Schizophrenia is often conceptualized as a brain network disorder, yet the organizational principles and heterogeneity underlying widespread cortical abnormalities remain poorly understood. Leveraging multisite MRI data from 3,958 individuals diagnosed with schizophrenia and 5,489 neurotypical individuals, we studied the cortical organization and its subtyping by analyzing individualized cortical network similarity. We used eigenvector decompositions to study spatial patterning of the gradients and graph theory to study small-world topology. Individuals with schizophrenia showed widespread alterations of gradient loadings, which followed inferior-superior and frontal-temporal axes. Alterations in small-world topology were localized in key network hubs, including the insula and anterior cingulate cortex. Brain-symptom association analyses identified a latent dimension linking disorganization symptoms to topological alterations. Finally, clustering cortical alterations identified two robust subtypes, characterized by divergent anterior cingulate (S1) versus temporoparietal (S2) thickness differences aligned with the intrinsic gradient-topology patterns. Both subtypes were present early in the illness and stable across disease stages and age groups. These findings reveal systematic disruptions of cortical organization in schizophrenia, providing a network-level framework for macroscale brain organization and inter-individual heterogeneity.

Implicit visuomotor sequence learning is crucial for acquiring skills that result in automated behaviors. The oscillatory dynamics underpinning this learning process are not well understood. To address this gap, the current study employed electroencephalography with a medium-density array (64 electrodes) to investigate oscillatory activity associated with implicit visuomotor sequence learning in the Serial Reaction Time task. In the task, participants unknowingly learn a series of finger movements. Eighty-five healthy adults participated in the study. Analyses revealed that theta activity at the vertex and alpha/beta activity over the motor areas decreased over the course of learning. No associations between alpha/beta and theta power were observed. These findings are interpreted within a dual-process framework: midline theta activity is posited to regulate top-down attentional processes, whereas beta activity from motor areas underlies the bottom-up encoding of sensory information from movement. From this model, we suggest that during implicit visuomotor sequence learning, top-down processes become disengaged (indicated by a reduction in theta activity), and modality specific bottom-up processes encode the motor sequence (indicated by a reduction in alpha/beta activity).

Introduction Altered neuromuscular control of the scapula and humeral head is a typical feature of multidirectional instability (MDI) of the glenohumeral joint, suggesting a central component to this condition. A previous randomised controlled trial showed MDI patients participating in the Watson Instability Program 1 (WIP1) had significantly improved clinical outcomes compared with a general shoulder strength programme. The aim of this paper is to outline a multimodal MRI protocol to identify potential ameliorative effects of the WIP1 on the brain.Methods and analysis Thirty female participants aged 18–35 years with right-sided atraumatic MDI and 30 matched controls will be recruited. MDI patients will participate in 24 weeks of the WIP1, involving prescription and progression of a home exercise programme. Multimodal MRI scans will be collected from both groups at baseline and in MDI patients at follow-up. Potential brain changes (primary outcome 1) in MDI patients will be probed using region-of-interest (ROI) and whole-brain approaches. ROIs will depict areas of functional alteration in MDI patients during executed and imagined shoulder movements (MDI vs controls at baseline), then examining the effects of the 24-week WIP1 intervention (baseline vs follow-up in MDI patients only). Whole-brain analyses will examine baseline versus follow-up voxel-wise measures in MDI patients only. Outcome measures used to assess WIP1 efficacy will include the Western Ontario Shoulder Index and the Melbourne Instability Shoulder Score (primary outcomes 2 and 3). Secondary outcomes will include the Tampa Scale for Kinesiophobia, Short Form Orebro, Global Rating of Change Score, muscle strength, scapular upward rotation, programme compliance and adverse events.Discussion This trial will establish if the WIP1 is associated with brain changes in MDI.Ethics and dissemination Participant confidentiality will be maintained with publication of results. Swinburne Human Research Ethics Committee (Ref: 20202806-5692).Trial registration number Australian New Zealand Clinical Trial Registry (ACTRN12621001207808).

Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can hamper the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (https://www.neurodesk.org/). Neurodesk includes a browser-accessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.

The AirSticks are a gesture-based audio-visual instrument. This latest incarnation combines spatially controlled sound design with a 3D game environment projected onto a transparent screen. This system allows for the composition of highly integrated audio-visual environments superimposed directly onto the performance area.

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Generalised Anxiety Disorder (GAD) is a prevalent, chronic mental health disorder. The measurement of regional brain gamma-aminobutyric acid (GABA) offers insight into its role in anxiety and is a potential biomarker for treatment response. Research literature suggests Piper methysticum (Kava) is efficacious as an anxiety treatment, but no study has assessed its effects on central GABA levels. This study investigated dorsal anterior cingulate (dACC) GABA levels in 37 adult participants with GAD. GABA was measured using proton magnetic resonance spectroscopy (1H-MRS) at baseline and following an eight-week administration of Kava (standardised to 120 mg kavalactones twice daily) (n = 20) or placebo (n = 17). This study was part of the Kava for the Treatment of GAD (KGAD; ClinicalTrials.gov: NCT02219880), a 16-week intervention study. Compared with the placebo group, the Kava group had a significant reduction in dACC GABA (p = 0.049) at eight weeks. Baseline anxiety scores on the HAM-A were positively correlated with GABA levels but were not significantly related to treatment. Central GABA reductions following Kava treatment may signal an inhibitory effect, which, if considered efficacious, suggests that GABA levels are modulated by Kava, independent of reported anxiety symptoms. dACC GABA patterns suggest a functional role of higher levels in clinical anxiety but warrants further research for symptom benefit. Findings suggest that dACC GABA levels previously un-examined in GAD could serve as a biomarker for diagnosis and treatment response.

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca’s area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Background:While advances in the field of functional magnetic resonance imaging (fMRI) provide new opportunities to study brain networks underlying the experience of hallucinations in psychosis, there are methodological challenges unique to symptom-capture studies. Study Design:We extracted brain networks activated during hallucination-capture for schizophrenia patients when fMRI data collected from two sites was merged (combined N = 27). A multidimensional analysis technique was applied, which would allow separation of brain networks involved in the hallucinatory experience itself from those involved in the motor response of indicating the beginning and end of the perceived hallucinatory experience. To avoid reverse inference when attributing a function (e.g., a hallucination) to anatomical regions, it was required that longer hallucinatory experiences produce extended brain responses relative to shorter. Study Results:For radio-speech sound files, an auditory perception brain network emerged, and displayed speech-duration-dependent hemodynamic responses (HDRs). However, in the hallucination-capture blocks, no network showed hallucination-duration-dependent HDRs, but a retrieved network that was anatomically classified as motor response emerged. Conclusions:During symptom capture of hallucinations during fMRI, no HDR showed duration dependence, but a brain network anatomically matching the motor response network was retrieved. Previous reports on brain networks detected by fMRI during hallucination capture are reviewed in this context; namely, that the brain networks interpreted as involved in hallucinations may in fact be involved only in the motor response indicating the onset of the hallucination.

Sex differences in symptoms and executive control across schizophrenia spectrum disorders (SSD) are consistently reported. Similarly, these findings of sex differences are also observed in schizotypy, that is, schizophrenia-like features occurring in healthy individuals in the absence of a clinical diagnosis. This study aimed to examine the relationships between performance on three major domains of executive control: performance monitoring, response inhibition, and cognitive set-shifting, and schizotypy factor scores in both SSD patients and healthy controls (HCs), and whether sex moderated any relationships observed. A total of 111 (67 males and 44 females) patients with SSD and 258 (129 males and 129 females) HCs were included in this study. Schizotypal personality traits (in both SSD and HC) was assessed using the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE). Executive control performance was assessed using seven tasks. Stepwise linear regressions revealed that performance on cognitive set-shifting tasks was significantly associated with the introvertive anhedonia, cognitive disorganisation, and unusual experiences subscales of the O-LIFE. When sex was examined as a moderator, it was not a significant moderator of any of the relationships between cognitive set-shifting tasks and schizotypy factors. The results suggest that independent of sex, cognitive set-shifting ability is associated to an increased vulnerability to schizotypal personality traits, although performance monitoring and response inhibition did not.

Abstract Empirical work has shown that subjective age is susceptible to momentary fluctuation throughout the day, and in certain contexts like challenging cognitive evaluations. We propose and test a contextual model that describes how momentary experiences impact subjective age, which in turn impacts daily activities and well-being. Using an experience sampling approach, 200 participants were asked to complete 6 surveys per day for a week. Questions asked about the task they were engaged in, including mental, physical and social engagement, challenge, motivation, confidence, and enjoyment. Participants also completed a manipulation of mental challenge and reported their momentary subjective age. Preliminary multilevel models show that certain momentary factors, such as whether participants were enjoying a task or found the task engaging, predict fluctuations in subjective age. We will also discuss moderators, subjective age domains, time of day effects, and the cross-lagged influence of cognitive stressors over time.

Despite a growing body of research, there is yet to be a cohesive synthesis of studies examining differences in brain morphology according to patterns of cognitive function among both schizophrenia-spectrum disorder (SSD) and bipolar disorder (BD) individuals. We aimed to provide a systematic overview of the morphological differences-inclusive of grey and white matter volume, cortical thickness, and cortical surface area-between cognitive subgroups of these disorders and healthy controls, and between cognitive subgroups themselves. An initial search of PubMed and Scopus databases resulted in 1486 articles of which 20 met inclusion criteria and were reviewed in detail. The findings of this review do not provide strong evidence that cognitive subgroups of SSD or BD map to unique patterns of brain morphology. There is preliminary evidence to suggest that reductions in cortical thickness may be more strongly associated with cognitive impairment, whilst volumetric deficits may be largely tied to the presence of disease.

BACKGROUND: Autistic adults have difficulty in learning vocational and social skills, which often translates into low employment rates. Video self-modelling (VSM) is an effective educational technique for high-support-needs autistic adults, with the ability to teach challenging vocational skills as well as basic social skills. OBJECTIVE: The present study examined the use of video self-modelling to teach vocational and social skills to a 22-yearold autistic adult. Target behaviours categories included (1) reading order forms, (2) transporting goods, and (3) engaging with customers. METHODS: A multiple baseline design was used to evaluate the effectiveness of the videos in teaching these target behaviours. The dependent variables were the percentage of tasks completed correctly, and quantitative prompt dependency, using a least-to-most prompting strategy. RESULTS: Results showed that VSM modestly improved reading order forms and transporting goods, and moderately improved engagement with customers. CONCLUSION: This intervention resulted in the successful employment of an autistic adult in a job that he desired, whilst teaching him skills he specifically struggled with. As such, VSM should be considered for others wanting to learn combined social and vocational skills.

Background: Cognitive heterogeneity in schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) has been explored using clustering analyses. However, the resulting subgroups have not been cognitively validated beyond measures used as clustering variables themselves. We compared the emergent cross-diagnostic subgroups of SSD and BD patients on measures used to classify them, and also across a range of alternative cognitive measures assessing some of the same constructs. Method: Domain scores from the Matrics Consensus Cognitive Battery were used in a cross-diagnostic clustering analysis of 86 patients with SSD (n = 45) and BD (n = 41). The emergent subgroups were then compared to each other and healthy controls (n = 76) on these and alternative measures of these domains, as well as on premorbid IQ, global cognition and a proxy of cognitive decline. Results: A three-cluster solution was most appropriate, with subgroups labelled as Globally Impaired, Selectively Impaired, and Superior/Near-Normal relative to controls. With the exception of processing speed performance, the subgroups were generally differentiated on the cognitive domain scores used as clustering variables. Differences in cognitive performance among these subgroups were not always statistically significant when compared on the alternative cognitive measures. There was evidence of global cognitive impairment and putative cognitive decline in the two cognitively impaired subgroups. Limitations: For clustering analysis, sample size was relatively small. Conclusions: The overall pattern of findings tentatively suggest that emergent cross-diagnostic cognitive subgroups are not artefacts of the measures used to define them, but may represent the outcome of different cognitive trajectories.

Increasing evidence suggests that facial emotion recognition is impaired in bipolar disorder (BD). However, patient-control differences are small owing to ceiling effects on the tasks used to assess them. The extant literature is also limited by a relative absence of attention towards identifying patterns of emotion misattribution or understanding whether neutral faces are mislabelled in the same way as ones displaying emotion. We addressed these limitations by comparing facial emotion recognition performance in BD patients and healthy controls on a novel and challenging task. Thirty-four outpatients with BD I and 32 demographically matched healthy controls completed a facial emotion recognition task requiring the labelling of neutral and emotive faces displayed at low emotional intensities. Results indicated that BD patients were significantly less accurate at labelling faces than healthy controls, particularly if they displayed fear or neutral expressions. There were no between-group differences in response times or patterns of emotion mislabelling, with both groups confusing sad and neutral faces, although BD patients also mislabelled sad faces as angry. Task performance did not significantly correlate with mood symptom severity in the BD group. These findings suggest that facial emotion recognition impairments in BD extend to neutral face recognition. Emotion misattribution occurs in a similar, albeit exaggerated manner in patients with BD compared to healthy controls. Future behavioural and neuroimaging research should reconsider the use of neutral faces as baseline stimuli in their task designs.

SummaryAn analysis of an internationally shared functional magnetic resonance imaging (fMRI) data involving healthy participants and schizophrenia patients extracted brain networks involved in listening to radio speech and capture hallucination experiences. A multidimensional analysis technique demonstrated that for radio-speech sound files, a brain network matching known auditory perception networks emerged, and importantly, displayed speech-duration-dependent hemodynamic responses (HDRs), confirming fMRI detection of these speech events. In the hallucination-capture data, although a sensorimotor (response) network emerged, it did not show hallucination-duration-dependent HDRs. We conclude that although fMRI retrieved the brain network involved in generating the motor responses indicating the start and end of an experienced hallucination, the hallucination event itself was not detected. Previous reports on brain networks detected by fMRI during hallucination capture is reviewed in this context.

It has been documented that individuals who hear auditory verbal hallucinations (AVH) exhibit diminished capabilities in processing external speech. While functional neuroimaging studies have attempted to characterise the cortical regions and networks facilitating these deficits in a bid to understand AVH, considerable methodological heterogeneity has prevented a consensus being reached. The current systematic review investigated the neurobiological underpinnings of external speech processing deficits in voice-hearers in 38 studies published between January 1990 to June 2020. AVH-specific deviations in the activity and lateralisation of the temporal auditory regions were apparent when processing speech sounds, words and sentences. During active or affective listening tasks, functional connectivity changes arose within the language, limbic and default mode networks. However, poor study quality and lack of replicable results plague the field. A detailed list of recommendations has been provided to improve the quality of future research on this topic.

This paper describes the technology, concepts and development of Computer Storm, a live audio-visual piece created for a gestural instrument, the 'AirSticks'. The AirSticks allow the composition, performance and improvisation of live electronic music and graphics using movements captured by handheld motion controllers. In this piece, the AirSticks are combined with commodity depth sensors, and a custom visualisation system 'Confluence' which generates graphics from music and motion in real-time. The hardware used to display the images within the performance space is also described, as well as an overview of the resulting performance, which explores harmony across music, visuals and movement, and investigates our complex relationship with technology.

Objectives: Schizophrenia is a debilitating psychiatric illness associated with positive and negative symptoms as well as significant impairments in cognition. Current antipsychotic medications do not alleviate these cognitive deficits, and more effective therapeutic options are required. Increased oxidative stress and altered antioxidant levels, including glutathione (GSH) have been observed both in individuals with cognitive impairment and in people with schizophrenia. A GSH precursor, the antioxidant N-acetylcysteine (NAC) has been investigated as a novel treatment for the cognitive symptoms of schizophrenia, and recent research suggests that NAC may be a promising adjunctive treatment option. However, the current literature lacks integration as to why NAC may effectively improve cognition in schizophrenia. The present theoretical synthesis aimed to address this gap by examining the processes by which NAC may improve cognitive function in schizophrenia. Methods: The schizophrenia literature was reviewed in three key domains: cognitive impairment, the relationship between oxidative stress and cognition, and the efficacy of NAC as a novel treatment. This led to a theoretical analysis of the neurobiological processes by which NAC may improve cognition in schizophrenia. Results: This theoretical review concluded that improved cognition may result from a combination of factors, including decreased oxidative stress, neuroprotection of cognitive networks and an increase in glutamatergic modulation of the N-methyl-d-aspartate receptor system. Whilst a number of mechanisms by which NAC may improve cognition and symptoms in schizophrenia have been proposed, there is still limited understanding of the specific metabolic pathways involved and how they interrelate and modify specific symptomology. Discussion: Exploration of how NAC treatment may act to improve cognitive function could guide clinical trials by investigation of the specific neurotransmitter systems and processes involved, allowing for targeted neurological outcome measures. Future research would benefit from the investigation of both in vivo cortical GSH concentration and peripheral plasma GSH in a population of individuals with chronic schizophrenia.