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BACKGROUND: Disruptions of axonal connectivity are thought to be a core pathophysiological feature of psychotic illness, but whether they are present early in the illness, prior to antipsychotic exposure, and whether they can predict clinical outcome remains unknown. METHODS: We acquired diffusion-weighted MRI to map structural connectivity between each pair of 319 parcellated brain regions in 61 antipsychotic-naive individuals with First Episode Psychosis (FEP; 15-25 years, 46% female) and a demographically matched sample of 27 control participants, along with clinical follow-up data in patients three months and 12 months after the scan. We used connectome-wide analyses to map disruptions of inter-regional pairwise connectivity and connectome-based predictive modelling to predict longitudinal change in symptoms and functioning. RESULTS: Individuals with FEP showed disrupted connectivity in a brain-wide network linking all brain regions when compared with controls (pFWE=.03). Baseline structural connectivity significantly predicted change in functioning over 12 months (r=.44;pFWE=.041), such that lower connectivity within fronto-striato-thalamic systems predicted worse functional outcomes. CONCLUSIONS: Brain-wide reductions of structural connectivity exist during the early stages of psychotic illness and cannot be attributed to antipsychotic medication. Moreover, baseline measures of structural connectivity can predict change in patient functional outcomes up to one year after engagement with treatment services.

The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case-control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive-compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience-ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks.

IMPORTANCE: Psychotic illness is associated with anatomically distributed gray matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown. OBJECTIVE: To test the hypothesis that brain network architecture constrains cross-sectional and longitudinal gray matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicenters from which volume loss spreads. DESIGN, SETTINGS, AND PARTICIPANTS: This case-control study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naive first-episode psychosis (n = 59) and a group of patients receiving medications within 3 years of psychosis onset (n = 121). Late-stage cohorts comprised 2 independent samples of people with established schizophrenia (n = 136). Each patient group had a corresponding matched control group (n = 218). A sample of healthy adults (n = 356) was used to derive representative structural and functional brain networks for modeling of network-based spreading processes. Longitudinal illness-related and antipsychotic-related gray matter changes over 3 and 12 months were examined using a triple-blind randomized placebo-control magnetic resonance imaging study of the antipsychotic-naive patients. All data were collected between April 29, 2008, and January 15, 2020, and analyses were performed between March 1, 2021, and January 14, 2023. MAIN OUTCOMES AND MEASURES: Coordinated deformation models were used to estimate the extent of gray matter volume (GMV) change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicenters of volume loss, a network diffusion model was used to simulate the spread of pathology from different seed regions. Correlations between estimated

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women’s worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7, 876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women’s brains and provide initial evidence for neuroscience-informed policies for gender equality.

Dysfunction of fronto-striato-thalamic (FST) circuits is thought to contribute to dopaminergic dysfunction and symptom onset in psychosis, but it remains unclear whether this dysfunction is driven by aberrant bottom-up subcortical signalling or impaired top-down cortical regulation. We used spectral dynamic causal modelling of resting-state functional MRI to characterize the effective connectivity of dorsal and ventral FST circuits in a sample of 46 antipsychotic-naïve first-episode psychosis patients and 23 controls and an independent sample of 36 patients with established schizophrenia and 100 controls. We also investigated the association between FST effective connectivity and striatal 18F-DOPA uptake in an independent healthy cohort of 33 individuals who underwent concurrent functional MRI and PET. Using a posterior probability threshold of 0.95, we found that midbrain and thalamic connectivity were implicated as dysfunctional across both patient groups. Dysconnectivity in first-episode psychosis patients was mainly restricted to the subcortex, with positive symptom severity being associated with midbrain connectivity. Dysconnectivity between the cortex and subcortical systems was only apparent in established schizophrenia patients. In the healthy 18F-DOPA cohort, we found that striatal dopamine synthesis capacity was associated with the effective connectivity of nigrostriatal and striatothalamic pathways, implicating similar circuits to those associated with psychotic symptom severity in patients. Overall, our findings indicate that subcortical dysconnectivity is evident in the early stages of psychosis, that cortical dysfunction may emerge later in the illness, and that nigrostriatal and striatothalamic signalling are closely related to striatal dopamine synthesis capacity, which is a robust marker for psychosis.

01 juni 2023, Item does not contain fulltext, The anatomy of the brain necessarily constrains its function, but precisely how remains unclear. The classical and dominant paradigm in neuroscience is that neuronal dynamics are driven by interactions between discrete, functionally specialized cell populations connected by a complex array of axonal fibres(1-3). However, predictions from neural field theory, an established mathematical framework for modelling large-scale brain activity(4-6), suggest that the geometry of the brain may represent a more fundamental constraint on dynamics than complex interregional connectivity(7,8). Here, we confirm these theoretical predictions by analysing human magnetic resonance imaging data acquired under spontaneous and diverse task-evoked conditions. Specifically, we show that cortical and subcortical activity can be parsimoniously understood as resulting from excitations of fundamental, resonant modes of the brain's geometry (that is, its shape) rather than from modes of complex interregional connectivity, as classically assumed. We then use these geometric modes to show that task-evoked activations across over 10,000 brain maps are not confined to focal areas, as widely believed, but instead excite brain-wide modes with wavelengths spanning over 60 mm. Finally, we confirm predictions that the close link between geometry and function is explained by a dominant role for wave-like activity, showing that wave dynamics can reproduce numerous canonical spatiotemporal properties of spontaneous and evoked recordings. Our findings challenge prevailing views and identify a previously underappreciated role of geometry in shaping function, as predicted by a unifying and physically principled model of brain-wide dynamics.

Contains fulltext : 293775.pdf (Publisher’s version ) (Open Access), BACKGROUND: Neuroimaging studies of functional connectivity (FC) in autism have been hampered by small sample sizes and inconsistent findings with regard to whether connectivity is increased or decreased in individuals with autism, whether these alterations affect focal systems or reflect a brain-wide pattern, and whether these are age and/or sex dependent. METHODS: The study included resting-state functional magnetic resonance imaging and clinical data from the EU-AIMS LEAP (European Autism Interventions Longitudinal European Autism Project) and the ABIDE (Autism Brain Imaging Data Exchange) 1 and 2 initiatives of 1824 (796 with autism) participants with an age range of 5-58 years. Between-group differences in FC were assessed, and associations between FC and clinical symptom ratings were investigated through canonical correlation analysis. RESULTS: Autism was associated with a brainwide pattern of hypo- and hyperconnectivity. Hypoconnectivity predominantly affected sensory and higher-order attentional networks and correlated with social impairments, restrictive and repetitive behavior, and sensory processing. Hyperconnectivity was observed primarily between the default mode network and the rest of the brain and between cortical and subcortical systems. This pattern was strongly associated with social impairments and sensory processing. Interactions between diagnosis and age or sex were not statistically significant. CONCLUSIONS: The FC alterations observed, which primarily involve hypoconnectivity of primary sensory and attention networks and hyperconnectivity of the default mode network and subcortex with the rest of the brain, do not appear to be age or sex dependent and correlate with clinical dimensions of social difficulties, restrictive and repetitive behaviors, and alterations in sensory processing. These findings suggest that the observed connectivity alterations are stable, trait-like features of autism that are related to the main symptom domains of the

Contains fulltext : 293739.pdf (Publisher’s version ) (Open Access)

Both psychotic illness and subclinical psychosis-like experiences (PLEs) have been associated with cortico-striatal dysfunction. This work has largely relied on a discrete parcellation of the striatum into distinct functional areas, but recent evidence suggests that the striatum comprises multiple overlapping and smoothly varying gradients (i.e., modes) of functional organization. Here, we investigated two of these functional connectivity modes, previously associated with variations in the topographic patterning of cortico-striatal connectivity (first-order gradient), and dopaminergic innervation of the striatum (second-order gradient), and assessed continuities in striatal function from subclinical to clinical domains. We applied connectopic mapping to resting-state fMRI data to obtain the first-order and second-order striatal connectivity modes in two distinct samples: (1) 56 antipsychotic-free patients (26 females) with first-episode psychosis (FEP) and 27 healthy controls (17 females); and (2) a community-based cohort of 377 healthy individuals (213 females) comprehensively assessed for subclinical PLEs and schizotypy. The first-order "cortico-striatal" and second-order "dopaminergic" connectivity gradients were significantly different in FEP patients compared to controls bilaterally. In the independent sample of healthy individuals, variations in the left first-order "cortico-striatal" connectivity gradient were associated with inter-individual differences in a factor capturing general schizotypy and PLE severity. The presumed cortico-striatal connectivity gradient was implicated in both subclinical and clinical cohorts, suggesting that variations in its organization may represent a neurobiological trait marker across the psychosis continuum. Disruption of the presumed dopaminergic gradient was only noticeable in patients, suggesting that neurotransmitter dysfunction may be more apparent to clinical illness.

BACKGROUND: Despite reports of altered brain morphology in established bipolar disorder (BD), there is limited understanding of when these morphological abnormalities emerge. Assessment of patients during the early course of illness can help to address this gap, but few studies have examined surface-based brain morphology in patients at this illness stage. METHODS: We completed a secondary analysis of baseline data from a randomised control trial of BD individuals stabilised after their first episode of mania (FEM). The magnetic resonance imaging scans of n = 35 FEM patients and n = 29 age-matched healthy controls were analysed. Group differences in cortical thickness, surface area and gyrification were assessed at each vertex of the cortical surface using general linear models. Significant results were identified at p < 0.05 using cluster-wise correction. RESULTS: The FEM group did not differ from healthy controls with regards to cortical thickness or gyrification. However, there were two clusters of increased surface area in the left hemisphere of FEM patients, with peak coordinates falling within the lateral occipital cortex and pars triangularis. CONCLUSIONS: Cortical thickness and gyrification appear to be intact in the aftermath of a first manic episode, whilst cortical surface area in the inferior/middle prefrontal and occipitoparietal cortex is increased compared to age-matched controls. It is possible that increased surface area in the FEM group is the outcome of abnormalities in a premorbidly occurring process. In contrast, the findings raise the hypothesis that cortical thickness reductions seen in past studies of individuals with more established BD may be more attributable to post-onset factors.

01 september 2023, Contains fulltext : 296133.pdf (Publisher’s version ) (Open Access), The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case-control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive-compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience-ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks.

Background Neuroimaging studies of functional connectivity (FC) in autism have been hampered by small sample sizes and inconsistent findings with regard to whether connectivity is increased or decreased in individuals with autism, whether these alterations affect focal systems or reflect a brain-wide pattern, and whether these are age and/or sex dependent. Methods The study included resting-state functional magnetic resonance imaging and clinical data from the EU-AIMS LEAP (European Autism Interventions Longitudinal European Autism Project) and the ABIDE (Autism Brain Imaging Data Exchange) 1 and 2 initiatives of 1824 (796 with autism) participants with an age range of 5–58 years. Between-group differences in FC were assessed, and associations between FC and clinical symptom ratings were investigated through canonical correlation analysis. Results Autism was associated with a brainwide pattern of hypo- and hyperconnectivity. Hypoconnectivity predominantly affected sensory and higher-order attentional networks and correlated with social impairments, restrictive and repetitive behavior, and sensory processing. Hyperconnectivity was observed primarily between the default mode network and the rest of the brain and between cortical and subcortical systems. This pattern was strongly associated with social impairments and sensory processing. Interactions between diagnosis and age or sex were not statistically significant. Conclusions The FC alterations observed, which primarily involve hypoconnectivity of primary sensory and attention networks and hyperconnectivity of the default mode network and subcortex with the rest of the brain, do not appear to be age or sex dependent and correlate with clinical dimensions of social difficulties, restrictive and repetitive behaviors, and alterations in sensory processing. These findings suggest that the observed connectivity alterations are stable, trait-like features of autism that are related to the main symptom domains of the cond

Network control theory can be used to model how one should steer the brain between different states by driving a specific region with an input. The needed energy to control a network is often used to quantify its controllability, and controlling brain networks requires diverse energy depending on the selected input region. We use the theory of how input node placement affects the longest control chain (LCC) in the controllability of brain networks to study the role of the architecture of white matter fibers in the required control energy. We show that the energy needed to control human brain networks is related to the LCC, i.e., the longest distance between the input region and other regions in the network. We indicate that regions that control brain networks with lower energy have small LCCs. These regions align with areas that can steer the brain around the state space smoothly. By contrast, regions that need higher energy to move the brain toward different target states have larger LCCs. We also investigate the role of the number of paths between regions in the control energy. Our results show that the more paths between regions, the lower cost needed to control brain networks. We evaluate the number of paths by counting specific motifs in brain networks since determining all paths in graphs is a difficult problem., Comment: 14 pages, 8 figures

Contains fulltext : 248295.pdf (Publisher’s version ) (Open Access), Autism spectrum disorders are complex, with a strong genetic basis. Genetic research in autism spectrum disorders is limited by the fact that these disorders are largely heterogeneous so that patients are variable in their clinical presentations. To address this limitation, we investigated the genetics of individual dimensions of the autism spectrum disorder phenotypes, or autistic-like traits. These autistic-like traits are continuous variations in autistic behaviours that occur in the general population. Therefore, we meta-analysed data from four different population cohorts in which autistic-like traits were measured. We performed a set of genetic analyses to identify common variants for autistic-like traits, understand how these variants related to autism spectrum disorders, and how they contribute to neurobiological processes. Our results showed genetic associations with specific autistic-like traits and a link to the immune system. We offer an example of the potential to use a dimensional approach when dealing with heterogeneous, complex disorder like autism spectrum disorder. Decomposing the complex autism spectrum disorder phenotype in its core features can inform on the specific biology of these features which is likely to account to clinical variability in patients.

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

Dysfunction of fronto-striato-thalamic (FST) circuits is thought to contribute to dopaminergic dysfunction and symptom onset in psychosis, but it remains unclear whether this dysfunction is driven by aberrant bottom-up subcortical signaling or impaired top-down cortical regulation. We used spectral dynamic causal modelling of resting-state functional magnetic resonance imaging (fMRI) to characterize the effective connectivity of dorsal and ventral FST circuits in a sample of 46 antipsychotic-naive first-episode psychosis patients and 23 controls and an independent sample of 36 patients with established schizophrenia patients and 100 controls. We also investigated the association between FST effective connectivity and striatal [18F]DOPA uptake in an independent healthy cohort of 33 individuals who underwent concurrent fMRI and positron emission tomography. Using a posterior probability threshold of 0.95, we found that midbrain and thalamic connectivity were implicated as dysfunctional across both patient groups. Dysconnectivity in first-episode psychosis patients was mainly restricted to the subcortex, with positive symptom severity being associated with midbrain connectivity. Dysconnectivity between the cortex and subcortical systems was only apparent in established schizophrenia patients. In the healthy [18F]DOPA cohort, we found that striatal dopamine synthesis capacity was associated with the effective connectivity of nigrostriatal and striatothalamic pathways, implicating similar circuits to those associated with psychotic symptom severity in patients. Overall, our findings indicate that subcortical dysconnectivity is evident in the early stages of psychosis, that cortical dysfunction may emerge later in the illness, and that nigrostriatal and striatothalamic signaling are closely related to striatal dopamine synthesis capacity, which is a robust marker for psychosis.Copyright © The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

Contains fulltext : 248295.pdf (Publisher’s version ) (Open Access), Autism spectrum disorders are complex, with a strong genetic basis. Genetic research in autism spectrum disorders is limited by the fact that these disorders are largely heterogeneous so that patients are variable in their clinical presentations. To address this limitation, we investigated the genetics of individual dimensions of the autism spectrum disorder phenotypes, or autistic-like traits. These autistic-like traits are continuous variations in autistic behaviours that occur in the general population. Therefore, we meta-analysed data from four different population cohorts in which autistic-like traits were measured. We performed a set of genetic analyses to identify common variants for autistic-like traits, understand how these variants related to autism spectrum disorders, and how they contribute to neurobiological processes. Our results showed genetic associations with specific autistic-like traits and a link to the immune system. We offer an example of the potential to use a dimensional approach when dealing with heterogeneous, complex disorder like autism spectrum disorder. Decomposing the complex autism spectrum disorder phenotype in its core features can inform on the specific biology of these features which is likely to account to clinical variability in patients.

Contains fulltext : 248295.pdf (Publisher’s version ) (Open Access), Autism spectrum disorders are complex, with a strong genetic basis. Genetic research in autism spectrum disorders is limited by the fact that these disorders are largely heterogeneous so that patients are variable in their clinical presentations. To address this limitation, we investigated the genetics of individual dimensions of the autism spectrum disorder phenotypes, or autistic-like traits. These autistic-like traits are continuous variations in autistic behaviours that occur in the general population. Therefore, we meta-analysed data from four different population cohorts in which autistic-like traits were measured. We performed a set of genetic analyses to identify common variants for autistic-like traits, understand how these variants related to autism spectrum disorders, and how they contribute to neurobiological processes. Our results showed genetic associations with specific autistic-like traits and a link to the immune system. We offer an example of the potential to use a dimensional approach when dealing with heterogeneous, complex disorder like autism spectrum disorder. Decomposing the complex autism spectrum disorder phenotype in its core features can inform on the specific biology of these features which is likely to account to clinical variability in patients.

BACKGROUND: The finding that transcranial magnetic stimulation (TMS) can enhance memory performance via stimulation of parietal sites within the Cortical-Hippocampal Network counts as one of the most exciting findings in this field in the past decade. However, the first independent effort aiming to fully replicate this finding found no discernible influence of TMS on memory performance. OBJECTIVE: We examined whether this might relate to interindividual spatial variation in brain connectivity architecture, and the capacity of personalisation methodologies to overcome the noise inherent across independent scanners and cohorts. METHODS: We implemented recently detailed personalisation methodology to retrospectively compute individual-specific parietal targets and then examined relation to TMS outcomes. RESULTS: Closer proximity between actual and novel fMRI-personalized targets associated with greater improvement in memory performance. CONCLUSION: These findings demonstrate the potential importance of aligning brain stimulation targets according to individual-specific differences in brain connectivity, and extend upon recent findings in prefrontal cortex.

Goal-directed behavior is dependent upon the ability to detect errors and implement appropriate posterror adjustments. Accordingly, several studies have explored the neural activity underlying error-monitoring processes, identifying the insula cortex as crucial for error awareness and reporting mixed findings with respect to the anterior cingulate cortex (ACC). Variable patterns of activation have previously been attributed to insufficient statistical power. We therefore sought to clarify the neural correlates of error awareness in a large event-related functional magnetic resonance imaging (fMRI) study. Four hundred and two healthy participants undertook the error awareness task, a motor Go/No-Go response inhibition paradigm in which participants were required to indicate their awareness of commission errors. Compared to unaware errors, aware errors were accompanied by significantly greater activity in a network of regions, including the insula cortex, supramarginal gyrus (SMG), and midline structures, such as the ACC and supplementary motor area (SMA). Error awareness activity was related to indices of task performance and dimensional measures of psychopathology in selected regions, including the insula, SMG, and SMA. Taken together, we identified a robust and reliable neural network associated with error awareness.

Previous customers profoundly influence the purchasing or booking decision of potential customers, and, therefore, it is imperative for businesses to assess and evaluate the social media reviews on their services or products. The aim of this project was to introduce deep learning as a tool for analyzing and evaluating customer reviews in the hotel industry. More specifically, we aimed to design several recurrent neural networks (RNN) models to analyze hotel reviews and reactions gathered from a popular travel accommodation website, TripAdvisor. To analyze the reviews, four LSTM RNN models with different labels and a convolutional neural network (CNN) model were developed. All models were evaluated to determine the most suitable model for hyperparameter tuning and distinguish the best performing model multi-class text classification. Based on the performance metrics, LSTM RNN was reported to be promising for sentiment analysis and the LSTM RNN with three classes and five classes achieved the best performance outcomes compared to the other models.

Contains fulltext : 237038.pdf (Publisher’s version ) (Open Access)

Objectives: Age and female sex are risk factors for dementia, and menopause is associated with cognitive dysfunction. Previous work largely considered the effects of sex and menopause as being independent of age. We studied whether age interacts with sex or menopause in explaining imaging biomarkers of dementia during midlife. Method(s): In this cross-sectional study of UK Biobank participants with brain magnetic resonance imaging (MRI), we explored the interaction of age with sex or menopausal status in explaining total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), white matter hyperintensity volume (WMHV), regional cortical volume, and subcortical volume. Result(s): Data were available for 1827 postmenopausal women, 230 pre/perimenopausal women and 2165 men (median age 63.3 years). There was a significant interaction between age and sex (P=.024) for TBV, where the inverse association age with TBV was steeper in women (beta=-5.35 mL/year) than in men (beta=-4.77 mL/year). Similar age-sex interactions were also observed for GMV and WMV. In women, there was a significant interaction between age and menopausal status (P=.007) where the inverse association of age with TBV was steeper in postmenopausal (beta=-5.89 mL/year) than in pre/perimenopausal women (beta=-1.61 mL/year). Similar age-menopause interactions were found in predicting lower GMV and higher WMHV. Differences in the direction of these age-sex and age-menopause interactions were found for regional cortical and subcortical brain volumes. Conclusion(s): Sex and menopause both interact with age during midlife in explaining MRI biomarkers of dementia. Further work is required to understand the mechanisms driving these interactions to develop strategies for delaying dementia.Copyright © 2020 The Author(s) 2020. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Understanding how the living human brain functions requires sophisticated in vivo neuroimaging technologies to characterise the complexity of neuroanatomy, neural function, and brain metabolism. Fluorodeoxyglucose positron emission tomography (FDG-PET) studies of human brain function have historically been limited in their capacity to measure dynamic neural activity. Simultaneous [18F]-FDG-PET and functional magnetic resonance imaging (fMRI) with FDG infusion protocols enable examination of dynamic changes in cerebral glucose metabolism simultaneously with dynamic changes in blood oxygenation. The Monash vis-fPET-fMRI dataset is a simultaneously acquired FDG-fPET/BOLD-fMRI dataset acquired from n=10 healthy adults (18-49yrs) whilst they viewed a flickering checkerboard task. The dataset contains both raw (unprocessed) images and source data organized according to the BIDS specification. The source data includes PET listmode, normalization, sinogram and physiology data. Here, the technical feasibility of using opensource frameworks to reconstruct the PET listmode data is demonstrated. The dataset has significant re-use value for the development of new processing pipelines, signal optimisation methods, and to formulate new hypotheses concerning the relationship between neuronal glucose uptake and cerebral haemodynamics.Copyright © 2021. The Author(s).

Background: Aberrant dopaminergic activity within fronto-striato-thalamic (FST) circuits is thought to contribute to psychosis onset. It remains unclear whether primary abnormality arises from bottom-up subcortical signaling or impaired top-down cortical regulation. We mapped causal interactions (effective connectivity) of dorsal and ventral FST circuits across the psychosis continuum and identified connections associated with striatal dopamine synthesis. Method(s): Spectral dynamic causal modelling (DCM) for resting-state functional magnetic resonance imaging (fMRI) modelled FST effective connectivity in: (1) 46 antipsychotic-naive first-episode psychosis (FEP) patients and 23 controls; (2) 36 established schizophrenia (SCZ) patients and 100 controls; and (3) 33 healthy individuals assessed for psychosis-like experiences (PLEs) with concurrent [18F]DOPA positron emission tomography. DCM estimated FST connectivity in patients and their respective controls, associations with symptom severity in all cohorts, and with striatal [18F]DOPA uptake in the PLE group. Result(s): Patients commonly showed midbrain disinhibition and reduced top-down influence of thalamus on nucleus accumbens. Cortical dysfunction was only apparent in the SCZ group. Positive symptoms were primarily associated with bottom-up connectivity in FEP and a mixture of bottom-up and top-down connectivity in SCZ and PLE groups, with disinhibition of ventromedial prefrontal cortex and extrinsic connectivity of the midbrain implicated across all cohorts. Thalamic and midbrain connectivity were associated with striatal [18F]DOPA uptake. Conclusion(s): We identified a primary role for subcortical dysconnectivity in psychosis, with cortical dysfunction emerging in established illness. Effective connectivity of the midbrain and thalamus are robustly linked to positive symptom severity and striatal dopamine synthesis capacity, suggesting a central role in the emergence of psychotic symptoms. Supported By: Nationa

Objectives: Age and female sex are risk factors for dementia, and menopause is associated with cognitive dysfunction. Previous work largely considered the effects of sex and menopause as being independent of age. We studied whether age interacts with sex or menopause in explaining imaging biomarkers of dementia during midlife. Method(s): In this cross-sectional study of UK Biobank participants with brain magnetic resonance imaging (MRI), we explored the interaction of age with sex or menopausal status in explaining total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), white matter hyperintensity volume (WMHV), regional cortical volume, and subcortical volume. Result(s): Data were available for 1827 postmenopausal women, 230 pre/perimenopausal women and 2165 men (median age 63.3 years). There was a significant interaction between age and sex (P=.024) for TBV, where the inverse association age with TBV was steeper in women (beta=-5.35 mL/year) than in men (beta=-4.77 mL/year). Similar age-sex interactions were also observed for GMV and WMV. In women, there was a significant interaction between age and menopausal status (P=.007) where the inverse association of age with TBV was steeper in postmenopausal (beta=-5.89 mL/year) than in pre/perimenopausal women (beta=-1.61 mL/year). Similar age-menopause interactions were found in predicting lower GMV and higher WMHV. Differences in the direction of these age-sex and age-menopause interactions were found for regional cortical and subcortical brain volumes. Conclusion(s): Sex and menopause both interact with age during midlife in explaining MRI biomarkers of dementia. Further work is required to understand the mechanisms driving these interactions to develop strategies for delaying dementia.Copyright © 2020 The Author(s) 2020. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Background: ASD and ADHD are prevalent neurodevelopmental disorders that frequently co-occur and have strong evidence for a degree of shared genetic aetiology. Behavioural and neurocognitive heterogeneity in ASD and ADHD has hampered attempts to map the underlying genetics and neurobiology, predict intervention response, and improve diagnostic accuracy. Moving away from categorical conceptualisations of psychopathology to a dimensional approach is anticipated to facilitate discovery of data-driven clusters and enhance our understanding of the neurobiological and genetic aetiology of these conditions. The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project is one of the first large-scale, family-based studies to take a truly transdiagnostic approach to ASD and ADHD. Using a comprehensive phenotyping protocol capturing dimensional traits central to ASD and ADHD, the MAGNET project aims to identify data-driven clusters across ADHD-ASD spectra using deep phenotyping of symptoms and behaviours; investigate the degree of familiality for different dimensional ASD-ADHD phenotypes and clusters; and map the neurocognitive, brain imaging, and genetic correlates of these data-driven symptom-based clusters. Method(s): The MAGNET project will recruit 1,200 families with children who are either typically developing, or who display elevated ASD, ADHD, or ASD-ADHD traits, in addition to affected and unaffected biological siblings of probands, and parents. All children will be comprehensively phenotyped for behavioural symptoms, comorbidities, neurocognitive and neuroimaging traits and genetics. Conclusion(s): The MAGNET project will be the first large-scale family study to take a transdiagnostic approach to ASD-ADHD, utilising deep phenotyping across behavioural, neurocognitive, brain imaging and genetic measures.Copyright © 2021, The Author(s).

Understanding how the living human brain functions requires sophisticated in vivo neuroimaging technologies to characterise the complexity of neuroanatomy, neural function, and brain metabolism. Fluorodeoxyglucose positron emission tomography (FDG-PET) studies of human brain function have historically been limited in their capacity to measure dynamic neural activity. Simultaneous [18F]-FDG-PET and functional magnetic resonance imaging (fMRI) with FDG infusion protocols enable examination of dynamic changes in cerebral glucose metabolism simultaneously with dynamic changes in blood oxygenation. The Monash vis-fPET-fMRI dataset is a simultaneously acquired FDG-fPET/BOLD-fMRI dataset acquired from n=10 healthy adults (18-49yrs) whilst they viewed a flickering checkerboard task. The dataset contains both raw (unprocessed) images and source data organized according to the BIDS specification. The source data includes PET listmode, normalization, sinogram and physiology data. Here, the technical feasibility of using opensource frameworks to reconstruct the PET listmode data is demonstrated. The dataset has significant re-use value for the development of new processing pipelines, signal optimisation methods, and to formulate new hypotheses concerning the relationship between neuronal glucose uptake and cerebral haemodynamics.Copyright © 2021. The Author(s).

Background: Aberrant dopaminergic activity within fronto-striato-thalamic (FST) circuits is thought to contribute to psychosis onset. It remains unclear whether primary abnormality arises from bottom-up subcortical signaling or impaired top-down cortical regulation. We mapped causal interactions (effective connectivity) of dorsal and ventral FST circuits across the psychosis continuum and identified connections associated with striatal dopamine synthesis. Method(s): Spectral dynamic causal modelling (DCM) for resting-state functional magnetic resonance imaging (fMRI) modelled FST effective connectivity in: (1) 46 antipsychotic-naive first-episode psychosis (FEP) patients and 23 controls; (2) 36 established schizophrenia (SCZ) patients and 100 controls; and (3) 33 healthy individuals assessed for psychosis-like experiences (PLEs) with concurrent [18F]DOPA positron emission tomography. DCM estimated FST connectivity in patients and their respective controls, associations with symptom severity in all cohorts, and with striatal [18F]DOPA uptake in the PLE group. Result(s): Patients commonly showed midbrain disinhibition and reduced top-down influence of thalamus on nucleus accumbens. Cortical dysfunction was only apparent in the SCZ group. Positive symptoms were primarily associated with bottom-up connectivity in FEP and a mixture of bottom-up and top-down connectivity in SCZ and PLE groups, with disinhibition of ventromedial prefrontal cortex and extrinsic connectivity of the midbrain implicated across all cohorts. Thalamic and midbrain connectivity were associated with striatal [18F]DOPA uptake. Conclusion(s): We identified a primary role for subcortical dysconnectivity in psychosis, with cortical dysfunction emerging in established illness. Effective connectivity of the midbrain and thalamus are robustly linked to positive symptom severity and striatal dopamine synthesis capacity, suggesting a central role in the emergence of psychotic symptoms. Supported By: Nationa

Background: ASD and ADHD are prevalent neurodevelopmental disorders that frequently co-occur and have strong evidence for a degree of shared genetic aetiology. Behavioural and neurocognitive heterogeneity in ASD and ADHD has hampered attempts to map the underlying genetics and neurobiology, predict intervention response, and improve diagnostic accuracy. Moving away from categorical conceptualisations of psychopathology to a dimensional approach is anticipated to facilitate discovery of data-driven clusters and enhance our understanding of the neurobiological and genetic aetiology of these conditions. The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project is one of the first large-scale, family-based studies to take a truly transdiagnostic approach to ASD and ADHD. Using a comprehensive phenotyping protocol capturing dimensional traits central to ASD and ADHD, the MAGNET project aims to identify data-driven clusters across ADHD-ASD spectra using deep phenotyping of symptoms and behaviours; investigate the degree of familiality for different dimensional ASD-ADHD phenotypes and clusters; and map the neurocognitive, brain imaging, and genetic correlates of these data-driven symptom-based clusters. Method(s): The MAGNET project will recruit 1,200 families with children who are either typically developing, or who display elevated ASD, ADHD, or ASD-ADHD traits, in addition to affected and unaffected biological siblings of probands, and parents. All children will be comprehensively phenotyped for behavioural symptoms, comorbidities, neurocognitive and neuroimaging traits and genetics. Conclusion(s): The MAGNET project will be the first large-scale family study to take a transdiagnostic approach to ASD-ADHD, utilising deep phenotyping across behavioural, neurocognitive, brain imaging and genetic measures.Copyright © 2021, The Author(s).

Changes in brain volume are a common finding in Magnetic Resonance Imaging (MRI) studies of people with psychosis and numerous longitudinal studies suggest that volume deficits progress with illness duration. However, a major unresolved question concerns whether these changes are driven by the underlying illness or represent iatrogenic effects of antipsychotic medication. In this study, 62 antipsychotic-naïve patients with first-episode psychosis (FEP) received either a second-generation antipsychotic (risperidone or paliperidone) or a placebo pill over a treatment period of 6 months. Both FEP groups received intensive psychosocial therapy. A healthy control group (n = 27) was also recruited. Structural MRI scans were obtained at baseline, 3 months and 12 months. Our primary aim was to differentiate illness-related brain volume changes from medication-related changes within the first 3 months of treatment. We secondarily investigated long-term effects at the 12-month timepoint. From baseline to 3 months, we observed a significant group x time interaction in the pallidum (p < 0.05 FWE-corrected), such that patients receiving antipsychotic medication showed increased volume, patients on placebo showed decreased volume, and healthy controls showed no change. Across the entire patient sample, a greater increase in pallidal grey matter volume over 3 months was associated with a greater reduction in symptom severity. Our findings indicate that psychotic illness and antipsychotic exposure exert distinct and spatially distributed effects on brain volume. Our results align with prior work in suggesting that the therapeutic efficacy of antipsychotic medications may be primarily mediated through their effects on the basal ganglia.

Cognitive impairments are a core feature of first-episode psychosis (FEP), arising before illness onset and antipsychotic exposure. Individuals with chronic psychosis experience poorer physical health while taking antipsychotic medication, but health disparities may be evident at FEP onset, prior to antipsychotic exposure. Given the links between cognition and physical health in healthy populations, the aim was to explore whether cognition and physical health are associated in FEP, which could inform early physical health interventions for cognition in FEP. Participants were aged 15 to 25 and included 86 individuals experiencing FEP with limited antipsychotic exposure and duration of untreated psychosis of ≤six months, and 43 age- and sex-matched controls. Individuals with FEP performed significantly poorer than controls in most cognitive domains (Cohen's d = 0.38 to 1.59). Groups were similar in metabolic health measures, excluding a significantly faster heart rate in FEP (d = 0.68). Through hierarchical regression analyses, we found that in the overall sample, BMI was negatively related to current IQ after controlling for education and group (FEP/control). Relationships between BMI and cognition were consistent across the FEP and healthy control groups. In FEP, current IQ and working memory were negatively correlated with lipid profiles. Findings suggest that in FEP, impaired cognition is exhibited earlier than physical health problems, and that compared to controls, similar relationships with cognition are demonstrated. Causal pathways and trajectories of relationships between health and cognition in FEP require investigation, especially as antipsychotic medications are introduced. The findings have implications for cognitive and health interventions.

IMPORTANCE: Altered functional connectivity (FC) is a common finding in resting-state functional magnetic resonance imaging (rs-fMRI) studies of people with psychosis, yet how FC disturbances evolve in the early stages of illness, and how antipsychotic treatment influences these disturbances, remains unknown. OBJECTIVE: To investigate longitudinal FC changes in antipsychotic-naive and antipsychotic-treated patients with first-episode psychosis (FEP). DESIGN, SETTING, AND PARTICIPANTS: This secondary analysis of a triple-blind, randomized clinical trial was conducted over a 5-year recruitment period between April 2008 and December 2016 with 59 antipsychotic-naive patients with FEP receiving either a second-generation antipsychotic or a placebo pill over a treatment period of 6 months. Participants were required to have low suicidality and aggression, to have a duration of untreated psychosis of less than 6 months, and to be living in stable accommodations with social support. Both FEP groups received intensive psychosocial therapy. A healthy control group was also recruited. Participants completed rs-fMRI scans at baseline, 3 months, and 12 months. Data were analyzed from May 2019 to August 2020. INTERVENTIONS: Resting-state functional MRI was used to probe brain FC. Patients received either a second-generation antipsychotic or a matched placebo tablet. Both patient groups received a manualized psychosocial intervention. MAIN OUTCOMES AND MEASURES: The primary outcomes of this analysis were to investigate (1) FC differences between patients and controls at baseline; (2) FC changes in medicated and unmedicated patients between baseline and 3 months; and (3) associations between longitudinal FC changes and clinical outcomes. An additional aim was to investigate long-term FC changes at 12 months after baseline. These outcomes were not preregistered. RESULTS: Data were analyzed for 59 patients (antipsychotic medication plus psychosocial treatment: 28 [47.5%]; mean [SD] a

Brain network hubs are both highly connected and highly inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization are poorly understood. Using diffusion-weighted magnetic resonance imaging in twins, we identify a major role for genes, showing that they preferentially influence connectivity strength between network hubs of the human connectome. Using transcriptomic atlas data, we show that connected hubs demonstrate tight coupling of transcriptional activity related to metabolic and cytoarchitectonic similarity. Finally, comparing over thirteen generative models of network growth, we show that purely stochastic processes cannot explain the precise wiring patterns of hubs, and that model performance can be improved by incorporating genetic constraints. Our findings indicate that genes play a strong and preferential role in shaping the functionally valuable, metabolically costly connections between connectome hubs.

BACKGROUND: ASD and ADHD are prevalent neurodevelopmental disorders that frequently co-occur and have strong evidence for a degree of shared genetic aetiology. Behavioural and neurocognitive heterogeneity in ASD and ADHD has hampered attempts to map the underlying genetics and neurobiology, predict intervention response, and improve diagnostic accuracy. Moving away from categorical conceptualisations of psychopathology to a dimensional approach is anticipated to facilitate discovery of data-driven clusters and enhance our understanding of the neurobiological and genetic aetiology of these conditions. The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project is one of the first large-scale, family-based studies to take a truly transdiagnostic approach to ASD and ADHD. Using a comprehensive phenotyping protocol capturing dimensional traits central to ASD and ADHD, the MAGNET project aims to identify data-driven clusters across ADHD-ASD spectra using deep phenotyping of symptoms and behaviours; investigate the degree of familiality for different dimensional ASD-ADHD phenotypes and clusters; and map the neurocognitive, brain imaging, and genetic correlates of these data-driven symptom-based clusters. METHODS: The MAGNET project will recruit 1,200 families with children who are either typically developing, or who display elevated ASD, ADHD, or ASD-ADHD traits, in addition to affected and unaffected biological siblings of probands, and parents. All children will be comprehensively phenotyped for behavioural symptoms, comorbidities, neurocognitive and neuroimaging traits and genetics. CONCLUSION: The MAGNET project will be the first large-scale family study to take a transdiagnostic approach to ASD-ADHD, utilising deep phenotyping across behavioural, neurocognitive, brain imaging and genetic measures.

Processing speed (PS) impairment is one of the most severe and common cognitive deficits in schizophrenia. Previous studies have reported correlations between PS and white matter diffusion properties, including fractional anisotropy (FA), in several fiber bundles in schizophrenia, suggesting that white matter alterations could underpin decreased PS. In schizophrenia, white matter alterations are most prevalent within inter-hub connections of the rich club. However, the spatial and topological characteristics of this association between PS and FA have not been investigated in patients. In this context, we tested whether structural connections comprising the rich club network would underlie PS impairment in 298 patients with schizophrenia or schizoaffective disorder and 190 healthy controls from the Australian Schizophrenia Research Bank. PS, measured using the digit symbol coding task, was largely (Cohen's d = 1.33) and significantly (P < .001) reduced in the patient group when compared with healthy controls. Significant associations between PS and FA were widespread in the patient group, involving all cerebral lobes. FA was not associated with other cognitive measures of phonological fluency and verbal working memory in patients, suggesting specificity to PS. A topological analysis revealed that despite being spatially widespread, associations between PS and FA were over-represented among connections forming the rich club network. These findings highlight the need to consider brain network topology when investigating high-order cognitive functions that may be spatially distributed among several brain regions. They also reinforce the evidence that brain hubs and their interconnections may be particularly vulnerable parts of the brain in schizophrenia.

Contains fulltext : 237038.pdf (Publisher’s version ) (Open Access)

Contains fulltext : 237038.pdf (Publisher’s version ) (Open Access)

Adoption of Augmented and Virtual Reality (AR and VR) interfaces in the aerospace and defense fields has been inhibited by conspicuous and cumbersome input mechanisms such as gestures and spoken voice recognition. Silent speech interfaces using non-invasive electromyography (EMG) sensors are posited as a means for controlling AR and VR interfaces with potential for inconspicuous and high bandwidth input. Our objective is to develop a silent speech interface that receives input from subvocalizations via skin surface EMG sensors, which is then decoded into commands for controlling a heads-up-display built on a Microsoft HoloLens. EMG sensors are placed on the Digastric, Stylohyoid, Sternohyoid, and Cricothyroid muscles located on the anterior cervical region. The collected data is used to train a convolutional neural network that functions as a classifier, determining the subject’s subvocal input against a word library. The user will equip the wearable interface and use it to silently send commands through subvocalizations to control an AR device. Effectiveness of the wearable interface will be defined by word recognition accuracies in mouthed trials using the current command library. Future work includes expanding the dataset used to train the recognition model and live demonstration in controlling an augmented reality interface.

The COVID-19 pandemic has pushed the world towards contactless technology. With the increase of these tech innovations the advantages have become clear. Using a smart phone to pay for items is convenient and efficient. The “Eagle Wallet” Android application utilizes Radio Frequency ID (RFID)/Near Field Communications (NFC) technology so students, faculty, and staff can use their smart phone to pay for meals. The application allows users to take advantage of the University’s “Dining Dollars” discount of ten percent off posted prices as well as view progress of any meal plans purchased. The user’s login credentials are stored safely in a remote server, and bank information uses bank grade security. The future implementations for the application would be to have the application work with on campus scanners at vending machines, campus merchants, bookstore, and buildings. The less contact between people and public items the less the virus is spread on campus.

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.

The COVID-19 pandemic has pushed the world towards contactless technology. With the increase of these tech innovations the advantages have become clear. Using a smart phone to pay for items is convenient and efficient. The “Eagle Wallet” Android application utilizes Radio Frequency ID (RFID)/Near Field Communications (NFC) technology so students, faculty, and staff can use their smart phone to pay for meals. The application allows users to take advantage of the University’s “Dining Dollars” discount of ten percent off posted prices as well as view progress of any meal plans purchased. The user’s login credentials are stored safely in a remote server, and bank information uses bank grade security. The future implementations for the application would be to have the application work with on campus scanners at vending machines, campus merchants, bookstore, and buildings. The less contact between people and public items the less the virus is spread on campus.

Adoption of Augmented and Virtual Reality (AR and VR) interfaces in the aerospace and defense fields has been inhibited by conspicuous and cumbersome input mechanisms such as gestures and spoken voice recognition. Silent speech interfaces using non-invasive electromyography (EMG) sensors are posited as a means for controlling AR and VR interfaces with potential for inconspicuous and high bandwidth input. Our objective is to develop a silent speech interface that receives input from subvocalizations via skin surface EMG sensors, which is then decoded into commands for controlling a heads-up-display built on a Microsoft HoloLens. EMG sensors are placed on the Digastric, Stylohyoid, Sternohyoid, and Cricothyroid muscles located on the anterior cervical region. The collected data is used to train a convolutional neural network that functions as a classifier, determining the subject’s subvocal input against a word library. The user will equip the wearable interface and use it to silently send commands through subvocalizations to control an AR device. Effectiveness of the wearable interface will be defined by word recognition accuracies in mouthed trials using the current command library. Future work includes expanding the dataset used to train the recognition model and live demonstration in controlling an augmented reality interface.

The present study investigated the utility of fluorine-18 ( 18 F) fluoro-2-deoxy-D-glucose (FDG) positron emission tomography/computed tomography (PET/CT) in assessing bone marrow involvement (BMI) compared with bone marrow biopsy (BMB) in newly diagnosed pediatric Hodgkin lymphoma (HL). 18 F-FDG PET/CT shows high diagnostic performance in evaluating BMI in pediatric HL. BMB should be ideally reserved for patients with doubtful 18 F-FDG PET/CT BMI findings. Introduction: The present study investigated the utility of fluorine-18 ( 18 F) fluoro-2-deoxy-D-glucose ( 18 F-FDG) positron emission tomography/computed tomography (PET/CT) in assessing bone marrow involvement (BMI) compared with bone marrow biopsy (BMB) in newly diagnosed pediatric Hodgkin lymphoma (HL). Patients and Methods: A total of 224 pediatric patients with HL underwent 18 F-FDG PET/CT at staging. BMB or follow-up imaging was used as the standard of reference for the evaluation of BMI. Results: 18 F-FDG PET/CT was negative for BMI in 193 cases. Of the 193 patients, the findings for 16 were originally reported as doubtful and later interpreted as negative for BMI, with negative findings on follow-up imaging and BMB. At BMB, 1 of the 16 patients (6.25%) had BMI. Of the 193 patients, 192 (99.48%) had negative BMB findings. Thus, the 18 F-FDG PET/CT findings were truly negative for 192 patients and falsely negative for 1 patient for BMI. Conclusion: 18 F-FDG PET/CT showed high diagnostic performance in the evaluation of BMI in pediatric HL. Thus, BMB should be ideally reserved for patients presenting with doubtful 18 F-FDG PET/CT findings for BMI.

(Neuron 101, 365–369; February 6, 2019) In the original publication of this NeuroView, the member list for the Australian Brain Alliance was omitted. This has now been corrected online. Neuron apologizes for the error.