using an effort-based reinforcement task. We examined regional activations related to reward type (positive and negative reinforcement), effort level, and their composite value, as well as resting-state functional connectivities within the meso-striatal-prefrontal pathway. We found that integrated reward and effort values of low effort-positive reinforcement and high effort-negative reinforcement were behaviorally anticipated and represented in the putamen and medial orbitofrontal cortex activities. Patients with schizophrenia and depression did not show anticipation-related and work-related reaction time reductions, respectively. Greater amotivation severity correlated with smaller work-related putamen activity changes according to reward type in schizophrenia and effort level in depression. Patients with schizophrenia showed feedback-related putamen hyperactivity of low effort compared with healthy controls and depressed patients. The strength of medial orbitofrontal-striatal functional connectivity predicted work-related reaction time reduction of high effort negative reinforcement in healthy controls and amotivation severity in both patients with schizophrenia and those with depression. Patients with depression showed deficient medial orbitofrontal-striatal functional connectivity compared with healthy controls and patients with schizophrenia. These results indicate that amotivation in depression and schizophrenia involves different pathophysiology in the prefrontal-striatal circuitry.SIGNIFICANCE STATEMENT Amotivation is present in both depression and schizophrenia. However, treatment involves the use of drugs that enhance serotonin activity in depression and inhibit serotonin and dopamine activity in schizophrenia. Understanding how motivation processed in the mesocorticolimbic and nigostriatal pathways is affected in depression and schizophrenia is important in discovering treatment targets and strategies for amotivation. To our knowledge, this is the first study to compare patients with depression and schizophrenia in a common functional construct. By using an effort-based reinforcement task and examining resting-state functional connectivity in the dopaminergic network, we propose that difference in striato-orbitofrontal dysfunction in effort-based reinforcement between depression and schizophrenia may be related to differences in the extent of functional dysconnectivity in the dopaminergic pathway.

Network-Level Dysconnectivity in Drug-Naïve First-Episode Psychosis: Dissociating Transdiagnostic and Diagnosis-Specific Alterations

The neuroimaging literature provides compelling evidence for functional dysconnectivity in people with psychosis. However, it is likely that at least some of the observed alterations represent secondary effects of illness chronicity and/or antipsychotic medication. In addition, the extent to which these alterations are specific to psychosis or represent a transdiagnostic feature of psychiatric illness remains unclear. The aim of this study was therefore to examine the diagnostic specificity of functional dysconnectivity in drug-naïve first-episode psychosis (FEP). We used resting-state functional magnetic resonance imaging and functional connectivity analysis to estimate network-level connectivity in 50 patients with FEP, 50 patients with major depressive disorder (MDD), 50 patients with post-traumatic stress disorder (PTSD), and 122 healthy controls (HCs). The FEP, MDD, and PTSD groups showed reductions in intranetwork connectivity of the default mode network relative to the HC group (p<0.05 corrected); therefore, intranetwork alterations were expressed across the three diagnostic groups. In addition, the FEP group showed heightened internetwork connectivity between the default mode network, particularly the anterior cingulate cortex, and the central executive network relative to the MDD, PTSD, and HC groups (p<0.05 corrected); therefore, internetwork alterations were specific to the FEP. These findings suggest that network-level alterations are present in individuals with a first episode of psychosis who have not been exposed to antipsychotic medication. In addition, they suggest a dissociation between aberrant internetwork connectivity as a distinctive feature of psychosis and aberrant intranetwork connectivity as a transdiagnostic feature of psychiatric illness.

Functional Magnetic Resonance Imaging Correlates of First-Episode Psychoses during Attentional and Memory Task Performance

BACKGROUND

The nature of the alteration of the response to cognitive tasks in first-episode psychosis (FEP) still awaits clarification. We used activation likelihood estimation, an increasingly used method in evaluating normal and pathological brain function, to identify activation changes in functional magnetic resonance imaging (fMRI) studies of FEP during attentional and memory tasks.

METHODS

We included 11 peer-reviewed fMRI studies assessing FEP patients versus healthy controls (HCs) during performance of attentional and memory tasks.

RESULTS

Our database comprised 290 patients with FEP, matched with 316 HCs. Between-group analyses showed that HCs, compared to FEP patients, exhibited hyperactivation of the right middle frontal gyrus (Brodmann area, BA, 9), right inferior parietal lobule (BA 40), and right insula (BA 13) during attentional task performances and hyperactivation of the left insula (BA 13) during memory task performances.

CONCLUSIONS

Right frontal, parietal, and insular dysfunction during attentional task performance and left insular dysfunction during memory task performance are significant neural functional FEP correlates.

Auditory verbal hallucinations: neuroimaging and treatment

Auditory verbal hallucinations (AVH) are a frequently occurring phenomenon in the general population and are considered a psychotic symptom when presented in the context of a psychiatric disorder. Neuroimaging literature has shown that AVH are subserved by a variety of alterations in brain structure and function, which primarily concentrate around brain regions associated with the processing of auditory verbal stimuli and with executive control functions. However, the direction of association between AVH and brain function remains equivocal in certain research areas and needs to be carefully reviewed and interpreted. When AVH have significant impact on daily functioning, several efficacious treatments can be attempted such as antipsychotic medication, brain stimulation and cognitive-behavioural therapy. Interestingly, the neural correlates of these treatments largely overlap with brain regions involved in AVH. This suggests that the efficacy of treatment corresponds to a normalization of AVH-related brain activity. In this selected review, we give a compact yet comprehensive overview of the structural and functional neuroimaging literature on AVH, with a special focus on the neural correlates of efficacious treatment.

Risperidone Effects on Brain Dynamic Connectivity-A Prospective Resting-State fMRI Study in Schizophrenia

Resting-state functional connectivity studies in schizophrenia evaluating average connectivity over the entire experiment have reported aberrant network integration, but findings are variable. Examining time-varying (dynamic) functional connectivity may help explain some inconsistencies. We assessed dynamic network connectivity using resting-state functional MRI in patients with schizophrenia, while unmedicated (n = 34), after 1 week (n = 29) and 6 weeks of treatment with risperidone (n = 24), as well as matched controls at baseline (n = 35) and after 6 weeks (n = 19). After identifying 41 independent components (ICs) comprising resting-state networks, sliding window analysis was performed on IC timecourses using an optimal window size validated with linear support vector machines. Windowed correlation matrices were then clustered into three discrete connectivity states (a relatively sparsely connected state, a relatively abundantly connected state, and an intermediately connected state). In unmedicated patients, static connectivity was increased between five pairs of ICs and decreased between two pairs of ICs when compared to controls, dynamic connectivity showed increased connectivity between the thalamus and somatomotor network in one of the three states. State statistics indicated that, in comparison to controls, unmedicated patients had shorter mean dwell times and fraction of time spent in the sparsely connected state, and longer dwell times and fraction of time spent in the intermediately connected state. Risperidone appeared to normalize mean dwell times after 6 weeks, but not fraction of time. Results suggest that static connectivity abnormalities in schizophrenia may partly be related to altered brain network temporal dynamics rather than consistent dysconnectivity within and between functional networks and demonstrate the importance of implementing complementary data analysis techniques.

Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task

Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n-back condition and group (p = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect (p = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task.

Converging effects of diverse treatment modalities on frontal cortex in schizophrenia: A review of longitudinal functional magnetic resonance imaging studies

OBJECTIVES

A variety of treatment options exist for schizophrenia, but the effects of these treatments on brain function are not clearly understood. To facilitate the development of more effective treatment strategies, it is important to identify how brain function in schizophrenia patients is affected by the diverse therapeutic approaches that are currently available. The aim of the present article is to systematically review the evidence for functional brain changes associated with different treatment modalities for schizophrenia.

METHODS

We searched PubMed for longitudinal functional MRI (fMRI) studies reporting on the effects of antipsychotic medications (APM), repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), cognitive remediation therapy (CRT) and cognitive behavioral therapy for psychosis (CBTp) on brain function in schizophrenia.

RESULTS

Thirty six studies fulfilled the inclusion criteria. Functional alterations were observed in diverse brain regions. Across intervention modalities, changes in fMRI parameters were reported most commonly in frontal brain regions including prefrontal cortex, anterior cingulate and inferior frontal cortex.

CONCLUSIONS

We conclude that current treatments for schizophrenia commonly induce functional brain alterations in frontal brain regions. However, interpretability is limited by inconsistency in task and region of interest selection, and failures to replicate. Further task independent fMRI studies examining treatment effects with whole brain analysis are needed to deepen our insights.

Predicting individual brain functional connectivity using a Bayesian hierarchical model

Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients. These studies provide the impetus to develop statistical methodology that would help provide predictive information on disease progression-related or treatment-related changes in neural connectivity. To this end, we propose a prediction method based on Bayesian hierarchical model that uses individual's baseline fMRI scans, coupled with relevant subject characteristics, to predict the individual's future functional connectivity. A key advantage of the proposed method is that it can improve the accuracy of individualized prediction of connectivity by combining information from both group-level connectivity patterns that are common to subjects with similar characteristics as well as individual-level connectivity features that are particular to the specific subject. Furthermore, our method also offers statistical inference tools such as predictive intervals that help quantify the uncertainty or variability of the predicted outcomes. The proposed prediction method could be a useful approach to predict the changes in individual patient's brain connectivity with the progression of a disease. It can also be used to predict a patient's post-treatment brain connectivity after a specified treatment regimen. Another utility of the proposed method is that it can be applied to test-retest imaging data to develop a more reliable estimator for individual functional connectivity. We show there exists a nice connection between our proposed estimator and a recently developed shrinkage estimator of connectivity measures in the neuroimaging community. We develop an expectation-maximization (EM) algorithm for estimation of the proposed Bayesian hierarchical model. Simulations studies are performed to evaluate the accuracy of our proposed prediction methods. We illustrate the application of the methods with two data examples: the longitudinal resting-state fMRI from ADNI2 study and the test-retest fMRI data from Kirby21 study. In both the simulation studies and the fMRI data applications, we demonstrate that the proposed methods provide more accurate prediction and more reliable estimation of individual functional connectivity as compared with alternative methods.

Altered Insular Function during Aberrant Salience Processing in Relation to the Severity of Psychotic Symptoms

There is strong evidence for abnormal salience processing in patients with psychotic experiences. In particular, there are indications that the degree of aberrant salience processing increases with the severity of positive symptoms. The aim of the present study was to elucidate this relationship by means of brain imaging. Functional magnetic resonance imaging was acquired to assess hemodynamic responses during the Salience Attribution Test, a paradigm for reaction time that measures aberrant salience to irrelevant stimulus features. We included 42 patients who were diagnosed as having a psychotic disorder and divided them into two groups according to the severity of their positive symptoms. Whole brain analysis was performed using Statistical Parametric Mapping. We found no significant behavioral differences with respect to task performance. Patients with more positive symptoms showed increased hemodynamic responses in the left insula corresponding to aberrant salience than in patients with less positive symptoms. In addition, left insula activation correlated negatively with cumulative antipsychotic medication. Aberrant salience processing in the insula may be increased in psychosis, depending on the severity of positive symptoms. This study indicates that clinically similar psychosis manifestations share the same functional characteristics. In addition, our results suggest that antipsychotic medication can modulate insular function.

Dysfunctional insular connectivity during reward prediction in patients with first-episode psychosis

BACKGROUND

Increasing evidence indicates that psychosis is associated with abnormal reward processing. Imaging studies in patients with first-episode psychosis (FEP) have revealed reduced activity in diverse brain regions, including the ventral striatum, insula and anterior cingulate cortex (ACC), during reward prediction. However, whether these reductions in local brain activity are due to altered connectivity has rarely been explored.

METHODS

We applied dynamic causal modelling and Bayesian model selection to fMRI data during the Salience Attribution Task to investigate whether patients with FEP showed abnormal modulation of connectivity between the ventral striatum, insula and ACC induced by rewarding cues and whether these changes were related to positive psychotic symptoms and atypical antipsychotic medication.

RESULTS

The model including reward-induced modulation of insula-ACC connectivity was the best fitting model in each group. Compared with healthy controls (n = 19), patients with FEP (n = 29) revealed reduced right insula-ACC connectivity. After subdividing patients according to current antipsychotic medication, we found that the reduced insula-ACC connectivity relative to healthy controls was observed only in untreated patients (n = 17), not in patients treated with antipsychotics (n = 12), and that it correlated negatively with unusual thought content in untreated patients with FEP.

LIMITATIONS

The modest sample size of untreated patients with FEP was a limitation of our study.

CONCLUSION

This study indicates that insula-ACC connectivity during reward prediction is reduced in untreated patients with FEP and related to the formation of positive psychotic symptoms. Our study further suggests that atypical antipsychotics may reverse connectivity between the insula and the ACC during reward prediction.

Ketamine-induced changes in connectivity of functional brain networks in awake female nonhuman primates: a translational functional imaging model

RATIONALE

There is a significant interest in the NMDA-receptor antagonist ketamine due to its efficacy in treating depressive disorders and its induction of psychotic-like symptoms that make it a useful tool for modeling psychosis. Pharmacological MRI in awake nonhuman primates provides a highly translational model for studying the brain network dynamics involved in producing these drug effects.

OBJECTIVE

The present study evaluated ketamine-induced changes in functional connectivity (FC) in awake rhesus monkeys. The effects of ketamine after pretreatment with the antipsychotic drug risperidone were also examined.

METHODS

Functional MRI scans were conducted in four awake adult female rhesus monkeys during sub-anesthetic i.v. infusions of ketamine (0.345 mg/kg bolus followed by 0.256 mg kg^-1 h^-1 constant infusion) with and without risperidone pretreatment (0.06 mg/kg). A 10-min window of stable BOLD signal was used to compare FC between baseline and drug conditions. FC was assessed in specific regions of interest using seed-based cross-correlation analysis.

RESULTS

Ketamine infusion induced extensive changes in FC. In particular, FC to the dorsolateral prefrontal cortex (dlPFC) was increased in several cortical and subcortical regions. Pretreatment with risperidone largely attenuated ketamine-induced changes in FC.

CONCLUSIONS

The results are highly consistent with similar human imaging studies showing ketamine-induced changes in FC, as well as a significant attenuation of these changes when ketamine infusion is preceded by pretreatment with risperidone. The extensive increases shown in FC to the dlPFC are consistent with the idea that disinhibition of the dlPFC may be a key driver of the antidepressant and psychotomimetic effects of ketamine.

Connectivity of the anterior insula differentiates participants with first-episode schizophrenia spectrum disorders from controls: a machine-learning study

BACKGROUND

Early diagnosis of schizophrenia could improve the outcomes and limit the negative effects of untreated illness. Although participants with schizophrenia show aberrant functional connectivity in brain networks, these between-group differences have a limited diagnostic utility. Novel methods of magnetic resonance imaging (MRI) analyses, such as machine learning (ML), may help bring neuroimaging from the bench to the bedside. Here, we used ML to differentiate participants with a first episode of schizophrenia-spectrum disorder (FES) from healthy controls based on resting-state functional connectivity (rsFC).

METHOD

We acquired resting-state functional MRI data from 63 patients with FES who were individually matched by age and sex to 63 healthy controls. We applied linear kernel support vector machines (SVM) to rsFC within the default mode network, the salience network and the central executive network.

RESULTS

The SVM applied to the rsFC within the salience network distinguished the FES from the control participants with an accuracy of 73.0% (p = 0.001), specificity of 71.4% and sensitivity of 74.6%. The classification accuracy was not significantly affected by medication dose, or by the presence of psychotic symptoms. The functional connectivity within the default mode or the central executive networks did not yield classification accuracies above chance level.

CONCLUSIONS

Seed-based functional connectivity maps can be utilized for diagnostic classification, even early in the course of schizophrenia. The classification was probably based on trait rather than state markers, as symptoms or medications were not significantly associated with classification accuracy. Our results support the role of the anterior insula/salience network in the pathophysiology of FES.

Dopamine-Related Disruption of Functional Topography of Striatal Connections in Unmedicated Patients With Schizophrenia

IMPORTANCE

Despite the well-established role of striatal dopamine in psychosis, current views generally agree that cortical dysfunction is likely necessary for the emergence of psychotic symptoms. The topographic organization of striatal-cortical connections is central to gating and integration of higher-order information, so a disruption of such topography via dysregulated dopamine could lead to cortical dysfunction in schizophrenia. However, this hypothesis remains to be tested using multivariate methods ascertaining the global pattern of striatal connectivity and without the confounding effects of antidopaminergic medication.

OBJECTIVES

To examine whether the pattern of brain connectivity across striatal subregions is abnormal in unmedicated patients with schizophrenia and whether this abnormality relates to psychotic symptoms and extrastriatal dopaminergic transmission.

DESIGN, SETTING, AND PARTICIPANTS

In this multimodal, case-control study, we obtained resting-state functional magnetic resonance imaging data from 18 unmedicated patients with schizophrenia and 24 matched healthy controls from the New York State Psychiatric Institute. A subset of these (12 and 17, respectively) underwent positron emission tomography with the dopamine D2 receptor radiotracer carbon 11-labeled FLB457 before and after amphetamine administration. Data were acquired between June 16, 2011, and February 25, 2014. Data analysis was performed from September 1, 2014, to January 11, 2016.

MAIN OUTCOMES AND MEASURES

Group differences in the striatal connectivity pattern (assessed via multivariable logistic regression) across striatal subregions, the association between the multivariate striatal connectivity pattern and extrastriatal baseline D2 receptor binding potential and its change after amphetamine administration, and the association between the multivariate connectivity pattern and the severity of positive symptoms evaluated with the Positive and Negative Syndrome Scale.

RESULTS

Of the patients with schizophrenia (mean [SEM] age, 35.6 [11.8] years), 9 (50%) were male and 9 (50%) were female. Of the controls (mean [SEM] age, 33.7 [8.8] years), 10 (42%) were male and 14 (58%) were female. Patients had an abnormal pattern of striatal connectivity, which included abnormal caudate connections with a distributed set of associative cortex regions (χ229 = 53.55, P = .004). In patients, more deviation from the multivariate pattern of striatal connectivity found in controls correlated specifically with more severe positive symptoms (ρ = -0.77, P = .002). Striatal connectivity also correlated with baseline binding potential across cortical and extrastriatal subcortical regions (t25 = 3.01, P = .01, Bonferroni corrected) but not with its change after amphetamine administration.

CONCLUSIONS AND RELEVANCE

Using a multimodal, circuit-level interrogation of striatal-cortical connections, it was demonstrated that the functional topography of these connections is globally disrupted in unmedicated patients with schizophrenia. These findings suggest that striatal-cortical dysconnectivity may underlie the effects of dopamine dysregulation on the pathophysiologic mechanism of psychotic symptoms.

Aberrant Hippocampal Connectivity in Unmedicated Patients With Schizophrenia and Effects of Antipsychotic Medication: A Longitudinal Resting State Functional MRI Study

To better characterize hippocampal pathophysiology in schizophrenia, we conducted a longitudinal study evaluating hippocampal functional connectivity during resting state, using seeds prescribed in its anterior and posterior regions. We enrolled 34 unmedicated patients with schizophrenia or schizoaffective disorder (SZ) and 34 matched healthy controls. SZ were scanned while off medication, then were treated with risperidone for 6 weeks and re-scanned (n = 22). Group differences in connectivity, as well as changes in connectivity over time, were assessed on the group's participant level functional connectivity maps. We found significant dysconnectivity with anterior and posterior hippocampal seeds in unmedicated SZ. Baseline connectivity between the hippocampus and anterior cingulate cortex, caudate nucleus, auditory cortex and calcarine sulcus in SZ predicted subsequent response to antipsychotic medications. These same regions demonstrated changes over the 6-week treatment trial that were correlated with symptomatic improvement. Our findings implicate several neural networks relevant to clinical improvement with antipsychotic medications.

Classifying Schizophrenia Using Multimodal Multivariate Pattern Recognition Analysis: Evaluating the Impact of Individual Clinical Profiles on the Neurodiagnostic Performance

Previous studies have shown that structural brain changes are among the best-studied candidate markers for schizophrenia (SZ) along with functional connectivity (FC) alterations of resting-state (RS) patterns. This study aimed to investigate effects of clinical and sociodemographic variables on the classification by applying multivariate pattern analysis (MVPA) to both gray matter (GM) volume and FC measures in patients with SZ and healthy controls (HC). RS and structural magnetic resonance imaging data (sMRI) from 74 HC and 71 SZ patients were obtained from a Mind Research Network COBRE dataset available via COINS (http://coins.mrn.org/dx). We used a MVPA framework using support-vector machines embedded in a repeated, nested cross-validation to generate a multi-modal diagnostic system and evaluate its generalizability. The dependence of neurodiagnostic performance on clinical and sociodemographic variables was evaluated. The RS classifier showed a slightly higher accuracy (70.5%) compared to the structural classifier (69.7%). The combination of sMRI and RS outperformed single MRI modalities classification by reaching 75% accuracy. The RS based moderator analysis revealed that the neurodiagnostic performance was driven by older SZ patients with an earlier illness onset and more pronounced negative symptoms. In contrast, there was no linear relationship between the clinical variables and neuroanatomically derived group membership measures. This study achieved higher accuracy distinguishing HC from SZ patients by fusing 2 imaging modalities. In addition the results of RS based moderator analysis showed that age of patients, as well as their age at the illness onset were the most important clinical features.

Neurophysiological evidence of impaired self-monitoring in schizotypal personality disorder and its reversal by dopaminergic antagonism

Background

Schizotypal personality disorder (SPD) is a schizophrenia-spectrum disorder characterized by odd or bizarre behavior, strange speech, magical thinking, unusual perceptual experiences, and social anhedonia. Schizophrenia proper has been associated with anomalies in dopaminergic neurotransmission and deficits in neurophysiological markers of self-monitoring, such as low amplitude in cognitive event-related brain potentials (ERPs) like the error-related negativity (ERN), and the error positivity (Pe). These components occur after performance errors, rely on adequate fronto-striatal function, and are sensitive to dopaminergic modulation. Here we postulated that analogous to observations in schizophrenia, SPD individuals would show deficits in self-monitoring, as measured by the ERN and the Pe. We also assessed the capacity of dopaminergic antagonists to reverse these postulated deficits.

Methods

We recorded the electroencephalogram (EEG) from 9 SPD individuals and 12 healthy controls in two separate experimental sessions while they performed the Eriksen Flanker Task, a classical task recruiting behavioral monitoring. Participants received a placebo or 1 mg risperidone according to a double-blind randomized design.

Results

After placebo, SPD individuals showed slower reaction times to hits, longer correction times following errors and reduced ERN and Pe amplitudes. While risperidone impaired performance and decreased ERN and Pe in the control group, it led to behavioral improvements and ERN amplitude increases in the SPD individuals.

Conclusions

These results indicate that SPD individuals show deficits in self-monitoring analogous to those in schizophrenia. These deficits can be evidenced by neurophysiological measures, suggest a dopaminergic imbalance, and can be reverted by dopaminergic antagonists.

Cognitive Behavioral Therapy Normalizes Functional Connectivity for Social Threat in Psychosis

Psychosis is often characterized by paranoia and poor social functioning. Neurally, there is evidence of functional dysconnectivity including abnormalities when processing facial affect. We sought to establish whether these abnormalities are resolved by cognitive behavioral therapy for psychosis (CBTp). The study involved 38 outpatients with one or more persistent positive psychotic symptoms, and 20 healthy participants. All participants completed an implicit facial affect processing task during functional magnetic resonance imaging (fMRI). Subsequently, patients either continued to receive standard care only (SCO,n= 16) or received CBTp on top of standard care (+CBTp,n= 22), with fMRI repeated 6-8 months later. To examine the mechanisms underlying CBTp-led changes in threat processing and appraisal, functional connectivity during the social threat (angry faces) condition was assessed separately from left amygdala and right dorsolateral prefrontal cortex (DLPFC) seeds. At baseline, patients, compared with healthy participants, showed greater amygdala connectivity with the insula and visual areas, but less connectivity with somatosensory areas. These differences normalized following CBTp and, compared with the SCO group, the +CBTp group showed greater increases in amygdala connectivity with DLPFC and inferior parietal lobule, with the latter correlating with improvement in positive symptoms. From the DLPFC seed, the +CBTp (compared with SCO) group showed significantly greater increase in DLPFC connectivity with other prefrontal regions including dorsal anterior cingulate and ventromedial prefrontal cortex. These findings indicate that CBTp strengthens connectivity between higher-order cognitive systems and those involved in threat and salience, potentially facilitating reappraisal.

Change in brain network topology as a function of treatment response in schizophrenia: a longitudinal resting-state fMRI study using graph theory

A number of neuroimaging studies have provided evidence in support of the hypothesis that faulty interactions between spatially disparate brain regions underlie the pathophysiology of schizophrenia, but it remains unclear to what degree antipsychotic medications affect these. We hypothesized that the balance between functional integration and segregation of brain networks is impaired in unmedicated patients with schizophrenia, but that it can be partially restored by antipsychotic medications. We included 32 unmedicated patients with schizophrenia (SZ) and 32 matched healthy controls (HC) in this study. We obtained resting-state scans while unmedicated, and again after 6 weeks of treatment with risperidone to assess functional integration and functional segregation of brain networks using graph theoretical measures. Compared with HC, unmedicated SZ showed reduced global efficiency and increased clustering coefficients. This pattern of aberrant functional network integration and segregation was modulated with antipsychotic medications, but only in those who responded to treatment. Our work lends support to the concept of schizophrenia as a dysconnectivity syndrome, and suggests that faulty brain network topology in schizophrenia is modulated by antipsychotic medication as a function of treatment response.

Abnormal frontostriatal connectivity in adolescent-onset schizophrenia and its relationship to cognitive functioning

BACKGROUND

Adolescent-onset schizophrenia (AOS) is associated with cognitive impairment and poor clinical outcome. Cognitive dysfunction is hypothesised, in part, to reflect functional dysconnectivity between the frontal cortex and the striatum, although structural abnormalities consistent with this hypothesis have not yet been demonstrated in adolescence.

OBJECTIVE

To characterise frontostriatal white matter (WM) tracts in relation to cognition in AOS.

DESIGN

A MRI volumetric and diffusion tensor imaging study.

PARTICIPANTS

Thirty-seven AOS subjects and 24 age and sex-matched healthy subjects.

OUTCOME MEASURES

Using probabilistic tractography, cortical regions with the highest connection probability for each striatal voxel were determined, and correlated with IQ and specific cognitive functions after co-varying for age and sex. Fractional anisotropy (FA) from individual tracts was a secondary measure.

RESULTS

Bayesian Structural Equation modeling of FA from 12 frontostriatal tracts showed processing speed to be an intermediary variable for cognition. AOS patients demonstrated generalised cognitive impairment with specific deficits in verbal learning and memory and in processing speed after correction for IQ. Dorsolateral prefrontal cortex connectivity with the striatum correlated positively with these measures and with IQ. DTI voxel-wise comparisons showed lower connectivity between striatum and the motor and lateral orbitofrontal cortices bilaterally, the left amygdalohippocampal complex, right anterior cingulate cortex, left medial orbitofrontal cortex and right dorsolateral prefrontal cortex.

CONCLUSIONS

Frontostriatal dysconnectivity in large WM tracts that can explain core cognitive deficits are evident during adolescence. Processing speed, which is affected by alterations in WM connectivity, appears an intermediary variable in the cognitive deficits seen in schizophrenia.

Dysfunctional Striatal Systems in Treatment-Resistant Schizophrenia

The prevalence of treatment-resistant schizophrenia points to a discrete illness subtype, but to date its pathophysiologic characteristics are undetermined. Information transfer from ventral to dorsal striatum depends on both striato-cortico-striatal and striato-nigro-striatal subcircuits, yet although the functional integrity of the former appears to track improvement of positive symptoms of schizophrenia, the latter have received little experimental attention in relation to the illness. Here, in a sample of individuals with schizophrenia stratified by treatment resistance and matched controls, functional pathways involving four foci along the striatal axis were assessed to test the hypothesis that treatment-resistant and non-refractory patients would exhibit contrasting patterns of resting striatal connectivity. Compared with non-refractory patients, treatment-resistant individuals exhibited reduced connectivity between ventral striatum and substantia nigra. Furthermore, disturbance to corticostriatal connectivity was more pervasive in treatment-resistant individuals. The occurrence of a more distributed pattern of abnormality may contribute to the failure of medication to treat symptoms in these individuals. This work strongly supports the notion of pathophysiologic divergence between individuals with schizophrenia classified by treatment-resistance criteria.

Medial Prefrontal and Anterior Insular Connectivity in Early Schizophrenia and Major Depressive Disorder: A Resting Functional MRI Evaluation of Large-Scale Brain Network Models

Anomalies in the medial prefrontal cortex, anterior insulae, and large-scale brain networks associated with them have been proposed to underlie the pathophysiology of schizophrenia and major depressive disorder (MDD). In this study, we examined the connectivity of the medial prefrontal cortices and anterior insulae in 24 healthy controls, 24 patients with schizophrenia, and 24 patients with MDD early in illness with seed-based resting state functional magnetic resonance imaging analysis using Statistical Probability Mapping. As hypothesized, reduced connectivity was found between the medial prefrontal cortex and the dorsal anterior cingulate cortex and other nodes associated with directed effort in patients with schizophrenia compared to controls while patients with MDD had reduced connectivity between the medial prefrontal cortex and ventral prefrontal emotional encoding regions compared to controls. Reduced connectivity was found between the anterior insulae and the medial prefrontal cortex in schizophrenia compared to controls, but contrary to some models emotion processing regions failed to demonstrate increased connectivity with the medial prefrontal cortex in MDD compared to controls. Although, not statistically significant after correction for multiple comparisons, patients with schizophrenia tended to demonstrate decreased connectivity between basal ganglia-thalamocortical regions and the medial prefrontal cortex compared to patients with MDD, which might be expected as these regions effect action. Results were interpreted to support anomalies in nodes associated with directed effort in schizophrenia and nodes associated with emotional encoding network in MDD compared to healthy controls.

Triiodothyronine accelerates and enhances the antipsychotic effect of risperidone in acute schizophrenia

In acute psychotic schizophrenia patients we investigated if the combination of triiodothyronine (T3) plus risperidone was more effective when compared to risperidone monotherapy. Thirty-two in-patients meeting the DSM-IV-TR diagnostic criteria for schizophrenia and without thyroid disease received risperidone (flexibly adjusted dose for tolerability) and were randomized to additionally receive either T3 (25 μg daily; risperidone plus T3 group) or placebo (risperidone plus placebo group). Treatment lasted until meeting the response to treatment criteria defined as score of ≤ 3 on the Clinical Global Impression Severity and Improvement scales. Acute psychotic episode symptom severity was evaluated using the Brief Psychiatric Rating Scale (BPRS) at treatment initiation and at the final study assessment. Fourteen patients were randomized to receive risperidone plus T3 and eighteen to receive risperidone plus placebo. The time until treatment response was shorter in the risperidone plus T3 group relative to the risperidone plus placebo group (25.5 ± 4.4 days vs 32.2 ± 8.2 days, respectively; p = 0.001). Moreover, there was a greater reduction of BPRS-total score (p = 0.01) in the risperidone plus T3 group relative to the risperidone plus placebo group. Treatment with T3 was associated with shorter time to treatment response (β = -0.440, p = 0.022) and with greater improvement in BPRS score (β = 0.240, p = 0.053), independent of patients' gender, age, baseline BPRS score and mean risperidone dose. The study confirms that addition of T3 to risperidone was associated with accelerated and enhanced treatment response in acutely psychotic schizophrenic patients.

Polygenic risk score prediction of antipsychotic dosage in schizophrenia

OBJECTIVE

Genetic variants have yet to be identified as reliable predictors of antipsychotic dosage. The purpose of this study is to quantify significant genetic risk variants prioritized from the Psychiatric GWAS Consortium (PGC2) study for schizophrenia as a polygenic score to test our hypothesis that it may represent symptom severity in patients and therefore predict antipsychotic dosage.

METHODS

Antipsychotic medication and dosage were collected in our sample of 83 patients with schizophrenia spectrum disorders of a homogeneous European background. Antipsychotic dosage was standardized according to the Product Monograph (PM%), chlorpromazine equivalents (CPZe), and Defined Daily Dose (DDD). We calculated polygenic risk scores (PRS) for the significant risk loci identified from the PGC2 GWAS to predict dosage using a linear regression model.

RESULTS

In our analysis, the PRS showed no significant association with PM%, CPZe, and DDD dosage. Considering symptom severity and overall functioning, our PRS was similarly not significantly associated with Global Assessment of Functioning (GAF) scores.

DISCUSSION

Our results do not provide evidence for a polygenic inheritance of schizophrenia that influences levels of antipsychotic dosage. To the best of our knowledge, this is one of the first studies of its kind to use the PRS from the PGC2 significant risk variants to predict a clinically relevant phenotype. The PRS offers a novel approach to analyzing the genetic liability for many clinically relevant phenotypes in schizophrenia.

Functional connectivity as a means to delineate differences between treatment-resistant and treatment-responsive schizophrenia

It has been estimated that one-third of schizophrenia patients are treatment resistant (TRS). Recent studies have shown that functional connectivity (FC) can be used for measuring connections between brain regions in diseased states. White, Wigton, Joyce, Collier, Fornito, and Shergill (Neuropsychopharmacology First published September 9, 2015; doi:10.1038/npp.2015.277) used FC to identify differences between schizophrenia patients responding to antipsychotic treatment and TRS patients. Their results support the idea that the groups differ not only in treatment response but also neurophysiologically through differences in FC.

Baseline Striatal Functional Connectivity as a Predictor of Response to Antipsychotic Drug Treatment

OBJECTIVE

Clinical response to antipsychotic drug treatment is highly variable, yet prognostic biomarkers are lacking. The authors recently demonstrated that successful antipsychotic drug treatment alters resting-state functional connectivity of the striatum. The goal of the present study was to test whether intrinsic striatal connectivity patterns provide prognostic information and can serve as a potential biomarker of treatment response to antipsychotic drugs.

METHOD

The authors used resting-state functional MRI (fMRI) to develop a prognostic index in a discovery cohort of 41 first-episode schizophrenia patients, then tested this index in an independent cohort of 40 newly hospitalized chronic patients with acute psychosis. In the discovery cohort, patients underwent resting-state fMRI scanning at the initiation of randomized controlled treatment with a second-generation antipsychotic. Whole-brain functional connectivity maps were generated for each subject from striatal seed regions. A stringent measure of clinical response was calculated that required sustained improvement over two consecutive study visits. Clinical response was entered into a survival analysis, and Cox regression was applied to the functional connectivity data. A striatal connectivity index was created, comprising functional connections of the striatum that predicted treatment response. This striatal connectivity index was tested on a generalizability cohort of patients with psychotic disorders who were hospitalized for an acute psychotic episode.

RESULTS

A total of 91 regions functionally connected with the striatum provided significant prognostic information. Connectivity in these regions was used to create a baseline striatal connectivity index that predicted response to antipsychotic treatment with high sensitivity and specificity in both the discovery and generalizability cohorts.

CONCLUSIONS

These results provide evidence that individual differences in striatal functional connectivity predict response to antipsychotic drug treatment in acutely psychotic patients. With further development, this has the potential to serve as a prognostic biomarker with clinical utility and to reduce the overall burden associated with psychotic illnesses.

Connectomic markers of disease expression, genetic risk and resilience in bipolar disorder

Bipolar disorder (BD) is characterized by emotional dysregulation and cognitive deficits associated with abnormal connectivity between subcortical-primarily emotional processing regions-and prefrontal regulatory areas. Given the significant contribution of genetic factors to BD, studies in unaffected first-degree relatives can identify neural mechanisms of genetic risk but also resilience, thus paving the way for preventive interventions. Dynamic causal modeling (DCM) and random-effects Bayesian model selection were used to define and assess connectomic phenotypes linked to facial affect processing and working memory in a demographically matched sample of first-degree relatives carefully selected for resilience (n=25), euthymic patients with BD (n=41) and unrelated healthy controls (n=46). During facial affect processing, patients and relatives showed similarly increased frontolimbic connectivity; resilient relatives, however, evidenced additional adaptive hyperconnectivity within the ventral visual stream. During working memory processing, patients displayed widespread hypoconnectivity within the corresponding network. In contrast, working memory network connectivity in resilient relatives was comparable to that of controls. Our results indicate that frontolimbic dysfunction during affect processing could represent a marker of genetic risk to BD, and diffuse hypoconnectivity within the working memory network a marker of disease expression. The association of hyperconnectivity within the affect-processing network with resilience to BD suggests adaptive plasticity that allows for compensatory changes and encourages further investigation of this phenotype in genetic and early intervention studies.

Abnormalities in large scale functional networks in unmedicated patients with schizophrenia and effects of risperidone

Objective

To describe abnormalities in large scale functional networks in unmedicated patients with schizophrenia and to examine effects of risperidone on networks.

Material and methods

34 unmedicated patients with schizophrenia and 34 matched healthy controls were enrolled in this longitudinal study. We collected resting state functional MRI data with a 3T scanner at baseline and six weeks after they were started on risperidone. In addition, a group of 19 healthy controls were scanned twice six weeks apart. Four large scale networks, the dorsal attention network, executive control network, salience network, and default mode network were identified with seed based functional connectivity analyses. Group differences in connectivity, as well as changes in connectivity over time, were assessed on the group's participant level functional connectivity maps.

Results

In unmedicated patients with schizophrenia we found resting state connectivity to be increased in the dorsal attention network, executive control network, and salience network relative to control participants, but not the default mode network. Dysconnectivity was attenuated after six weeks of treatment only in the dorsal attention network. Baseline connectivity in this network was also related to clinical response at six weeks of treatment with risperidone.

Conclusions

Our results demonstrate abnormalities in large scale functional networks in patients with schizophrenia that are modulated by risperidone only to a certain extent, underscoring the dire need for development of novel antipsychotic medications that have the ability to alleviate symptoms through attenuation of dysconnectivity.

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We found widespread functional dysconnectivity in unmedicated patients with schizophrenia.

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Large scale functional networks appear differentially affected in the disorder.

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Attenuation of dysconnectivity with risperidone is seen only to a limited extent.

Schizophrenia

Schizophrenia is a chronic psychiatric disorder with a heterogeneous genetic and neurobiological background that influences early brain development, and is expressed as a combination of psychotic symptoms - such as hallucinations, delusions and disorganization - and motivational and cognitive dysfunctions. The mean lifetime prevalence of the disorder is just below 1%, but large regional differences in prevalence rates are evident owing to disparities in urbanicity and patterns of immigration. Although gross brain pathology is not a characteristic of schizophrenia, the disorder involves subtle pathological changes in specific neural cell populations and in cell-cell communication. Schizophrenia, as a cognitive and behavioural disorder, is ultimately about how the brain processes information. Indeed, neuroimaging studies have shown that information processing is functionally abnormal in patients with first-episode and chronic schizophrenia. Although pharmacological treatments for schizophrenia can relieve psychotic symptoms, such drugs generally do not lead to substantial improvements in social, cognitive and occupational functioning. Psychosocial interventions such as cognitive-behavioural therapy, cognitive remediation and supported education and employment have added treatment value, but are inconsistently applied. Given that schizophrenia starts many years before a diagnosis is typically made, the identification of individuals at risk and those in the early phases of the disorder, and the exploration of preventive approaches are crucial.

Dissecting the Heterogeneity of Treatment Response in First-Episode Schizophrenia

The Mental Health Centers for Intervention Development and Applied Research (CIDAR) program prioritized research to provide an evidence base for biomarker development. At the Zucker Hillside Hospital (ZHH), our CIDAR grant supported research on a comprehensive investigation of treatment response and outcome in first episode schizophrenia. Results provide evidence that baseline neuroimaging, neurocognitive, and genetic measures are significantly associated with clinical response to treatment, and that our currently available interventions can effectively treat aspects of psychotic illness, as well as potentially reduce comorbidity associated with illness. Future research may include combining modalities to more robustly predict response and identify treatment targets, as well as to further develop more effective intervention strategies for these devastating and disabling disorders.

Disrupted sensorimotor and social-cognitive networks underlie symptoms in childhood-onset schizophrenia

Schizophrenia is increasingly recognized as a neurodevelopmental disorder with altered connectivity among brain networks. In the current study we examined large-scale network interactions in childhood-onset schizophrenia, a severe form of the disease with salient genetic and neurobiological abnormalities. Using a data-driven analysis of resting-state functional magnetic resonance imaging fluctuations, we characterized data from 19 patients with schizophrenia and 26 typically developing controls, group matched for age, sex, handedness, and magnitude of head motion during scanning. This approach identified 26 regions with decreased functional correlations in schizophrenia compared to controls. These regions were found to organize into two function-related networks, the first with regions associated with social and higher-level cognitive processing, and the second with regions involved in somatosensory and motor processing. Analyses of across- and within-network regional interactions revealed pronounced across-network decreases in functional connectivity in the schizophrenia group, as well as a set of across-network relationships with overall negative coupling indicating competitive or opponent network dynamics. Critically, across-network decreases in functional connectivity in schizophrenia predicted the severity of positive symptoms in the disorder, such as hallucinations and delusions. By contrast, decreases in functional connectivity within the social-cognitive network of regions predicted the severity of negative symptoms, such as impoverished speech and flattened affect. These results point toward the role that abnormal integration of sensorimotor and social-cognitive processing may play in the pathophysiology and symptomatology of schizophrenia.

Molecular evidence for decreased synaptic efficacy in the postmortem olfactory bulb of individuals with schizophrenia

Multiple lines of evidence suggest altered synaptic plasticity/connectivity as a pathophysiologic mechanism for various symptom domains of schizophrenia. Olfactory dysfunction, an endophenotype of schizophrenia, reflects altered activity of the olfactory circuitry, which conveys signals from olfactory receptor neurons to the olfactory cortex via synaptic connections in the glomeruli of the olfactory bulb. The olfactory system begins with intranasal olfactory receptor neuron axons synapsing with mitral and tufted cells in the glomeruli of the olfactory bulb, which then convey signals directly to the olfactory cortex. We hypothesized that olfactory dysfunction in schizophrenia is associated with dysregulation of synaptic efficacy in the glomeruli of the olfactory bulb. To test this, we employed semi-quantitative immunohistochemistry to examine the olfactory bulbs of 13 postmortem samples from schizophrenia and their matched control pairs for glomerular expression of 5 pre- and postsynaptic proteins that are involved in the integrity and function of synapses. In the glomeruli of schizophrenia cases compared to their matched controls, we found significant decreases in three presynaptic proteins which play crucial roles in vesicular glutamate transport - synapsin IIa (-18.05%, p=0.019), synaptophysin (-24.08% p=0.0016) and SNAP-25 (-23.9%, p=0.046). Two postsynaptic proteins important for spine formation and glutamatergic signaling were also decreased-spinophilin (-17.40%, p=0.042) and PSD-95 (-34.06%, p=0.015). These findings provide molecular evidence for decreased efficacy of synapses within the olfactory bulb, which may represent a synaptic mechanism underlying olfactory dysfunction in schizophrenia.

Atomoxetine Treatment Strengthens an Anti-Correlated Relationship between Functional Brain Networks in Medication-Naïve Adults with Attention-Deficit Hyperactivity Disorder: A Randomized Double-Blind Placebo-Controlled Clinical Trial

BACKGROUND

Although atomoxetine demonstrates efficacy in individuals with attention-deficit hyperactivity disorder, its treatment effects on brain resting-state functional connectivity remain unknown. Therefore, we aimed to investigate major brain functional networks in medication-naïve adults with attention-deficit hyperactivity disorder and the efficacy of atomoxetine treatment on resting-state functional connectivity.

METHODS

After collecting baseline resting-state functional MRI scans from 24 adults with attention-deficit hyperactivity disorder (aged 18-52 years) and 24 healthy controls (matched in demographic characteristics), the participants with attention-deficit hyperactivity disorder were randomly assigned to atomoxetine (n=12) and placebo (n=12) arms in an 8-week, double-blind, placebo-controlled trial. The primary outcome was functional connectivity assessed by a resting-state functional MRI. Seed-based functional connectivity was calculated and compared for the affective, attention, default, and cognitive control networks.

RESULTS

At baseline, we found atypical cross talk between the default, cognitive control, and dorsal attention networks and hypoconnectivity within the dorsal attention and default networks in adults with attention-deficit hyperactivity disorder. Our first-ever placebo-controlled clinical trial incorporating resting-state functional MRI showed that treatment with atomoxetine strengthened an anticorrelated relationship between the default and task-positive networks and modulated all major brain networks. The strengthened anticorrelations were associated with improving clinical symptoms in the atomoxetine-treated adults.

CONCLUSIONS

Our results support the idea that atypical default mode network task-positive network interaction plays an important role in the pathophysiology of adult attention-deficit hyperactivity disorder. Strengthening this atypical relationship following atomoxetine treatment suggests an important pathway to treat attention-deficit hyperactivity disorder.

Aberrant functioning of the putamen links delusions, antipsychotic drug dose, and compromised connectivity in first episode psychosis--Preliminary fMRI findings

The dopamine theory proposes the relationship of delusions to aberrant signaling in striatal circuitries that can be normalized with dopamine D2 receptor-blocking drugs. Localization of such circuitries, as well as their upstream and downstream signaling, remains poorly known. We collected functional magnetic resonance images from first-episode psychosis patients and controls during an audiovisual movie. Final analyses included 20 patients and 20 controls; another sample of 10 patients and 10 controls was used to calculate a comparison signal-time course. We identified putamen circuitry in which the signal aberrance (poor correlation with the comparison signal time course) was predicted by the dopamine theory, being greater in patients than controls; correlating positively with delusion scores; and correlating negatively with antipsychotic-equivalent dosage. In Granger causality analysis, patients showed a compromised contribution of the cortical salience network to the putamen and compromised contribution of the putamen to the default mode network. Results were corrected for multiple comparisons at the cluster level with primary voxel-wise threshold p < 0.005 for the salience network contribution, but liberal primary threshold p < 0.05 was used in other group comparisons. If replicated in larger studies, these findings may help unify and extend current hypotheses on dopaminergic dysfunction, salience processing and pathogenesis of delusions.

Connectome and schizophrenia

PURPOSE OF REVIEW

The neural connections, interconnections and organized networks of the central nervous system (CNS), which represent the human connectome, are critical for intact brain function. Consequently, disturbances at any level or juncture of these networks may alter behaviour and/or lead to brain dysfunction. In this review, we focus on highlighting recent work using advanced imaging methods to address alterations in the structural and functional connectome in patients with schizophrenia.

RECENT FINDINGS

Using structural, diffusion, resting-state and task-related functional imaging and advanced computational analysis methods such as graph theory, more than 200 publications have addressed different aspects of structural and/or functional connectivity in schizophrenia over the last year. These studies have focused on determining how brain networks differ from those in controls, interact with symptom profiles within and across diagnoses, interface with disease-related cognitive impairments and confer genetic risk for the disorder.

SUMMARY

Much existing evidence supports the view that schizophrenia is a disorder of altered brain connectivity. Recent and continued characterization of the structural and functional connectome in schizophrenia patients have advanced our understanding of the neurobiology underlying clinical symptoms and cognitive impairments in a particular patient, their overlaps with other neuropsychiatric disorders sharing common features as well as the contributions of genetic risk factors. Although the clinical utility of the schizophrenia connectome remains to be realized, recent findings provide further promise that research in this area may lead to improved diagnosis, treatments and clinical outcomes.

Electrophysiological Neuroimaging using sLORETA Comparing 22 Age Matched Male and Female Schizophrenia Patients

INTRODUCTION

The purpose of this electrophysiological neuroimaging study was to provide a deeper mechanistic understanding of both olanzapine and risperidone pharmacodynamics relative to gender. In doing so, we age-matched 22 men and women and evaluated their resting-state EEG recordings and later used standard low resolution brain Electrotomography to visualize the differences in brain activity amongst the two patient groups.

METHODS

In this investigation, electroencephalogram (EEG) data were analyzed from male and female schizophrenia patients treated with either olanzapine or risperidone, both atypical antipsychotics, during their in-patient stay at the Department of Psychiatry. Twenty-two males and females were age-matched and EEG recordings were analyzed from 19 Ag/AgCl electrodes. Thirty-seconds of resting EEG were spectrally transformed in standardized low resolution electromagnetic tomography (sLORETA). 3D statistical non-paramentric maps for the sLORETA Global Field Power within each band were finally computed.

RESULTS

The results indicated that, relative to males patients, females schizophrenia patients had increased neuronal synchronization in delta frequency, slow-wave, EEG band located in the dorsolateral prefrontal cortex, within the middle frontal gyrus (t= -2.881, p < 0.03580). These findings suggest that females experience greater dopamine (D2) receptor and serotonin (5-HT2) receptor neuronal blockade relative to age-matched males. Further, our finding provided insight to the pharmacodynamics of second-generation antipsychotics olanzapine and risperidone.

CONCLUSION

When compared to male patients, female patients, suffering from schizophrenia, have D2 and 5-HT2 receptors that are blocked more readily than age-matched male schizophrenia patients. Clinically, this may translate into a quicker time to treatment-response in females as compared to male patients.