Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations

Schizophrenia is a psychiatric disorder that has eluded characterization in terms of local abnormalities of brain activity, and is hypothesized to affect the collective, “emergent” working of the brain. Indeed, several recent publications have demonstrated that functional networks in the schizophrenic brain display disrupted topological properties. However, is it possible to explain such abnormalities just by alteration of local activation patterns? This work suggests a negative answer to this question, demonstrating that significant disruption of the topological and spatial structure of functional MRI networks in schizophrenia (a) cannot be explained by a disruption to area-based task-dependent responses, i.e. indeed relates to the emergent properties, (b) is global in nature, affecting most dramatically long-distance correlations, and (c) can be leveraged to achieve high classification accuracy (93%) when discriminating between schizophrenic vs control subjects based just on a single fMRI experiment using a simple auditory task. While the prior work on schizophrenia networks has been primarily focused on discovering statistically significant differences in network properties, this work extends the prior art by exploring the generalization (prediction) ability of network models for schizophrenia, which is not necessarily captured by such significance tests.     

Intra- and Inter-Frequency Brain Network Structure in Health and Schizophrenia

Empirical studies over the past two decades have provided support for the hypothesis that schizophrenia is characterized by altered connectivity patterns in functional brain networks. These alterations have been proposed as genetically mediated diagnostic biomarkers and are thought to underlie altered cognitive functions such as working memory. However, the nature of this dysconnectivity remains far from understood. In this study, we perform an extensive analysis of functional connectivity patterns extracted from MEG data in 14 subjects with schizophrenia and 14 healthy controls during a 2-back working memory task. We investigate uni-, bi- and multivariate properties of sensor time series by computing wavelet entropy of and correlation between time series, and by constructing binary networks of functional connectivity both within and between classical frequency bands (, , , and ). Networks are based on the mutual information between wavelet time series, and estimated for each trial window separately, enabling us to consider both network topology and network dynamics. We observed significant decreases in time series entropy and significant increases in functional connectivity in the schizophrenia group in comparison to the healthy controls and identified an inverse relationship between these measures across both subjects and sensors that varied over frequency bands and was more pronounced in controls than in patients. The topological organization of connectivity was altered in schizophrenia specifically in high frequency and band networks as well as in the - cross-frequency networks. Network topology varied over trials to a greater extent in patients than in controls, suggesting disease-associated alterations in dynamic network properties of brain function. Our results identify signatures of aberrant neurophysiological behavior in schizophrenia across uni-, bi- and multivariate scales and lay the groundwork for further clinical studies that might lead to the discovery of new intermediate phenotypes.     

Increased Intra-Individual Variability of Cognitive Processing in Subjects at Risk Mental State and Schizophrenia Patients

Intra-individual variability (IIV) has received recent attention as an indicator of the stability of cognitive functioning that may outperform mean performance in reflecting putative neurobiological abnormalities. Increased IIV is regarded as a core deficit in schizophrenia patients; however, whether this deficit is present in the prodromal phase before the onset of schizophrenia has not been well established. In the present study, we investigated IIV using the stop-signal paradigm in at-risk mental state (ARMS) individuals and in schizophrenia patients. The study included 27 ARMS subjects, 37 schizophrenia patients, and 38 normal controls. The stop-signal task was administered to assess IIV and response inhibition. IIV was estimated by calculating the standard deviation across sub-blocks for the three groups. We observed increased IIV in ARMS subjects and schizophrenia patients compared with normal controls in both the “stop” and the “go” processes even though the mean response inhibition performances were not impaired in the ARMS group. Schizophrenia patients showed impaired response inhibition that was associated with the severity of negative symptoms. Our findings suggest that the analysis of IIV may identify cognitive and clinical features of ARMS that are not detectable by conventional mean performance analysis. The unstable response patterns associated with ARMS may originate from abnormal processing in neural systems caused by alterations in the integrity of functional brain networks and dopamine neuromodulation.     

Neurexin-1 and frontal lobe white matter: an overlapping intermediate phenotype for schizophrenia and autism spectrum disorders

BACKGROUND: Structural variation in the neurexin-1 (NRXN1) gene increases risk for both autism spectrum disorders (ASD) and schizophrenia. However, the manner in which NRXN1 gene variation may be related to brain morphology to confer risk for ASD or schizophrenia is unknown. METHOD/PRINCIPAL FINDINGS: 53 healthy individuals between 18-59 years of age were genotyped at 11 single nucleotide polymorphisms of the NRXN1 gene. All subjects received structural MRI scans, which were processed to determine cortical gray and white matter lobar volumes, and volumes of striatal and thalamic structures. Each subject's sensorimotor function was also assessed. The general linear model was used to calculate the influence of genetic variation on neural and cognitive phenotypes. Finally, in silico analysis was conducted to assess potential functional relevance of any polymorphisms associated with brain measures. A polymorphism located in the 3' untranslated region of NRXN1 significantly influenced white matter volumes in whole brain and frontal lobes after correcting for total brain volume, age and multiple comparisons. Follow-up in silico analysis revealed that this SNP is a putative microRNA binding site that may be of functional significance in regulating NRXN1 expression. This variant also influenced sensorimotor performance, a neurocognitive function impaired in both ASD and schizophrenia. CONCLUSIONS: Our findings demonstrate that the NRXN1 gene, a vulnerability gene for SCZ and ASD, influences brain structure and cognitive function susceptible in both disorders. In conjunction with our in silico results, our findings provide evidence for a neural and cognitive susceptibility mechanism by which the NRXN1 gene confers risk for both schizophrenia and ASD.     

Brain Correlates of Self-Evaluation Deficits in Schizophrenia: A Combined Functional and Structural MRI Study

Self-evaluation plays an important role in adaptive functioning and is a process that is typically impaired in patients with schizophrenia. Underlying neural mechanisms for this dysfunction may be associated with manifested psychosis. However, the brain substrates underlying this deficit are not well known. The present study used brain blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and gray matter voxel-based morphometry to explore the functional and structural brain correlates of self-evaluation deficits in schizophrenia. Eighteen patients with schizophrenia and 17 healthy controls were recruited and asked to judge whether a set of personality-trait adjectives were appropriate for describing themselves, a familiar other, or whether the adjectives were of positive or negative valence. Patients had slower response times for negative trait attributions than controls did; responses to positive trait attributions were faster than those for negative traits among the patient group, while no differences were observed in the control group. Control subjects showed greater activation within the dorsal medial prefrontal cortex (dMPFC) and the anterior cingulate cortex (ACC) than the patient group during the self-evaluation > semantic positivity-evaluation contrast. Patients showed greater activation mainly within the posterior cingulate gyrus (PCC) as compared to controls for the other-evaluation > semantic positivity-evaluation contrast. Furthermore, gray matter volume was reduced in the MPFC, temporal lobe, cuneus, and the dorsal lateral prefrontal cortex (DLPFC) among the patient group when compared to controls. The present study adds to previous findings regarding self- and other-referential processing in schizophrenia, providing support for neurobiological models of self-reflection impairment.     

Evaluation of the factors influencing brain language laterality in presurgical planning

Brain lesions cause functional deficits, and one treatment for this condition is lesion resection. In most cases, presurgical planning (PSP) and the information from laterality indices are necessary for maximum preservation of the critical functions after surgery. Language laterality index (LI) is reliably estimated using functional magnetic resonance imaging (fMRI); however, this measure is under the influence of some external factors. In this study, we investigated the influence of a number of factors on language LI, using data from 120 patients (mean age = 35.65 (±13.4) years) who underwent fMRI for PSP. Using two proposed language tasks from our previous works, brain left hemisphere was showed to be dominant for the language function, although a higher LI was obtained using the “Word Generation” task, compared to the “Reverse Word Reading”. In addition, decline of LIs with age, and lower LI when the lesion invaded brain language area were observed. Meanwhile, gender, lesion side (affected hemisphere), LI calculation strategy, and fMRI analysis Z-values did not statistically show any influences on the LIs. Although fMRI is widely used to estimate language LI, it is shown here that in order to present a reliable language LI and to correctly select the dominant hemisphere of the brain, the influence of external factors should be carefully considered.     

Functional biomarkers in the diagnostics of mental disorders: Cognitive event-related potentials

The article deals with recent research in the field of fundamental knowledge about the mechanisms of information processing in the human brain for the diagnosis of mental disorders performed in the laboratory of neurobiology for action programming of the Bechtereva Institute of the Human Brain of the Russian Academy of Sciences. These studies were connected with the analysis of functional components for cognitive event-related potentials (ERPs) obtained under various behavioral conditions. The main goal of this fundamental approach is the decomposition of multi-channel ERPs into functionally different components. These components are generated in various cortical areas, have different temporal dynamics, and reflect a variety of mental operations. The main methodology we used is the independent component analysis, applied to a large set of ERPs (from hundreds of people) obtained by varying functional conditions in the psychological test. In particular, components related to psychological processes, such as the comparison of sensory signals with a trace in working memory, inhibition of current activity, and monitoring of conflict, were identified in the GO/NOGO test. In the European project, a normative database was constructed for the components described above, and this allowed us to compare the data obtained from large groups of patients (including patients with attention deficit disorder, schizophrenia, obsessive disorders, depression, autism, dyslexia, brain trauma, and dementia) with the healthy subjects. This article presents data from patients with a diagnosis of attention deficit disorder and schizophrenia.     

Gene expression in the rodent brain is associated with its regional connectivity

The putative link between gene expression of brain regions and their neural connectivity patterns is a fundamental question in neuroscience. Here this question is addressed in the first large scale study of a prototypical mammalian rodent brain, using a combination of rat brain regional connectivity data with gene expression of the mouse brain. Remarkably, even though this study uses data from two different rodent species (due to the data limitations), we still find that the connectivity of the majority of brain regions is highly predictable from their gene expression levels-the outgoing (incoming) connectivity is successfully predicted for 73% (56%) of brain regions, with an overall fairly marked accuracy level of 0.79 (0.83). Many genes are found to play a part in predicting both the incoming and outgoing connectivity (241 out of the 500 top selected genes, p-value<1e-5). Reassuringly, the genes previously known from the literature to be involved in axon guidance do carry significant information about regional brain connectivity. Surveying the genes known to be associated with the pathogenesis of several brain disorders, we find that those associated with schizophrenia, autism and attention deficit disorder are the most highly enriched in the connectivity-related genes identified here. Finally, we find that the profile of functional annotation groups that are associated with regional connectivity in the rodent is significantly correlated with the annotation profile of genes previously found to determine neural connectivity in C. elegans (Pearson correlation of 0.24, p<1e-6 for the outgoing connections and 0.27, p<1e-5 for the incoming). Overall, the association between connectivity and gene expression in a specific extant rodent species' brain is likely to be even stronger than found here, given the limitations of current data.     

Early cognitive experience prevents adult deficits in a neurodevelopmental schizophrenia model

Brain abnormalities acquired early in life may cause schizophrenia, characterized by adulthood onset of psychosis, affective flattening, and cognitive impairments. Cognitive symptoms, like impaired cognitive control, are now recognized to be important treatment targets but cognition-promoting treatments are ineffective. We hypothesized that cognitive training during the adolescent period of neuroplastic development can tune compromised neural circuits to develop in the service of adult cognition and attenuate schizophrenia-related cognitive impairments that manifest in adulthood. We report, using neonatal ventral hippocampus lesion rats (NVHL), an established neurodevelopmental model of schizophrenia, that adolescent cognitive training prevented the adult cognitive control impairment in NVHL rats. The early intervention also normalized brain function, enhancing cognition-associated synchrony of neural oscillations between the hippocampi, a measure of brain function that indexed cognitive ability. Adolescence appears to be a critical window during which prophylactic cognitive therapy may benefit people at risk of schizophrenia.     

Schizophrenia and the neurodevelopmental continuum:evidence from genomics

The idea that disturbances occurring early in brain development contribute to the pathogenesis of schizophrenia, often referred to as the neurodevelopmental hypothesis, has become widely accepted. Despite this, the disorder is viewed as being distinct nosologically, and by implication pathophysiologically and clinically, from syndromes such as autism spectrum disorders, attention‐deficit/hyperactivity disorder (ADHD) and intellectual disability, which typically present in childhood and are grouped together as “neurodevelopmental disorders”. An alternative view is that neurodevelopmental disorders, including schizophrenia, rather than being etiologically discrete entities, are better conceptualized as lying on an etiological and neurodevelopmental continuum, with the major clinical syndromes reflecting the severity, timing and predominant pattern of abnormal brain development and resulting functional abnormalities. It has also been suggested that, within the neurodevelopmental continuum, severe mental illnesses occupy a gradient of decreasing neurodevelopmental impairment as follows: intellectual disability, autism spectrum disorders, ADHD, schizophrenia and bipolar disorder. Recent genomic studies have identified large numbers of specific risk DNA changes and offer a direct and robust test of the predictions of the neurodevelopmental continuum model and gradient hypothesis. These findings are reviewed in detail. They not only support the view that schizophrenia is a disorder whose origins lie in disturbances of brain development, but also that it shares genetic risk and pathogenic mechanisms with the early onset neurodevelopmental disorders (intellectual disability, autism spectrum disorders and ADHD). They also support the idea that these disorders lie on a gradient of severity, implying that they differ to some extent quantitatively as well as qualitatively. These findings have important implications for nosology, clinical practice and research.     

Higher Dimensional Meta-State Analysis Reveals Reduced Resting fMRI Connectivity Dynamism in Schizophrenia Patients

Resting-state functional brain imaging studies of network connectivity have long assumed that functional connections are stationary on the timescale of a typical scan. Interest in moving beyond this simplifying assumption has emerged only recently. The great hope is that training the right lens on time-varying properties of whole-brain network connectivity will shed additional light on previously concealed brain activation patterns characteristic of serious neurological or psychiatric disorders. We present evidence that multiple explicitly dynamical properties of time-varying whole-brain network connectivity are strongly associated with schizophrenia, a complex mental illness whose symptomatic presentation can vary enormously across subjects. As with so much brain-imaging research, a central challenge for dynamic network connectivity lies in determining transformations of the data that both reduce its dimensionality and expose features that are strongly predictive of important population characteristics. Our paper introduces an elegant, simple method of reducing and organizing data around which a large constellation of mutually informative and intuitive dynamical analyses can be performed. This framework combines a discrete multidimensional data-driven representation of connectivity space with four core dynamism measures computed from large-scale properties of each subject’s trajectory, ie., properties not identifiable with any specific moment in time and therefore reasonable to employ in settings lacking inter-subject time-alignment, such as resting-state functional imaging studies. Our analysis exposes pronounced differences between schizophrenia patients (N_sz = 151) and healthy controls (N_hc = 163). Time-varying whole-brain network connectivity patterns are found to be markedly less dynamically active in schizophrenia patients, an effect that is even more pronounced in patients with high levels of hallucinatory behavior. To the best of our knowledge this is the first demonstration that high-level dynamic properties of whole-brain connectivity, generic enough to be commensurable under many decompositions of time-varying connectivity data, exhibit robust and systematic differences between schizophrenia patients and healthy controls.     

GAD1 mRNA expression and DNA methylation in prefrontal cortex of subjects with schizophrenia

Dysfunction of prefrontal cortex in schizophrenia includes changes in GABAergic mRNAs, including decreased expression of GAD1, encoding the 67 kDa glutamate decarboxylase (GAD67) GABA synthesis enzyme. The underlying molecular mechanisms remain unclear. Alterations in DNA methylation as an epigenetic regulator of gene expression are thought to play a role but this hypothesis is difficult to test because no techniques are available to extract DNA from GAD1 expressing neurons efficiently from human postmortem brain. Here, we present an alternative approach that is based on immunoprecipitation of mononucleosomes with anti-methyl-histone antibodies differentiating between sites of potential gene expression as opposed to repressive or silenced chromatin. Methylation patterns of CpG dinucleotides at the GAD1 proximal promoter and intron 2 were determined for each of the two chromatin fractions separately, using a case-control design for 14 schizophrenia subjects affected by a decrease in prefrontal GAD1 mRNA levels. In controls, the methylation frequencies at CpG dinucleotides, while overall higher in repressive as compared to open chromatin, did not exceed 5% at the proximal GAD1 promoter and 30% within intron 2. Subjects with schizophrenia showed a significant, on average 8-fold deficit in repressive chromatin-associated DNA methylation at the promoter. These results suggest that chromatin remodeling mechanisms are involved in dysregulated GABAergic gene expression in schizophrenia.     

The inheritance of neuropsychological dysfunction in twins discordant for schizophrenia

While genetic influences in schizophrenia are substantial, the disorder's molecular genetic basis remains elusive. Progress has been hindered by lack of means to detect nonpenetrant carriers of the predisposing genes and by uncertainties concerning the extent of locus heterogeneity. One approach to solving this complexity is to examine the inheritance of pathophysiological processes mediating between genotype and disease phenotype. Here we evaluate whether deficits in neurocognitive functioning covary with degree of genetic relationship with a proband in the unaffected MZ and DZ co-twins of patients with schizophrenia. Twin pairs discordant for schizophrenia were recruited from a total population cohort and were compared with a demographically balanced sample of control twin pairs, on a comprehensive neuropsychological test battery. The following four neuropsychological functions contributed uniquely to the discrimination of degree of genetic loading for schizophrenia and, when combined, were more highly correlated within MZ pairs than within DZ pairs, in both discordant and control twins: spatial working memory (i.e., remembering a sequence of spatial locations over a brief delay), divided attention (i.e., simultaneous performance of a counting and visual-search task), intrusions during recall of a word list (i.e., "remembering" nonlist items), and choice reaction time to visual targets. Together with evidence from human and animal studies of mediation of these functions by partially distinct brain systems, our findings suggest that there are multiple independently inherited dimensions of neural deficit in schizophrenia and encourage a search for genes contributing to quantitative variation in discrete aspects of disease liability. On tests of verbal and visual episodic memory, but not on the liability-related measures, patients were more impaired than their own MZ co-twins, suggesting a preferential impact of nongenetic influences on long-term memory systems.     

An expanded role for functional neuroimaging in schizophrenia

Functional magnetic resonance imaging is a surprisingly versatile tool in the quest for disentangling the complexities of mental illnesses such as schizophrenia. Yet, the identification of pathognomonic physiological features of the illness or even a consensus regarding the interpretation of reported findings remain unfulfilled goals, in spite of the increasing sophistication of this technology. Nonetheless, by providing quantification of brain function during various cognitive challenges, functional MRI has been used to leap ahead of these quandaries to identify relationships between genetic variation and brain function. By examining recent findings and efforts to link these findings to genes, this article will review these exciting developments in schizophrenia research.     

Electrical brain responses in language-impaired children reveal grammar-specific deficits

Background

Scientific and public fascination with human language have included intensive scrutiny of language disorders as a new window onto the biological foundations of language and its evolutionary origins. Specific language impairment (SLI), which affects over 7% of children, is one such disorder. SLI has received robust scientific attention, in part because of its recent linkage to a specific gene and loci on chromosomes and in part because of the prevailing question regarding the scope of its language impairment: Does the disorder impact the general ability to segment and process language or a specific ability to compute grammar? Here we provide novel electrophysiological data showing a domain-specific deficit within the grammar of language that has been hitherto undetectable through behavioural data alone.

Methods and Findings

We presented participants with Grammatical(G)-SLI, age-matched controls, and younger child and adult controls, with questions containing syntactic violations and sentences containing semantic violations. Electrophysiological brain responses revealed a selective impairment to only neural circuitry that is specific to grammatical processing in G-SLI. Furthermore, the participants with G-SLI appeared to be partially compensating for their syntactic deficit by using neural circuitry associated with semantic processing and all non-grammar-specific and low-level auditory neural responses were normal.

Conclusions

The findings indicate that grammatical neural circuitry underlying language is a developmentally unique system in the functional architecture of the brain, and this complex higher cognitive system can be selectively impaired. The findings advance fundamental understanding about how cognitive systems develop and all human language is represented and processed in the brain.     

Unique properties of mesoprefrontal neurons within a dual mesocorticolimbic dopamine system

The mesocorticolimbic dopamine system is essential for cognitive and emotive brain functions and is thus an important target in major brain diseases like schizophrenia, drug addiction, and attention deficit hyperactivity disorder. However, the cellular basis for the diversity in behavioral functions and associated dopamine-release pattern within the mesocorticolimbic system has remained unclear. Here, we report the identification of a type of dopaminergic neuron within the mesocorticolimbic dopamine system with unconventional fast-firing properties and small DAT/TH mRNA expression ratios that selectively projects to prefrontal cortex and nucleus accumbens core and medial shell as well as to basolateral amygdala. In contrast, well-described conventional slow-firing dopamine midbrain neurons only project to the lateral shell of the nucleus accumbens and the dorsolateral striatum. Among this dual dopamine midbrain system defined in this study by converging anatomical, electrophysiological, and molecular properties, mesoprefrontal dopaminergic neurons are unique, as only they do not possess functional somatodendritic Girk2-coupled dopamine D2 autoreceptors.     

A haplotype implicated in schizophrenia susceptibility is associated with reduced COMT expression in human brain

The gene encoding catechol-O-methyltransferase (COMT) is a strong candidate for schizophrenia susceptibility, owing to the role of COMT in dopamine metabolism, and the location of the gene within the deleted region in velocardiofacial syndrome, a disorder associated with high rates of schizophrenia. Recently, a highly significant association was reported between schizophrenia and a COMT haplotype in a large case-control sample (Shifman et al. 2002). In addition to a functional valine-->methionine (Val/Met) polymorphism, this haplotype included two noncoding single-nucleotide polymorphisms (SNPs) at either end of the COMT gene. Given the role of COMT in dopamine catabolism and that deletion of 22q11 (containing COMT) is associated with schizophrenia, we postulated that the susceptibility COMT haplotype is associated with low COMT expression. To test this hypothesis, we have applied quantitative measures of allele-specific expression using mRNA from human brain. We demonstrate that COMT is subject to allelic differences in expression in human brain and that the COMT haplotype implicated in schizophrenia (Shifman et al. 2002) is associated with lower expression of COMT mRNA. We also show that the 3' flanking region SNP that gave greatest evidence for association with schizophrenia in that study is transcribed in human brain and exhibits significant differences in allelic expression, with lower relative expression of the associated allele. Our results indicate that COMT variants other than the Val/Met change are of functional importance in human brain and that the haplotype implicated in schizophrenia susceptibility is likely to exert its effect, directly or indirectly, by down-regulating COMT expression.     

Regional Brain Atrophy and Functional Disconnection in Broca’s Area in Individuals at Ultra-High Risk for Psychosis and Schizophrenia

Background

Abnormalities in cognitive abilities such as verbal fluency and in cognitive-related brain regions, particularly Broca’s area, have been reported in patients with schizophrenia. Additionally, previous studies have demonstrated that structural and functional abnormalities in Broca’s area were associated with clinical symptoms and cognitive deficits in patients with schizophrenia, suggesting that deficits in this area may reflect the core pathology of schizophrenia. Thus, it is important to understand how the structural volume and functional connectivity in this area changes at rest according to the course of the illness.

Methods/Principal Findings

We used magnetic resonance imaging (MRI) to measure the structural volume of Broca’s area as a region of interest in 16 schizophrenia, 16 ultra-high risk (UHR), and 23 healthy matched controls. We also assessed verbal fluency and analyzed differences across groups in the functional connectivity patterns using resting-state functional MRI. The UHR group showed significantly reduced structural volume in Broca’s area and significantly reduced functional connectivity between Broca’s area and the lateral and medial frontal cortex as well as decreased cognitive performance. Altered functional connectivity in patients was correlated with their positive symptoms.

Conclusions/Significance

Our results suggest the existence of functional disconnections in Broca’s area, even during resting-states, among those with schizophrenia as well as those at UHR for this disorder. These alterations may contribute to their clinical symptoms, suggesting that this is one of the key regions involved in the pathophysiology of schizophrenia.