Emeritus Professor Patricia Michie

Schizophrenia (SCZ) is a chronic mental illness and among the most debilitating conditions encountered in medical practice. A recent landmark SCZ study of the protein-coding regions of the genome identified a causal role for ten genes and a concentration of rare variant signals in evolutionarily constrained genes1. This recent study¿and most other large-scale human genetics studies¿was mainly composed of individuals of European (EUR) ancestry, and the generalizability of the findings in non-EUR populations remains unclear. To address this gap, we designed a custom sequencing panel of 161 genes selected based on the current knowledge of SCZ genetics and sequenced a new cohort of 11,580 SCZ cases and 10,555 controls of diverse ancestries. Replicating earlier work, we found that cases carried a significantly higher burden of rare protein-truncating variants (PTVs) among evolutionarily constrained genes (odds ratio = 1.48; P = 5.4 × 10-6). In meta-analyses with existing datasets totaling up to 35,828 cases and 107,877 controls, this excess burden was largely consistent across five ancestral populations. Two genes (SRRM2 and AKAP11) were newly implicated as SCZ risk genes, and one gene (PCLO) was identified as shared by individuals with SCZ and those with autism. Overall, our results lend robust support to the rare allelic spectrum of the genetic architecture of SCZ being conserved across diverse human populations.

Schizophrenia has a heritability of 60¿80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

Mismatch negativity (MMN) is an electrophysiological signature that occurs in response to unexpected stimuli. It is often referred to as a measure of memory-based change detection, because the elicitation of a prediction error response relies on the formation of a prediction, which in turn, is dependent upon intact memory of previous auditory stimulation. As such, the MMN is altered in conditions in which memory is affected, such as Alzheimer's disease, schizophrenia and healthy aging. The most prominent pharmacological finding for MMN strengthens the link between MMN and synaptic plasticity, as glutamate N-methyl-D-aspartate receptor (NMDA-R) antagonists reduce the MMN response. However, recent data has begun to demonstrate that the link between NMDA-R function and MMN is not as clear as once thought, with low dose and low affinity NMDA-R antagonists observed to facilitate MMN.

During task-switching paradigms, both event-related potentials and time-frequency analyses show switch and mixing effects at frontal and parietal sites. Switch and mixing effects are associated with increased power in broad frontoparietal networks, typically stronger in the theta band (~4¿8¿Hz). However, it is not yet known whether mixing and switch costs rely upon common or distinct networks. In this study, we examine proactive and reactive control networks linked to task switching and mixing effects, and whether strength of connectivity in these networks is associated with behavioural outcomes. Participants (n¿= 197) completed a cued-trials task-switching paradigm with concurrent electroencephalography, after substantial task practice to establish strong cue-stimulus¿response representations. We used inter-site phase clustering, a measure of functional connectivity across electrode sites, to establish cross-site connectivity from a frontal and a parietal seed. Distinct theta networks were activated during proactive and reactive control periods. During the preparation interval, mixing effects were associated with connectivity from the frontal seed to parietal sites, and switch effects with connectivity from the parietal seed to occipital sites. Lateralised occipital connectivity was common to both switch and mixing effects. After target onset, frontal and parietal seeds showed a similar pattern of connectivity across trial types. These findings are consistent with distinct and common proactive control networks and common reactive networks in highly practised task-switching performers.

Rodent models play a significant role in understanding disease mechanisms and the screening of new treatments. With regard to psychiatric disorders such as schizophrenia, however, it is difficult to replicate the human symptoms in rodents because these symptoms are often either ¿uniquely human¿ or are only conveyed via self-report. There is a growing interest in rodent mismatch responses (MMRs) as a translatable ¿biomarker¿ for disorders such as schizophrenia. In this review, we will summarize the attributes of human MMN, and discuss the scope of exploring the attributes of human MMN in rodents. Here, we examine how reliably MMRs that are measured in rats mimic human attributes, and present original data examining whether manipulations of stimulus conditions known to modulate human MMN, do the same for rat MMRs. Using surgically-implanted epidural electroencephalographic electrodes and wireless telemetry in freely-moving rats, we observed human-like modulations of MMRs, namely that larger MMRs were elicited to unexpected (deviant) stimuli that a) had a larger change in pitch compared to the expected (standard) stimulus, b) were less frequently presented (lower probability), and c) had no jitter (stable stimulus onset asynchrony) compared to high jitter. Overall, these findings contribute to the mounting evidence for rat MMRs as a good analogue of human MMN, bolstering the development of a novel approach in future to validate the preclinical models based on a translatable biomarker, MMN.

Few studies have examined the post-discharge benefits associated with recover-oriented programs delivered in inpatient and sub-acute mental health settings. The aim of this study was to evaluate the medium-term outcomes of a 6-week sub-acute inpatient intervention program for 27 service users with a diagnosis of serious mental illness (mean age = 33.22¿years, 70.4% with a psychosis diagnosis). Recovery data were collected on admission, at discharge, and at 3- and 6-months post-discharge using self-report, collaborative and clinical measures. The three clinician-rated measures (assessing therapeutic engagement, functioning, and life skills) revealed linear improvements from admission to 6-month follow-up (with mean z-change ranging from 0.72 to 1.35), as did the self-reported social connection measure (Mental Health Recovery Star, MHRS; mean z-change: 1.05). There were also curvilinear improvements in self-determination and self-reported MHRS symptom management and functioning scores; however, only modest changes were detected in hope (Herth Hope Index) and MHRS self-belief scores. Change scores based on self-reported and clinician-rated measures tended to be uncorrelated. An exploration of client-level outcomes revealed three recovery trajectory subgroups: transient (21.7%), gradual (34.8%), or sustained (43.5%) improvement; with members of the latter group tending to have longer illness durations. The study¿s findings are encouraging, to the extent that they demonstrate recovery-focused sub-acute inpatient programs can promote clinical recovery and aspects of personal recovery. However, they also suggest that recovery perspectives differ between clients and clinicians, and that far more work is required to understand the psychological factors that generate and sustain the hope that recovery is possible.

Many factors and their interaction are linked to the aetiology of schizophrenia, leading to the development of animal models of multiple risk factors and adverse exposures. Differentiating between separate and combined effects for each factor could better elucidate schizophrenia pathology, and drive development of preventative strategies for high-load risk factors. An epidemiologically valid risk factor commonly associated with schizophrenia is adolescent cannabis use. The aim of this review is to evaluate how early-life adversity from various origins, in combination with adolescent cannabinoid exposure interact, and whether these interactions confer main, synergistic or protective effects in animal models of schizophrenia-like behavioural, cognitive and morphological alterations. Patterns emerge regarding which models show consistent synergistic or protective effects, particularly those models incorporating early-life exposure to maternal deprivation and maternal immune activation, and sex-specific effects are observed. It is evident that more research needs to be conducted to better understand the risks and alterations of interacting factors, with particular interest in sex differences, to better understand the translatability of these preclinical models to humans.

Previous neuroimaging studies have reported differences in regional brain activation between males and females during stop signal task performance, suggesting the presence of sex-linked differences in brain network organization of inhibitory ability. Despite a growing literature on sex differences during stop signal task performance, a consensus still has not been reached due to variations in task design and analysis methods. Due to these disparate findings we used up to date stop signal task methods to compare behavioral performance and associated brain activation between males and females using an event-related functional magnetic resonance imaging design. We observed that males were faster in inhibiting their responses, but females exhibited marked increased in stopping network activation, in addition to increased activation of the anterior insula and left amygdala. These findings suggest that males and females process stop signals differently.

Objectives: Large-scale genetic analysis of common variation in schizophrenia has been a powerful approach to understanding this complex but highly heritable psychotic disorder. To further investigate loci, genes and pathways associated more specifically in the well-characterized Australian Schizophrenia Research Bank cohort, we applied genome-wide single-nucleotide polymorphism analysis in these three annotation categories. Methods: We performed a case¿control genome-wide association study in 429 schizophrenia samples and 255 controls. Post-genome-wide association study analyses were then integrated with genomic annotations to explore the enrichment of variation at the gene and pathway level. We also examine candidate single-nucleotide polymorphisms with potential function within expression quantitative trait loci and investigate overall enrichment of variation within tissue-specific functional regulatory domains of the genome. Results: The strongest finding (p = 2.01 × 10-6, odds ratio = 1.82, 95% confidence interval = [1.42, 2.33]) in genome-wide association study was with rs10252923 at 7q21.13, downstream of FZD1 (frizzled class receptor 1). While this did not stand alone after correction, the involvement of FZD1 was supported by gene-based analysis, which exceeded the threshold for genome-wide significance (p = 2.78 × 10-6). Conclusion: The identification of FZD1, as an independent association signal at the gene level, supports the hypothesis that the Wnt signalling pathway is altered in the pathogenesis of schizophrenia and may be an important target for therapeutic development.

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

Neuroethics is central to the Australian Brain Initiative's aim to sustain a thriving and responsible neurotechnology industry. Diverse and inclusive community and stakeholder engagement and a trans-disciplinary approach to neuroethics will be key to the success of the Australian Brain Initiative.

Genome-wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re-analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity-by-descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow-up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes.

The ability to control behaviour is thought to rely at least partly on adequately suppressing impulsive responses to external stimuli. However, the evidence for a relationship between response inhibition ability and impulse control is weak and inconsistent. This study investigates the relationship between response inhibition and both self-report and behavioural measures of impulsivity as well as engagement in risky behaviours in a large community sample (N = 174) of healthy adolescents and young adults (15¿35 years). Using a stop-signal paradigm with a number parity go task, we implemented a novel hierarchical Bayesian model of response inhibition that estimates stop-signal reaction time (SSRT) as a distribution and also accounts for failures to react to the stop-signal (i.e., ¿trigger failure¿), and failure to react to the choice stimulus (i.e., ¿go failure¿ or omission errors). In line with previous studies, the model reduced estimates of SSRT by approximately 100 ms compared with traditional non-parametric SSRT estimation techniques. We found significant relationships between behavioural and self-report measures of impulsivity and traditionally estimated SSRT, that did not hold for the model-based SSRT estimates. Instead, behavioural impulsivity measures were correlated with rate of trigger failure. The relationship between trigger failure and impulsivity suggests that the former may index a higher order inhibition process, whereas SSRT may index a more automatic inhibition process. We suggest that the existence of distinct response inhibition processes that may be associated with different levels of cognitive control.

One of the most robust electrophysiological features of schizophrenia is reduced mismatch negativity, a component of the event related potential (ERP) induced by rare and unexpected stimuli in an otherwise regular pattern. Emerging evidence suggests that mismatch negativity (MMN) is not the only ERP index of deviance detection in the mammalian brain and that sensitivity to deviant sounds in a regular background can be observed at earlier latencies in both the human and rodent brain. Pharmacological studies in humans and rodents have previously found that MMN reductions similar to those seen in schizophrenia can be elicited by N-methyl-D-aspartate (NMDA) receptor antagonism, an observation in agreement with the hypothesised role of NMDA receptor hypofunction in schizophrenia pathogenesis. However, it is not known how NMDA receptor antagonism affects early deviance detection responses. Here, we show that NMDA antagonism impacts both early and late deviance detection responses. By recording EEG in awake, freely-moving rats in a drug-free condition and after varying doses of NMDA receptor antagonist MK-801, we found the hypothesised reduction of deviance detection for a late, negative potential (N55). However, the amplitude of an early component, P13, as well as deviance detection evident in the same component, were increased by NMDA receptor antagonism. These findings indicate that late deviance detection in rats is similar to human MMN, but the surprising effect of MK-801 in increasing ERP amplitudes as well as deviance detection at earlier latencies suggests that future studies in humans should examine ERPs over early latencies in schizophrenia and after NMDA antagonism.

Background: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. Methods: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11¿78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10¿87 years; 53% male) assessed with standardized methods at 39 centers worldwide. Results: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. Conclusions: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.

Animal models of maternal immune activation study the effects of infection, an environmental risk factor for schizophrenia, on brain development. Microglia activation and cytokine upregulation may have key roles in schizophrenia neuropathology. We hypothesised that maternal immune activation induces changes in microglia and cytokines in the brains of the adult offspring. Maternal immune activation was induced by injecting polyriboinosinic:polyribocytidylic acid into pregnant rats on gestational day (GD) 10 or GD19, with brain tissue collected from the offspring at adulthood. We observed no change in Iba1, Gfap, IL1-ß and TNF-a mRNA levels in the cingulate cortex (CC) in adult offspring exposed to maternal immune activation. Prenatal exposure to immune activation had a significant main effect on microglial IBA1-positive immunoreactive material (IBA1+IRM) in the corpus callosum; post-hoc analyses identified a significant increase in GD19 offspring, but not GD10. No change in was observed in the CC. In contrast, maternal immune activation had a significant main effect on GFAP+IRM in the CC at GD19 (not GD10); post-hoc analyses only identified a strong trend towards increased GFAP+IRM in the GD19 offspring, with no white matter changes. This suggests late gestation maternal immune activation causes subtle alterations to microglia and astrocytes in the adult offspring.

Increasingly, national governments across the globe are prioritizing investments in neuroscience. Currently, seven active or in-development national-level brain research initiatives exist, spanning four continents. Engaging with the underlying values and ethical concerns that drive brain research across cultural and continental divides is critical to future research. Culture influences what kinds of science are supported and where science can be conducted through ethical frameworks and evaluations of risk. Neuroscientists and philosophers alike have found themselves together encountering perennial questions; these questions are engaged by the field of neuroethics, related to the nature of understanding the self and identity, the existence and meaning of free will, defining the role of reason in human behavior, and more. With this Perspective article, we aim to prioritize and advance to the foreground a list of neuroethics questions for neuroscientists operating in the context of these international brain initiatives. Neuroscience is a national priority across the globe necessitating engagement with the underlying cultural and ethical values that drive brain research. We offer a list of neuroethics questions for neuroscientists to advance and accelerate an ethically tenable globalized neuroscience.

Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on ~150,000 individuals give a higher accuracy than LDSC estimates based on ~400,000 individuals (from combined meta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.

Maternal exposure to infectious agents during gestation has been identified as a significant risk factor for schizophrenia. Using a mouse model, past work has demonstrated that the gestational timing of the immune-activating event can impact the behavioural phenotype and expression of dopaminergic and glutamatergic neurotransmission markers in the offspring. In order to determine the inter-species generality of this effect to rats, another commonly used model species, the current study investigated the impact of a viral mimetic Poly (I:C) at either an early (gestational day 10) or late (gestational day 19) time-point on schizophrenia-related behaviour and neurotransmitter receptor expression in rat offspring. Exposure to Poly (I:C) in late, but not early, gestation resulted in transient impairments in working memory. In addition, male rats exposed to maternal immune activation (MIA) in either early or late gestation exhibited sensorimotor gating deficits. Conversely, neither early nor late MIA exposure altered locomotor responses to MK-801 or amphetamine. In addition, increased dopamine 1 receptor mRNA levels were found in the nucleus accumbens of male rats exposed to early gestational MIA. The findings from this study diverge somewhat from previous findings in mice with MIA exposure, which were often found to exhibit a more comprehensive spectrum of schizophrenia-like phenotypes in both males and females, indicating potential differences in the neurodevelopmental vulnerability to MIA exposure in the rat with regards to schizophrenia related changes.

Low frequency oscillations in the theta range (4¿8 Hz) are increasingly recognized as having a crucial role in flexible cognition. Such evidence is typically derived from studies in the context of reactive (stimulus-driven) control processes. However, little research has explored the role of theta oscillations in preparatory control processes. In the current study, we explored the extent of theta oscillations during proactive cognitive control and determined if these oscillations were associated with behavior. Results supported a general role of theta oscillations during proactive cognitive control, with increased power and phase coherence during the preparatory cue interval. Further, theta oscillations across frontoparietal electrodes were also modulated by proactive control demands, with increased theta phase synchrony and power for cues signaling the need for goal updating. Finally, we present novel evidence of negative associations between behavioral variability and both power and phase synchrony across many of these frontoparietal electrodes that were associated with the need for goal updating. In particular, greater consistency in frontoparietal theta oscillations, indicated by increased theta phase and power during mixed-task blocks, resulted in more consistent task-switching performance. Together, these findings provide new insight into the temporal dynamics and functional relevance of theta oscillations during proactive cognitive control.

We used Bayesian cognitive modelling to identify the underlying causes of apparent inhibitory deficits in the stop-signal paradigm. The analysis was applied to stop-signal data reported by Badcock et al. (Psychological Medicine 32: 87-297, 2002) and Hughes et al. (Biological Psychology 89: 220-231, 2012), where schizophrenia patients and control participants made rapid choice responses, but on some trials were signalled to stop their ongoing response. Previous research has assumed an inhibitory deficit in schizophrenia, because estimates of the mean time taken to react to the stop signal are longer in patients than controls. We showed that these longer estimates are partly due to failing to react to the stop signal (¿trigger failures¿) and partly due to a slower initiation of inhibition, implicating a failure of attention rather than a deficit in the inhibitory process itself. Correlations between the probability of trigger failures and event-related potentials reported by Hughes et al. are interpreted as supporting the attentional account of inhibitory deficits. Our results, and those of Matzke et al. (2016), who report that controls also display a substantial although lower trigger-failure rate, indicate that attentional factors need to be taken into account when interpreting results from the stop-signal paradigm.

White matter abnormalities associated with schizophrenia have been widely reported, although the consistency of findings across studies is moderate. In this study, neuroimaging was used to investigate white matter pathology and its impact on whole-brain white matter connectivity in one of the largest samples of patients with schizophrenia. Fractional anisotropy (FA) and mean diffusivity (MD) were compared between patients with schizophrenia or schizoaffective disorder (n = 326) and age-matched healthy controls (n = 197). Between-group differences in FA and MD were assessed using voxel-based analysis and permutation testing. Automated whole-brain white matter fiber tracking and the network-based statistic were used to characterize the impact of white matter pathology on the connectome and its rich club. Significant reductions in FA associated with schizophrenia were widespread, encompassing more than 40% (234ml) of cerebral white matter by volume and involving all cerebral lobes. Significant increases in MD were also widespread and distributed similarly. The corpus callosum, cingulum, and thalamic radiations exhibited the most extensive pathology according to effect size. More than 50% of cortico-cortical and cortico-subcortical white matter fiber bundles comprising the connectome were disrupted in schizophrenia. Connections between hub regions comprising the rich club were disproportionately affected. Pathology did not differ between patients with schizophrenia and schizoaffective disorder and was not mediated by medication. In conclusion, although connectivity between cerebral hubs is most extensively disturbed in schizophrenia, white matter pathology is widespread, affecting all cerebral lobes and the cerebellum, leading to disruptions in the majority of the brain's fiber bundles.

Schizophrenia is a complex psychiatric disorder, typically diagnosed through symptomatic evidence collected through patient interview. We aim to develop an objective biologically-based computational tool which aids diagnosis and relies on accessible imaging technologies such as electroencephalography (EEG). To achieve this, we used machine learning techniques and a combination of paradigms designed to elicit prediction errors or Mismatch Negativity (MMN) responses. MMN, an EEG component elicited by unpredictable changes in sequences of auditory stimuli, has previously been shown to be reduced in people with schizophrenia and this is arguably one of the most reproducible neurophysiological markers of schizophrenia. EEG data were acquired from 21 patients with schizophrenia and 22 healthy controls whilst they listened to three auditory oddball paradigms comprising sequences of tones which deviated in 10% of trials from regularly occurring standard tones. Deviant tones shared the same properties as standard tones, except for one physical aspect: 1) duration - the deviant stimulus was twice the duration of the standard; 2) monaural gap - deviants had a silent interval omitted from the standard, or 3) inter-aural timing difference, which caused the deviant location to be perceived as 90° away from the standards. We used multivariate pattern analysis, a machine learning technique implemented in the Pattern Recognition for Neuroimaging Toolbox (PRoNTo) to classify images generated through statistical parametric mapping (SPM) of spatiotemporal EEG data, i.e. event-related potentials measured on the two-dimensional surface of the scalp over time. Using support vector machine (SVM) and Gaussian processes classifiers (GPC), we were able classify individual patients and controls with balanced accuracies of up to 80.48% (p-values = 0.0326, FDR corrected) and an ROC analysis yielding an AUC of 0.87. Crucially, a GP regression revealed that MMN predicted global assessment of functioning (GAF) scores (correlation = 0.73, R2 = 0.53, p = 0.0006).

Task-switching performance relies on a broadly distributed frontoparietal network and declines in older adults. In this study, they investigated whether this age-related decline in task switching performance was mediated by variability in global or regional white matter microstructural health. Seventy cognitively intact adults (43¿87 years) completed a cued-trials task switching paradigm. Microstructural white matter measures were derived using diffusion tensor imaging (DTI) analyses on the diffusion-weighted imaging (DWI) sequence. Task switching performance decreased with increasing age and radial diffusivity (RaD), a measure of white matter microstructure that is sensitive to myelin structure. RaD mediated the relationship between age and task switching performance. However, the relationship between RaD and task switching performance remained significant when controlling for age and was stronger in the presence of cardiovascular risk factors. Variability in error and RT mixing cost were associated with RaD in global white matter and in frontoparietal white matter tracts, respectively. These findings suggest that age-related increase in mixing cost may result from both global and tract-specific disruption of cerebral white matter linked to the increased incidence of cardiovascular risks in older adults. Hum Brain Mapp 38:1588¿1603, 2017. © 2016 Wiley Periodicals, Inc.

Interstitial neurons are located among white matter tracts of the human and rodent brain. Post-mortem studies have identified increased interstitial white matter neuron (IWMN) density in the fibre tracts below the cortex in people with schizophrenia. The current study assesses IWMN pathology in a model of maternal immune activation (MIA); a risk factor for schizophrenia. Experimental MIA was produced by an injection of polyinosinic:polycytidylic acid (PolyI:C) into pregnant rats on gestational day (GD) 10 or GD19. A separate control group received saline injections. The density of neuronal nuclear antigen (NeuN⁺) and somatostatin (SST⁺) IWMNs was determined in the white matter of the corpus callosum in two rostrocaudally adjacent areas in the 12week old offspring of GD10 (n=10) or GD19 polyI:C dams (n=18) compared to controls (n=20). NeuN⁺ IWMN density trended to be higher in offspring from dams exposed to polyI:C at GD19, but not GD10. A subpopulation of these NeuN⁺ IWMNs was shown to express SST. PolyI:C treatment of dams induced a significant increase in the density of SST⁺ IWMNs in the offspring when delivered at both gestational stages with more regionally widespread effects observed at GD19. A positive correlation was observed between NeuN⁺ and SST⁺ IWMN density in animals exposed to polyI:C at GD19, but not controls. This is the first study to show that MIA increases IWMN density in adult offspring in a similar manner to that seen in the brain in schizophrenia. This suggests the MIA model will be useful in future studies aimed at probing the relationship between IWMNs and schizophrenia.

Schizophrenia may be conceptualised using a dimensional approach to examine trait-like expression such as schizotypy within non-clinical populations to better understand pathophysiology. A candidate psychosis-risk marker, the auditory mismatch negativity (MMN) is thought to index the functionality of glutamatergic NMDA receptor mediated neurotransmission. Although the MMN is robustly reduced in patients with schizophrenia, the association between MMN and schizotypy in the general population is under-investigated. Thirty-five healthy participants completed the Schizotypal Personality Questionnaire (SPQ) and a multi-feature MMN paradigm (standards 82%, 50¿ms, 1000¿Hz, 80¿dB) with duration (100¿ms), frequency (1200¿Hz) and intensity (90¿dB) deviants (6% each). Spearman's correlations were used to explore the association between schizotypal personality traits and MMN amplitude. Few associations were identified between schizotypal traits and MMN. Higher Suspiciousness subscale scores tended to be correlated with larger frequency MMN amplitude. A median-split comparison of the sample on Suspiciousness scores showed larger MMN (irrespective of deviant condition) in the High compared to the Low Suspiciousness group. The trend-level association between MMN and Suspiciousness is in contrast to the robustly attenuated MMN amplitude observed in schizophrenia. Reductions in MMN may reflect a schizophrenia-disease state, whereas non-clinical schizotypy may not be subserved by similar neuropathology.

The mismatch negativity (MMN) component of the auditory event-related potential, elicited in response to unexpected stimuli in the auditory environment, has great value for cognitive neuroscience research. It is changed in several neuropsychiatric disorders such as schizophrenia. The ability to measure and manipulate MMN-like responses in animal models, particularly rodents, would provide an enormous opportunity to learn more about the neurobiology underlying MMN. However, the MMN in humans is a very specific phenomenon: how do we decide which features we should focus on emulating in an animal model to achieve the highest level of translational validity? Here we discuss some of the key features of MMN in humans and summarise the success with which they have been translated into rodent models. Many studies from several different labs have successfully shown that the rat brain is capable of generating deviance detection responses that satisfy of the criteria for the human MMN.

Although the relationship between aging and cognitive decline is well established, there is substantial individual variability in the degree of cognitive decline in older adults. The present study investigates whether variability in cognitive performance in community-dwelling older adults is related to the presence of whole brain or tract-specific changes in white matter microstructure. Specifically, we examine whether age-related decline in performance on the Montreal Cognitive Assessment (MoCA), a cognitive screening tool, is mediated by the white matter microstructural decline. We also examine if this relationship is driven by the presence of cardiovascular risk factors or variability in cerebral arterial pulsatility, an index of cardiovascular risk. Sixty-nine participants (aged 43-87) completed behavioral and MRI testing including T1 structural, T2-weighted FLAIR, and diffusion-weighted imaging (DWI) sequences. Measures of white matter microstructure were calculated using diffusion tensor imaging analyses on the DWI sequence. Multiple linear regression revealed that MoCA scores were predicted by radial diffusivity (RaD) of white matter beyond age or other cerebral measures. While increasing age and arterial pulsatility were associated with increasing RaD, these factors did not mediate the relationship between total white matter RaD and MoCA. Further, the relationship between MoCA and RaD was specific to participants who reported at least one cardiovascular risk factor. These findings highlight the importance of cardiovascular risk factors in the presentation of cognitive decline in old age. Further work is needed to establish whether medical or lifestyle management of these risk factors can prevent or reverse cognitive decline in old age.

Prolonged heavy exposure to cannabis is associated with impaired cognition and brain functional and structural alterations. We recently reported attenuated mismatch negativity (MMN) and altered P50 sensory gating in chronic cannabis users. This study investigated the extent of brain functional recovery (indexed by MMN and P50) in chronic users after cessation of use. Eighteen ex-users (median 13.5 years prior regular use; median 3.5 years abstinence) and 18 nonusers completed (1) a multifeature oddball task with duration, frequency, and intensity deviants and (2) a P50 paired-click paradigm. Trend level smaller duration MMN amplitude and larger P50 ratios (indicative of poorer sensory gating) were observed in ex-users compared to controls. Poorer P50 gating correlated with prior duration of cannabis use. Duration of abstinence was positively correlated with duration MMN amplitude, even after controlling for age and duration of cannabis use. Impaired sensory gating and attenuated MMN amplitude tended to persist in ex-users after prolonged cessation of use, suggesting a lack of full recovery. An association with prolonged duration of prior cannabis use may indicate persistent cannabis-related alterations to P50 sensory gating. Greater reductions in MMN amplitude with increasing abstinence (positive correlation) may be related to either self-medication or an accelerated aging process.

For 30 years, the independent race model has been used to account for the attempt to reactively inhibit on-going responses in the stop-signal task (reactive behavioral inhibition). The success of the race model derives in part by assuming that motor response activation speed is not different on inhibition trials compared to trials where inhibition is not required. To date, neurophysiological evidence supporting this assumption (context independence) has been limited, especially in human participants. In this study, we used EEG to investigate stop-signal task performance in human participants, focusing on lateralized readiness potentials (LRPs) to examine context independence in human primary motor cortex (M1). The current results provided support for the context independence assumption, and further showed that successful inhibition was largely contingent upon the timing of response activation in M1 relative to stop-signal onset. These data afford a valuable insight into how stop-signal response inhibition is effected in the human brain.

Our understanding of the complex interplay between structural and functional organisation of brain networks is being advanced by the development of novel multi-modal analyses approaches. The Age-ility Project (Phase 1) data repository offers open access to structural MRI, diffusion MRI, and resting-state fMRI scans, as well as resting-state EEG recorded from the same community participants (n = 131, 15-35 y, 66 male). Raw imaging and electrophysiological data as well as essential demographics are made available via the NITRC website. All data have been reviewed for artifacts using a rigorous quality control protocol and detailed case notes are provided.

Although the scientific community appears to know a lot about MMN, about its neural generators and the computational processes that underlie its generation, do we have sufficient knowledge to understand what causes the reduction of MMN amplitude in schizophrenia? Here we attempt to integrate the evidence presented in this series of papers for the special issue on MMN in schizophrenia together with evidence from other new relevant research and ask-what have we learnt? While MMN research was the purview for decades of psychophysiologists interested in event-related potentials derived from scalp recorded EEG, it is now part of mainstream neuroscience research attracting the interest of basic auditory neuroscientists, neurobiologists and computational modellers. The confluence of these developments together with increasing clinical research has certainly advanced our understanding of the causes of reduced MMN in schizophrenia as this integrative review attempts to demonstrate-but much remains to be learnt. Future advances will rely on the application of multiple methodologies and approaches in order to arrive at better understanding of the neurobiology of MMN and implications for schizophrenia.

Background Alcohol misuse and depression represent two major social and health problems globally. These conditions commonly co-occur and both are associated with significant cognitive impairment. Despite this, few studies have examined the impact on cognitive functioning of co-occurring alcohol misuse and depression. This study aims to critically review findings from peer-reviewed published articles examining neuropsychological test performance among samples of people with co-occurring alcohol misuse and depression. Method A comprehensive literature search was conducted, yielding six studies reporting neuropsychological profiles of people with co-occurring alcohol misuse and depression. Results comparing cognitive functioning of people with this comorbidity to those with alcohol misuse alone, depression alone, healthy controls and published norms were examined as well as those describing the correlation between depressive symptoms and cognitive functioning in people with alcohol use disorders. Results In the majority of instances, the comorbid groups did not differ significantly from those with depression only or alcohol misuse only, nor from healthy controls or published norms. In the cases where a difference in neuropsychological test scores between groups was found, it was not consistently identified across studies. However, visual memory was identified in two studies as being impaired in comorbid samples and is worthy of inclusion in future studies. Limitations Due to the small number of included studies and the large variation in inclusion criteria as well as differing assessment tools and methodologies between studies, the review did not include a quantitative synthesis. Conclusions Research into cognitive deficits among people with singly occurring versus co-occurring alcohol misuse and depression is accumulating. Evidence suggests that the neuropsychological performance among samples with this comorbidity is generally not severely impaired and is unlikely to preclude benefit from treatment.

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

Hospital-treated deliberate self-poisoning (DSP) by central nervous system depressant drugs (CNS-D) has been associated with impairments in cognitive and psychomotor functions at the time of discharge. We aimed to replicate this finding and to compare recovery in the first month after discharge for CNS-D and CNS nondepressant drug ingestions. We also examined a series of multivariate explanatory models of recovery of neurocognitive outcomes over time. The CNS-D group was impaired at discharge compared with the CNS-nondepressant group in cognitive flexibility, cognitive efficiency, and working memory. There were no significant differences at discharge in visual attention, processing speed, visuomotor speed, or inhibition speed. Both groups improved in the latter measures over 1 month of follow-up. However, the CNS-D group's recovery was significantly slower for key neurocognitive domains underlying driving in complex traffic situations, namely, cognitive flexibility, cognitive efficiency, and working memory. Patients discharged after DSP with CNS-D drugs have impairments of some critical cognitive functions that may require up to 1 month to recover. Although more pre-than post-DSP variables were retained as explanatory models of neurocognitive performance overall, recovery over time could not be explained by any one of the measured covariates. Tests of cognitive flexibility could be used in clinical settings as a proxy measure for recovery of driving ability. Regulatory authorities should also consider the implications of these results for the period of nondriving advised after ingestion of CNS-D in overdose. Future research, with adequate sample size, should examine contributions of other variables to the pattern of recovery over time.

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R2 increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

The aim of this review is to explore the phenomenon of reduced mismatch negativity (MMN) in persons with schizophrenia and the possible relationship it has with attention impairments. In doing so we discuss (i) the prediction error account of MMN, (ii) reduced MMN as a faulty predictive processing system in persons with schizophrenia, (iii) the role of these systems in relevance filtering and attentional resource protection, (iv) attentional impairments in persons with schizophrenia, and (v) research that has explored MMN and attention in schizophrenia groups. Our review of the literature suggests that no study has appropriately examined the functional impact of smaller MMN in schizophrenia on the performance of a concurrent attention task. We conclude that future research should explore this notion further in the hope that it might embed MMN findings within outcomes of functional significance to individuals with the illness and those providing treatment. This article is part of a Special Issue entitled SI: Prediction and Attention.

Cognitive control involves both proactive and reactive processes. Paradigms that rely on reactive control have shown that frontoparietal oscillatory synchronization in the theta frequency band is associated with interference control. This study examines whether proactive control is also associated with connectivity in the same frontoparietal theta network or involves a distinct neural signature. A task-switching paradigm was used to differentiate between proactive and reactive control processes, involved in preparing to switch or repeat a task and resolving post-target interference, respectively. We confirm that reactive control is associated with frontoparietal theta connectivity. Importantly, we show that proactive control is also associated with theta band oscillatory synchronization but in a different frontoparietal network. These findings support the existence of distinct proactive and reactive cognitive control processes that activate different theta frontoparietal oscillatory networks.

Mismatch negativity (MMN) is a scalp-recorded electrical potential that occurs in humans in response to an auditory stimulus that defies previously established patterns of regularity. MMN amplitude is reduced in people with schizophrenia. In this study, we aimed to develop a robust and replicable rat model of MMN, as a platform for a more thorough understanding of the neurobiology underlying MMN. One of the major concerns for animal models of MMN is whether the rodent brain is capable of producing a human-like MMN, which is not a consequence of neural adaptation to repetitive stimuli. We therefore tested several methods that have been used to control for adaptation and differential exogenous responses to stimuli within the oddball paradigm. Epidural electroencephalographic electrodes were surgically implanted over different cortical locations in adult rats. Encephalographic data were recorded using wireless telemetry while the freely-moving rats were presented with auditory oddball stimuli to assess mismatch responses. Three control sequences were utilized: the flip-flop control was used to control for differential responses to the physical characteristics of standards and deviants; the many standards control was used to control for differential adaptation, as was the cascade control. Both adaptation and adaptation-independent deviance detection were observed for high frequency (pitch), but not low frequency deviants. In addition, the many standards control method was found to be the optimal method for observing both adaptation effects and adaptation-independent mismatch responses in rats. Inconclusive results arose from the cascade control design as it is not yet clear whether rats can encode the complex pattern present in the control sequence. These data contribute to a growing body of evidence supporting the hypothesis that rat brain is indeed capable of exhibiting human-like MMN, and that the rat model is a viable platform for the further investigation of the MMN and its associated neurobiology.

Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia. © 2014 Macmillan Publishers Limited. All rights reserved.

Repetitive patterning facilitates inferences about likely properties of sound to follow. Mismatch negativity (MMN) occurs when sound fails to match an inference. Smaller MMN in schizophrenia indexes deficient gain control (difference in utilizing a limited dynamic range). Although it is clear that this group has a lower limit to MMN size, this study addressed whether smaller MMN indicates impaired perceptual inference. MMN was elicited to four deviants in two sequences: one in which occurrence was random and one in which it was paired. Despite smaller MMN, persons with schizophrenia are equally able to reduce MMN size evoked by a deviant when its occurrence is cued. Results also expose alterations in the evoked response to repeated sounds that appear to be exacerbations of age-related amplitude decline. Since these anomalies impact the computed MMN, they highlight the need to identify all contributions to limits in gain control in schizophrenia. © 2014 Society for Psychophysiological Research.

Stop-signal paradigms operationalize a basic test of goal-directed behaviour whereby an overarching stop goal that is performed intermittently must be maintained throughout ongoing performance of a reaction time go task (go goal). Previous studies of sustained brain activation during stop-signal task performance in humans did not observe activation of the dorsolateral prefrontal cortex (DLPFC) that, in concert with the parietal cortex, is known to subserve goal maintenance. Here we explored the hypothesis that a DLPFC and parietal network has a key role in supporting ongoing stop-signal task performance. We used a blocked functional magnetic resonance imaging design that included blocks of trials containing typical stop-signal paradigm stimuli that were performed under three conditions: Stop condition, which required reaction time responding to go stimuli and inhibition of cued responses upon presentation of a stop signal; Go condition, identical except that the tone was ignored; and Passive condition, which required only quiescent attention to stimuli. We found that, whereas a distributed corticothalamic network was more active in Stop compared with Go, only the right DLPFC and bilateral parietal cortex survived after masking that contrast with Stop compared with Passive. These findings indicate that sustained activation of a right dominant frontoparietal network supports stop goal processes during ongoing performance of the stop-signal task. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Objective The present study was undertaken to evaluate the effect of cognitive training in improving trained and untrained cognitive processes in schizophrenia. Methods A simple pre- and post experimental study with a three month follow-up was conducted to determine the efficacy of cognitive training in speed of processing and executive functions improving cognition in 22 schizophrenia patients. Results Significant improvement was found in those cognitive domains specifically targeted in the training protocol, but also to a limited extent on verbal memory and social cognition. There was also evidence of improvements in symptoms and social functioning. The training effects failed to transfer to community functioning skills however. Except for social cognition, these improvements were maintained at 3 month follow-up. Conclusion The study highlights the importance of understanding the mechanisms that contribute to the transfer of skills as well as the maintenance of cognitive changes in individuals with schizophrenia. © 2013 Elsevier Inc. All rights reserved.

Background Schizophrenia is associated with lower pre-morbid intelligence (IQ) in addition to (pre-morbid) cognitive decline. Both schizophrenia and IQ are highly heritable traits. Therefore, we hypothesized that genetic variants associated with schizophrenia, including copy number variants (CNVs) and a polygenic schizophrenia (risk) score (PSS), may influence intelligence. Method IQ was estimated with the Wechsler Adult Intelligence Scale (WAIS). CNVs were determined from single nucleotide polymorphism (SNP) data using the QuantiSNP and PennCNV algorithms. For the PSS, odds ratios for genome-wide SNP data were calculated in a sample collected by the Psychiatric Genome-Wide Association Study (GWAS) Consortium (8690 schizophrenia patients and 11 831 controls). These were used to calculate individual PSSs in our independent sample of 350 schizophrenia patients and 322 healthy controls. Results Although significantly more genes were disrupted by deletions in schizophrenia patients compared to controls (p = 0.009), there was no effect of CNV measures on IQ. The PSS was associated with disease status (R 2 = 0.055, p = 2.1 × 10 -7) and with IQ in the entire sample (R 2 = 0.018, p = 0.0008) but the effect on IQ disappeared after correction for disease status. Conclusions Our data suggest that rare and common schizophrenia-associated variants do not explain the variation in IQ in healthy subjects or in schizophrenia patients. Thus, reductions in IQ in schizophrenia patients may be secondary to other processes related to schizophrenia risk. © Cambridge University Press 2013.

The stop-signal paradigm is increasingly being used as a probe of response inhibition in basic and clinical neuroimaging research. The critical feature of this task is that a cued response is countermanded by a secondary 'stop-signal' stimulus offset from the first by a 'stop-signal delay'. Here we explored the role of task difficulty in the stop-signal task with the hypothesis that what is critical for successful inhibition is the time available for stopping, that we define as the difference between stop-signal onset and the expected response time (approximated by reaction time from previous trial). We also used functional magnetic resonance imaging (fMRI) to examine how the time available for stopping affects activity in the putative right inferior frontal gyrus and presupplementary motor area (right IFG-preSMA) network that is known to support stopping. While undergoing fMRI scanning, participants performed a stop-signal variant where the time available for stopping was kept approximately constant across participants, which enabled us to compare how the time available for stopping affected stop-signal task difficulty both within and between subjects. Importantly, all behavioural and neuroimaging data were consistent with previous findings. We found that the time available for stopping distinguished successful from unsuccessful inhibition trials, was independent of stop-signal delay, and affected successful inhibition depending upon individual SSRT. We also found that right IFG and adjacent anterior insula were more strongly activated during more difficult stopping. These findings may have critical implications for stop-signal studies that compare different patient or other groups using fixed stop-signal delays. © 2013 .