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Background Obsessive-compulsive disorder (OCD) is characterized by both internalizing (anxiety) and externalizing (compulsivity) symptoms. Currently, little is known about their interrelationships and their relative contributions to disease heterogeneity. Our goal is to resolve affective and cognitive symptom heterogeneity related to internalized and externalized symptom dimensions by determining subtypes of children with OCD symptoms, and to identify any corresponding neural differences. Methods A total of 1269 children with OCD symptoms screened using the Child Behavior Checklist Obsessive-Compulsive Symptom scale and 3987 matched control subjects were obtained from the Adolescent Brain Cognitive Development (ABCD) Study. Consensus hierarchical clustering was used to cluster children with OCD symptoms into distinct subtypes. Ten neurocognitive task scores and 20 Child Behavior Checklist syndrome scales were used to characterize cognitive/behavioral differences. Gray matter volume, fractional anisotropy of major white matter fiber tracts, and functional connectivity among networks were used in case-control studies. Results We identified two subgroups with contrasting patterns in internalized and externalized dimensions. Group 1 showed compulsive thoughts and repeated acts but relatively low anxiety symptoms, whereas group 2 exhibited higher anxiety and perfectionism and relatively low repetitive behavior. Only group 1 had significant cognitive impairments and gray matter volume reductions in the bilateral inferior parietal lobe, precentral gyrus, and precuneus gyrus, and had white matter tract fractional anisotropy reductions in the corticostriatal fasciculus. Conclusions Children with OCD symptoms are heterogeneous at the level of symptom clustering and its underlying neural basis. Two subgroups represent distinct patterns of externalizing and internalizing symptoms, suggesting that anxiety is not its major predisposing factor. These results may have implications for the nosology and treatment of preteenage OCD.

Background: The widely divergent responsiveness of Parkinson’s disease (PD) patients to levodopa is an important clinical issue because of its relationship with quality of life and disease prognosis. Preliminary animal experiments have suggested that degeneration of the locus coeruleus (LC) attenuates the efficacy of levodopa treatment. Objective: To explore the relationship between LC degeneration and levodopa responsiveness in PD patients in vivo. Methods: Neuromelanin-sensitive magnetic resonance imaging (NM-MRI), a good indicator of LC and substantia nigra (SN) degeneration, and levodopa challenge tests were conducted in 57 PD patients. Responsiveness to levodopa was evaluated by the rates of change of the Unified Parkinson’s Disease Rating Scale Part III score and somatomotor network synchronization calculated from resting-state functional MRI before and after levodopa administration. Next, we assessed the relationship between the contrast-to-noise ratio of LC (CNRLC) and levodopa responsiveness. Multiple linear regression analysis was conducted to rule out the potential influence of SN degeneration on levodopa responsiveness. Results: A significant positive correlation was found between CNRLC and the motor improvement after levodopa administration (R = 0.421, p = 0.004). CNRLC also correlated with improvement in somatomotor network synchronization (R = –0.323, p = 0.029). Furthermore, the relationship between CNRLC and levodopa responsiveness was independent of SN degeneration. Conclusion: LC degeneration might be an essential factor for levodopa resistance. LC evaluation using NM-MRI might be an alternative tool for predicting levodopa responsiveness and for helping to stratify patients into clinical trials aimed at improving the efficacy of levodopa.

The accumulation of vast amounts of multimodal data for the human brain, in both normal and disease conditions, has provided unprecedented opportunities for understanding why and how brain disorders arise. Compared with traditional analyses of single datasets, the integration of multimodal datasets covering different types of data (i.e., genomics, transcriptomics, imaging, etc.) has shed light on the mechanisms underlying brain disorders in greater detail across both the microscopic and macroscopic levels. In this review, we first briefly introduce the popular large datasets for the brain. Then, we discuss in detail how integration of multimodal human brain datasets can reveal the genetic predispositions and the abnormal molecular pathways of brain disorders. Finally, we present an outlook on how future data integration efforts may advance the diagnosis and treatment of brain disorders.

Children’s behavioral problems have been associated with their family environments. Here, we investigate whether specific features of brain structures could relate to this link. Using structural magnetic resonance imaging of 8756 children aged 9-11 from the Adolescent Brain Cognitive Developmental study, we show that high family conflict and low parental monitoring scores are associated with children’s behavioral problems, as well as with smaller cortical areas of the orbitofrontal cortex, anterior cingulate cortex, and middle temporal gyrus. A longitudinal analysis indicates that psychiatric problems scores are associated with increased family conflict and decreased parental monitoring 1 year later, and mediate associations between the reduced cortical areas and family conflict, and parental monitoring scores. These results emphasize the relationships between the brain structure of children, their family environments, and their behavioral problems., Child behavior has been associated with parenting behavior. Here, the authors investigate associations between child behavior, parental behavior, and structural MRI using the Adolescent Brain Cognitive Developmental (ABCD) study dataset.

Funder: Program of Introducing Talents of Discipline to Universities, Plan 111 (No. B18015). National Key R&D Program of China (No. 2018YFC1312900)., Emerging evidence shows that the coronavirus disease 2019 (COVID-19) pandemic is negatively affecting mental health around the globe. Interventions to alleviate the psychological impact of the pandemic are urgently needed. Whether mindfulness practice may protect against the harmful emotional effects of a pandemic crisis remains hitherto unknown. We investigated the influence of mindfulness training on mental health during the COVID-19 outbreak in China. We hypothesized that mindfulness practitioners might manifest less pandemic-related distress, depression, anxiety, and stress than non-practitioners and that more frequent practice would be associated with an improvement in mental health during the pandemic. Therefore, we assessed pandemic-related distress and symptoms of depression, anxiety, and stress, as well as the frequency of meditation practice at the peak of new infections (Feb 4–5; N = 673) and three weeks later (Feb 29–30; N = 521) in mindfulness practitioners via online questionnaires. Self-reported symptoms were also collected from non-practitioners at peak time only (N = 1550). We found lower scores of pandemic-related distress in mindfulness practitioners compared to non-practitioners. In general, older participants showed fewer symptoms of depression and anxiety. In younger practitioners, pandemic-related distress decreased from peak to follow-up. Importantly, increased mindfulness training during the preceding two weeks was associated with lower scores of depression and anxiety at both assessments. Likewise, practice frequency predicted individual improvement in scores of depression, anxiety, and stress at follow-up. Our results indicate that mindfulness meditation might be a viable low-cost intervention to mitigate the psychological impact of the COVID-19 crisis and future pandemics.

We describe advances in the understanding of brain dynamics that are important for understanding the operation of the cerebral cortex in health and disease. Peaks in the resting state fMRI BOLD signal in many different brain areas can become synchronized. In data from 1,017 participants from the Human Connectome Project, we show that early visual and connected areas have the highest probability of synchronized peaks. We show that these cortical areas also have low temporal variability of their functional connectivity. We show that there is an approximately reciprocal relation between the probability that a brain region will be involved in synchronized peaks and the temporal variability of the connectivity of a brain region. We show that a high probability of synchronized peaks and a low temporal variability of the connectivity of cortical areas are related to high mean functional connectivity, and provide an account of how these dynamics with some of the properties of avalanches arise. These discoveries help to advance our understanding of cortical operation in health, and in some mental disorders including schizophrenia., Peaks in the resting state BOLD signal of different brain areas can become synchronized and the size of these synchronized events follows a power law distribution, consistent with avalanche dynamics that are found when a system is close to a critical point. We show that a high probability of synchronization events and a low temporal variability of the connectivity of cortical areas are related to high mean functional connectivity, and provide an account of how these dynamics arise, and where they start in the brain.

Psychological androgyny has long been associated with greater cognitive flexibility, adaptive behavior, and better mental health, but whether a similar concept can be defined using neural features remains unknown. Using the neuroimaging data from 9620 participants, we found that global functional connectivity was stronger in the male brain before middle age but became weaker after that, when compared with the female brain, after systematic testing of potentially confounding effects. We defined a brain gender continuum by estimating the likelihood of an observed functional connectivity matrix to represent a male brain. We found that participants mapped at the center of this continuum had fewer internalizing symptoms compared with those at the 2 extreme ends. These findings suggest a novel hypothesis proposing that there exists a neuroimaging concept of androgyny using the brain gender continuum, which may be associated with better mental health in a similar way to psychological androgyny.

Objective: The dual-pathway model has been proposed to explain the heterogeneity in symptoms of attention deficit hyperactivity disorder (ADHD) by two independent psychological pathways based on distinct brain circuits. The authors sought to test whether the hypothesized cognitive and motivational pathways have separable neural correlates. Methods: In a longitudinal community-based cohort of 1,963 adolescents, the neuroanatomical correlates of ADHD were identified by a voxel-wise association analysis and then validated using an independent clinical sample (99 never-medicated patients with ADHD, 56 medicated patients with ADHD, and 267 healthy control subjects). The cognitive and motivational pathways were assessed by neuropsychological tests of working memory, intrasubject variability, stop-signal reaction time, and delay discounting. The associations were tested between the identified neuroanatomical correlates and both ADHD symptoms 2 years later and the polygenic risk score for ADHD. Results: Gray matter volumes of both a prefrontal cluster and a posterior occipital cluster were negatively associated with inattention. Compared with healthy control subjects, never-medicated patients, but not medicated patients, had significantly lower gray matter volumes in these two clusters. Working memory and intrasubject variability were associated with the posterior occipital cluster, and delay discounting was independently associated with both clusters. The baseline gray matter volume of the posterior occipital cluster predicted the inattention symptoms in a 2-year follow-up and was associated with the genetic risk for ADHD. Conclusions: The dual-pathway model has both shared and separable neuroanatomical correlates, and the shared correlate in the occipital cortex has the potential to serve as an imaging trait marker of ADHD, especially the inattention symptom domain.

Reinforcement-related cognitive processes, such as reward processing, inhibitory control and social–emotional regulation are critical components of externalising and internalising behaviours. It is unclear to what extent the deficit in each of these processes contributes to individual behavioural symptoms, how their neural substrates give rise to distinct behavioural outcomes and whether neural activation profiles across different reinforcement-related processes might differentiate individual behaviours. We created a statistical framework that enabled us to directly compare functional brain activation during reward anticipation, motor inhibition and viewing emotional faces in the European IMAGEN cohort of 2,000 14-year-old adolescents. We observe significant correlations and modulation of reward anticipation and motor inhibition networks in hyperactivity, impulsivity, inattentive behaviour and conduct symptoms, and we describe neural signatures across cognitive tasks that differentiate these behaviours. We thus characterise shared and distinct functional brain activation patterns underling different externalising symptoms and identify neural stratification markers, while accounting for clinically observed comorbidity. On the basis of the IMAGEN database of 2,000 Caucasian adolescents, Jia et al identify neural patterns of activity during reward anticipation and motor inhibition associated with different externalising symptoms for ADHD and conduct problems.

Parcellation of the orbitofrontal cortex, anterior cingulate cortex, and inferior frontal gyrus based on their functional connectivity with the whole brain in resting state fMRI with 654 participants was performed to investigate how these regions with different functions in reward, emotion and their disorders are functionally connected to each other and to the whole brain. The human medial and lateral orbitofrontal cortex, the ventromedial prefrontal cortex, the anterior cingulate cortex, and the right and left inferior frontal gyrus have different functional connectivity with other brain areas and with each other; and each of these regions has several parcels with different functional connectivity with other brain areas. In terms of functional connectivity, the lateral orbitofrontal cortex extends especially on the right into the orbital part of the inferior frontal gyrus and provides connectivity with premotor cortical areas. The orbitofrontal cortex, especially the lateral orbitofrontal cortex, has connectivity not only with language-related areas in the inferior frontal gyrus (Broca's area), but also with the angular and supramarginal gyri. In this context, whereas the connectivity of the orbitofrontal cortex, ventromedial prefrontal cortex, and anterior cingulate cortex is symmetrical, the connectivity of the inferior frontal gyrus triangular and opercular parts is asymmetrical for the right and the left hemispheres. These findings have implications for understanding the neural bases of human emotion and decision-making, and for their disorders including depression.

The neurobiological heterogeneity of schizophrenia is widely accepted, but it is unclear how mechanistic differences converge to produce the observed phenotype. Establishing a pathophysiological model that accounts for both neurobiological heterogeneity and phenotypic similarity is essential to inform stratified treatment approaches. In this cross-sectional diffusion tensor imaging study, we recruited 77 healthy controls, and 70 patients with DSM-IV diagnosis of schizophrenia. We first confirmed the heterogeneity in structural connectivity by showing a reduced between-individual similarity of the structural connectivity in patients compared to healthy controls. Second, at a system level, we found the diversity of the topographic distribution of the strength of structural connectivity was significantly reduced in patients (P = 7.21 × 10 , T = 5.19 [95% CI: 3.37–7.52], Cohen's d = 0.91), and this affected 65 of the 90 brain regions examined (False Discovery Rate

China accounts for 17% of the global disease burden attributable to mental, neurological and substance use disorders. As a country undergoing profound societal change, China faces growing challenges to reduce the disease burden caused by psychiatric disorders. In this review, we aim to present an overview of progress in neuroscience research and clinical services for psychiatric disorders in China during the past three decades, analysing contributing factors and potential challenges to the field development. We first review studies in the epidemiological, genetic and neuroimaging fields as examples to illustrate a growing contribution of studies from China to the neuroscience research. Next, we introduce large-scale, open-access imaging genetic cohorts and recently initiated brain banks in China as platforms to study healthy brain functions and brain disorders. Then, we show progress in clinical services, including an integration of hospital and community-based healthcare systems and early intervention schemes. We finally discuss opportunities and existing challenges: achievements in research and clinical services are indispensable to the growing funding investment and continued engagement in international collaborations. The unique aspect of traditional Chinese medicine may provide insights to develop a novel treatment for psychiatric disorders. Yet obstacles still remain to promote research quality and to provide ubiquitous clinical services to vulnerable populations. Taken together, we expect to see a sustained advancement in psychiatric research and healthcare system in China. These achievements will contribute to the global efforts to realize good physical, mental and social well-being for all individuals.

Age-related changes in the brain are associated with a decline in functional flexibility. Intrinsic functional flexibility is evident in the brain's dynamic ability to switch between alternative spatiotemporal states during resting state. However, the relationship between brain connectivity states, associated psychological functions during resting state, and the changes in normal aging remain poorly understood. In this study, we analyzed resting-state functional magnetic resonance imaging (rsfMRI) data from the Human Connectome Project (HCP; N = 812) and the UK Biobank (UKB; N = 6,716). Using signed community clustering to identify distinct states of dynamic functional connectivity, and text-mining of a large existing literature for functional annotation of each state, our findings from the HCP dataset indicated that the resting brain spontaneously transitions between three functionally specialized states: sensory, somatomotor, and internal mentation networks. The occurrence, transition-rate, and persistence-time parameters for each state were correlated with behavioural scores using canonical correlation analysis. We estimated the same brain states and parameters in the UKB dataset, subdivided into three distinct age ranges: 50–55, 56–67, and 68–78 years. We found that the internal mentation network was more frequently expressed in people aged 71 and older, whereas people younger than 55 more frequently expressed sensory and somatomotor networks. Furthermore, analysis of the functional entropy — a measure of uncertainty of functional connectivity — also supported this finding across the three age ranges. Our study demonstrates that dynamic functional connectivity analysis can expose the time-varying patterns of transition between functionally specialized brain states, which are strongly tied to increasing age.

Understanding a neuron's input-output relationship is a longstanding challenge. Arguably, these signalling dynamics can be better understood if studied at three levels of analysis: computational, algorithmic and implementational (Marr, 1982). But it is difficult to integrate such analyses into a single platform that can realistically simulate neural information processing. Multiscale dynamical "whole-cell" modelling, a recent systems biology approach, makes this possible. Dynamical "whole-cell" models are computational models that aim to account for the integrated function of numerous genes or molecules to behave like virtual cells in silico. However, because constructing such models is laborious, only a couple of examples have emerged since the first one, built for Mycoplasma genitalium bacterium, was reported in 2012. Here, we review dynamic "whole-cell" neuron models for fly photoreceptors and how these have been used to study neural information processing. Specifically, we review how the models have helped uncover the mechanisms and evolutionary rules of quantal light information sampling and integration, which underlie light adaptation and further improve our understanding of insect vision. [Abstract copyright: Copyright © 2021. Published by Elsevier B.V.]

The aim was to go beyond functional connectivity, by measuring in the first large-scale study differences in effective, that is directed, connectivity between brain areas in autism compared to controls. Resting-state functional magnetic resonance imaging was analyzed from the Autism Brain Imaging Data Exchange (ABIDE) data set in 394 people with autism spectrum disorder and 473 controls, and effective connectivity (EC) was measured between 94 brain areas. First, in autism, the middle temporal gyrus and other temporal areas had lower effective connectivities to the precuneus and cuneus, and these were correlated with the Autism Diagnostic Observational Schedule total, communication, and social scores. This lower EC from areas implicated in face expression analysis and theory of mind to the precuneus and cuneus implicated in the sense of self may relate to the poor understanding of the implications of face expression inputs for oneself in autism, and to the reduced theory of mind. Second, the hippocampus and amygdala had higher EC to the middle temporal gyrus in autism, and these are thought to be back projections based on anatomical evidence and are weaker than in the other direction. This may be related to increased retrieval of recent and emotional memories in autism. Third, some prefrontal cortex areas had higher EC with each other and with the precuneus and cuneus. Fourth, there was decreased EC from the temporal pole to the ventromedial prefrontal cortex, and there was evidence for lower activity in the ventromedial prefrontal cortex, a brain area implicated in emotion-related decision-making. Autism Res 2019, 00: 1-13. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: To understand autism spectrum disorders better, it may be helpful to understand whether brain systems cause effects on each other differently in people with autism. In this first large-scale neuroimaging investigation of effective connectivity in people with autism, it is shown that parts of the temporal lobe involved in facial expression identification and theory of mind have weaker effects on the precuneus and cuneus implicated in the sense of self. This may relate to the poor understanding of the implications of face expression inputs for oneself in autism, and to the reduced theory of mind. [Abstract copyright: © 2019 International Society for Autism Research, Wiley Periodicals, Inc.]

Motivation Advances in neuroimaging and sequencing techniques provide an unprecedented opportunity to map the function of brain regions and identify the roots of psychiatric diseases. However, the results from most neuroimaging studies, i.e. activated clusters/regions or functional connectivities between brain regions, frequently cannot be conveniently and systematically interpreted, rendering the biological meaning unclear. Results We describe a brain annotation toolbox that generates functional and genetic annotations for neuroimaging results. The voxel-level functional description from the Neurosynth database and gene expression profile from the Allen Human Brain Atlas are used to generate functional/genetic information for region-level neuroimaging results. The validity of the approach is demonstrated by showing that the functional and genetic annotations for specific brain regions are consistent with each other; and further the region by region functional similarity network and genetic similarity network are highly correlated for major brain atlases. One application of brain annotation toolbox is to help provide functional/genetic annotations for newly discovered regions with unknown functions, e.g. the 97 new regions identified in the Human Connectome Project. Importantly, this toolbox can help understand differences between psychiatric patients and controls, and this is demonstrated using schizophrenia and autism data, for which the functional and genetic annotations for the neuroimaging changes in patients are consistent with each other and help interpret the results. Availability and implementation BAT is implemented as a free and open-source MATLAB toolbox and is publicly available at http://123.56.224.61:1313/post/bat. Supplementary information Supplementary data are available at Bioinformatics online.

We describe an approach to multivariate analysis, termed structured kernel principal component regression (sKPCR), to identify associations in voxel-level connectomes using resting-state functional magnetic resonance imaging (rsfMRI) data. This powerful and computationally efficient multivariate method can identify voxel-phenotype associations based on the whole-brain connectivity pattern of voxels, and it can detect linear and non-linear signals in both volume-based and surface-based rsfMRI data. For each voxel, sKPCR first extracts low-dimensional signals from the spatially smoothed connectivities by structured kernel principal component analysis, and then tests the voxel-phenotype associations by an adaptive regression model. The method's power is derived from appropriately modelling the spatial structure of the data when performing dimension reduction, and then adaptively choosing an optimal dimension for association testing using the adaptive regression strategy. Simulations based on real connectome data have shown that sKPCR can accurately control the false-positive rate and that it is more powerful than many state-of-the-art approaches, such as the connectivity-wise generalized linear model (GLM) approach, multivariate distance matrix regression (MDMR), adaptive sum of powered score (aSPU) test, and least-square kernel machine (LSKM). Moreover, since sKPCR can reduce the computational cost of non-parametric permutation tests, its computation speed is much faster. To demonstrate the utility of sKPCR for real data analysis, we have also compared sKPCR with the above methods based on the identification of voxel-wise differences between schizophrenic patients and healthy controls in four independent rsfMRI datasets. The results showed that sKPCR had better between-sites reproducibility and a larger proportion of overlap with existing schizophrenia meta-analysis findings. Code for our approach can be downloaded from https://github.com/weikanggong/sKPCR. [Abstract copyright: Copyright © 2018 Elsevier Inc. All rights reserved.]

Background\ud \ud The precuneus has connectivity with brain systems implicated in depression. \ud \ud Methods. \ud \ud We performed the first fully voxel - level resting state functional - connectivity neuroimaging analysis of depression of the precuneus, with 282 patients with major depressive disorder and 254 controls. \ud \ud Results\ud \ud In 125 unmedicated patients, voxels in the precuneus had significantly increased functional connectivity with the lateral orbito frontal cortex , a region implicated in non - reward and that is thereby implicated in depression. Functional connectivity was also increased in depression between the precuneus and dorsolateral prefrontal cortex; temporal cortex; and angular and supramarginal areas. In patients receiving medication, the functional connectivity between the lateral orbitofrontal cortex and precuneus was de creased back towards that in the controls. In the 254 controls, parcellation revealed superior anterior, superior posterior, and inferior subdivisions, with the inferior subdivision having high connectivity with the posterior cingulate cortex, parahippocampal gyrus, angular gyrus, and prefrontal cortex. It was the ventral subdivision of the precuneus that had increased connectivity in depression with the later al orbitofrontal cortex and adjoining inferior frontal gyrus. \ud \ud Conclusions \ud \ud The findings support the theory that the system in the lateral orbitofron tal cortex implicated in responding to not receiving expected rewards has increased effects on areas in which the self is represented, the precuneus. This may result in low self - esteem in depression. The increased connectivity of the precuneus with the pre frontal cortex short - term memory system may contribute to the rumination about low self - esteem in depression. These findings provide evidence that a target to ameliorate depression is the lateral orbitofrontal cortex. \ud

Funder: Shanghai Municipal Commission of Health and Family Planning Shanghai Shenkang Hospital Development Center Shanghai Municipal Education Commission National Natural Science Foundation of China Shanghai Committee of Science and Technology Xinhua Hospital of Shanghai Jiao Tong University School of Medicine Guangdong Key Project in "Development of new tools for diagnosis and treatment of Autism ", Funder: Shanghai Municipal Commission of Health and Family Planning Shanghai Municipal Education Commission National Natural Science Foundation of China the National Key Research and Development Program of China ZJ Lab, Funder: National Human Genetic Resources Sharing Service Platform 111 Project ZJ Lab, Funder: National Natural Science Foundation of China ZJ Lab, Bumetanide has been reported to alter synaptic excitation–inhibition (E-I) balance by potentiating the action of γ-aminobutyric acid (GABA), thereby attenuating the severity of autism spectrum disorder (ASD) in animal models. However, clinical evidence of its efficacy in young patients with ASD is limited. This was investigated in the present clinical trial of 83 patients, randomised to the bumetanide group (bumetanide treatment, 0.5 mg twice daily) or the control group (no bumetanide treatment). Primary [Children Autism Rating Scale (CARS)], secondary [Clinical Global Impressions (CGI)], and exploratory [inhibitory (γ-aminobutyric acid, GABA) and excitatory (glutamate, Glx) neurotransmitter concentrations measured in the insular cortex (IC) and visual cortex (VC) by magnetic resonance spectroscopy (MRS)] outcome measures were evaluated at baseline and at the 3-month follow-up. Side effects were monitored throughout the treatment course. Compared with the control group, the bumetanide group showed significant reduction in symptom severity, as indicated by both total CARS score and number of items assigned a score ≥ 3. The improvement in clinical symptoms was confirmed by CGI. GABA/Glx ratio in both the IC and VC decreased more rapidly over the 3-month period in the bumetanide group than that in the control group. This decrease in the IC was associated with the symptom improvement in the bumetanide group. Our study confirmed the clinical efficacy of bumetanide on alleviating the core symptoms of ASD in young children and it is the first demonstration that the improvement is associated with reduction in GABA/Glx ratios. This study suggests that the GABA/Glx ratio measured by MRS may provide a neuroimaging biomarker for assessing treatment efficacy for bumetanide.

We describe advances in the understanding of brain dynamics that are important for understanding the operation of the cerebral cortex in health and disease. In data from 1017 participants from the Human Connectome Project, we show that early visual and connected areas have low temporal variability of their functional connectivity. We show that a low temporal variability of the connectivity of cortical areas is related to high mean functional connectivity between those areas, and provide an account of how these dynamics arise. We then investigate how these concepts help to understand brain dynamics in mental disorders. We find that in both first episode and long-term schizophrenia, reduced functional connectivity of early visual and related temporal cortex areas is associated with increased temporal variability of the functional connectivity, consistent with decreased stability of attractor networks related to sensory processing. In ADHD, we find these functional connectivities are increased and their temporal variability is decreased, and relate this to increased engagement with visual sensory input as manifest in high screen time usage in ADHD. We further show that these differences in the dynamics of the cortex in schizophrenia, and ADHD can be related to differences in the functional connectivity of the specific sensory vs. association thalamic nuclei. These discoveries help to advance our understanding of cortical operation in health, and in some mental disorders.

Contains fulltext : 243961.pdf (Publisher’s version ) (Closed access) Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine.

The human cerebral cortex undergoes profound structural and functional dynamic variations across the lifespan, whereas the underlying molecular mechanisms remain unclear. Here, with a novel method transcriptome-connectome correlation analysis (TCA), which integrates the brain functional magnetic resonance images and region-specific transcriptomes, we identify age-specific cortex (ASC) gene signatures for adolescence, early adulthood and late adulthood. The ASC gene signatures are significantly correlated with the cortical thickness (P-value Availability: All scripts are written in R. Scripts for the TCA method and related statistics result can be freely accessed at https://github.com/Soulnature/TCA. Additional data related to this paper may be requested from the authors.

Humans and other primates can reverse their choice of stimuli in one trial when the rewards delivered by the stimuli change or reverse. Rapidly changing our behavior when the rewards change is important for many types of behavior, including emotional and social behavior. It is shown in a one-trial rule-based Go-NoGo deterministic visual discrimination reversal task to obtain points, that the human right lateral orbitofrontal cortex and adjoining inferior frontal gyrus is activated on reversal trials, when an expected reward is not obtained, and the non-reward allows the human to switch choices based on a rule. This reward reversal goes beyond model-free reinforcement learning. This functionality of the right lateral orbitofrontal cortex shown here in very rapid, one-trial, rule-based changes in human behavior when a reward is not received is related to the emotional and social changes that follow orbitofrontal cortex damage, and to depression in which this non-reward system is oversensitive and over-connected.

The orbitofrontal cortex in primates including humans is the key brain area in emotion, and in the representation of reward value and in non-reward, that is not obtaining an expected reward. Cortical processing before the orbitofrontal cortex is about the identity of stimuli, i.e. ‘what’ is present, and not about reward value. There is evidence that this holds for taste, visual, somatosensory and olfactory stimuli. The human medial orbitofrontal cortex represents many different types of reward, and the lateral orbitofrontal cortex represents non-reward and punishment. Not obtaining an expected reward can lead to sadness, and feeling depressed. The concept is advanced that an important brain region in depression is the orbitofrontal cortex, with depression related to over-responsiveness and over-connectedness of the non-reward-related lateral orbitofrontal cortex, and to under-responsiveness and under-connectivity of the reward-related medial orbitofrontal cortex. Evidence from large-scale voxel-level studies and supported by an activation study is described that provides support for this hypothesis. Increased functional connectivity of the lateral orbitofrontal cortex with brain areas that include the precuneus, posterior cingulate cortex and angular gyrus is found in patients with depression and is reduced towards the levels in controls when treated with medication. Decreased functional connectivity of the medial orbitofrontal cortex with medial temporal lobe areas involved in memory is found in patients with depression. Some treatments for depression may act by reducing activity or connectivity of the lateral orbitofrontal cortex. New treatments that increase the activity or connectivity of the medial orbitofrontal cortex may be useful for depression. These concepts, and that of increased activity in non-reward attractor networks, have potential for advancing our understanding and treatment of depression. The focus is on the orbitofrontal cortex in primates including humans, because of differences of operation of the orbitofrontal cortex, and indeed of reward systems, in rodents. Finally, the hypothesis is developed that the orbitofrontal cortex has a special role in emotion and decision-making in part because as a cortical area it can implement attractor networks useful in maintaining reward and emotional states online, and in decision-making., The orbitofrontal cortex is involved in emotion, reward value and reward-related decision-making. Rolls et al. describe how it implements these functions, and the effects of damage. In depression, the lateral orbitofrontal cortex has increased functional connectivity and sensitivity to non-reward; and the medial orbitofrontal cortex has decreased connectivity and sensitivity to reward., Graphical Abstract Graphical Abstract

Funder: Zhangjiang Lab, Funder: the Shanghai AI Platform for Diagnosis and Treatment of Brain Diseases, Funder: the Project of Zhangjiang Hi-Tech District Management Committee, Funder: Shanghai (grant 2016-17), Funder: BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics); Grant(s): MR/N027558/1, Funder: Associazione Emma e Ernesto Rulfo per la Genetica Medica (IT), Funder: the Swedish Research Council FORMAS, Funder: the Medical Research Council, Funder: the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, Funder: the Human Brain Project (HBP SGA 2), Funder: the Fondation de France, the Fondation pour la Recherche Médicale, Funder: the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Funder: Paris Sud University IDEX 2012, Funder: cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence, Background: Childhood trauma increases the risk for adult obesity through multiple complex pathways, and the neural substrates are yet to be determined. Methods: Participants from three population-based neuroimaging cohorts, including the IMAGEN cohort, the UK Biobank (UKB), and the Human Connectome Project (HCP), were recruited. Voxel-based morphometry analysis of both childhood trauma and body mass index (BMI) was performed in the longitudinal IMAGEN cohort; validation of the findings was performed in the UKB. White-matter connectivity analysis was conducted to study the structural connectivity between the identified brain region and subdivisions of the hypothalamus in the HCP. Results: In IMAGEN, a smaller frontopolar cortex (FPC) was associated with both childhood abuse (CA) (β = − .568, 95%CI − .942 to − .194; p = .003) and higher BMI (β = − .086, 95%CI − .128 to − .043; p < .001) in male participants, and these findings were validated in UKB. Across seven data collection sites, a stronger negative CA-FPC association was correlated with a higher positive CA-BMI association (β = − 1.033, 95%CI − 1.762 to − .305; p = .015). Using 7-T diffusion tensor imaging data (n = 156), we found that FPC was the third most connected cortical area with the hypothalamus, especially the lateral hypothalamus. A smaller FPC at age 14 contributed to higher BMI at age 19 in those male participants with a history of CA, and the CA-FPC interaction enabled a model at age 14 to account for some future weight gain during a 5-year follow-up (variance explained 5.8%). Conclusions: The findings highlight that a malfunctioning, top-down cognitive or behavioral control system, independent of genetic predisposition, putatively contributes to excessive weight gain in a particularly vulnerable population, and may inform treatment approaches.

ObjectiveTo identify biotypes in patients with newly diagnosed Parkinson disease (PD) and to test whether these biotypes could explain interindividual differences in longitudinal progression.MethodsIn this longitudinal analysis, we use a data-driven approach clustering PD patients from the Parkinson's Progression Markers Initiative (n = 314, age 61.0 ± 9.5, years 34.1% female, 5 years of follow-up). Voxel-level neuroanatomic features were estimated with deformation-based morphometry (DBM) of T1-weighted MRI. Voxels with deformation values that were significantly correlated (p < 0.01) with clinical scores (Movement Disorder Society–sponsored revision of the Unified Parkinson’s Disease Rating Scale Parts I–III and total score, tremor score, and postural instability and gait difficulty score) at baseline were selected. Then, these neuroanatomic features were subjected to hierarchical cluster analysis. Changes in the longitudinal progression and neuroanatomic pattern were compared between different biotypes.ResultsTwo neuroanatomic biotypes were identified: biotype 1 (n = 114) with subcortical brain volumes smaller than heathy controls and biotype 2 (n = 200) with subcortical brain volumes larger than heathy controls. Biotype 1 had more severe motor impairment, autonomic dysfunction, and much worse REM sleep behavior disorder than biotype 2 at baseline. Although disease durations at the initial visit and follow-up were similar between biotypes, patients with PD with smaller subcortical brain volume had poorer prognosis, with more rapid decline in several clinical domains and in dopamine functional neuroimaging over an average of 5 years.ConclusionRobust neuroanatomic biotypes exist in PD with distinct clinical and neuroanatomic patterns. These biotypes can be detected at diagnosis and predict the course of longitudinal progression, which should benefit trial design and evaluation.

Background Two studies have suggested that severe prolonged nausea and vomiting during pregnancy is associated with emotional and behavioral problems in offspring, with smaller sample size and short-term follow-up. Moreover, little information is available on the role of the brain structure in the associations. Methods In a US-based cohort, the association was investigated between severe prolonged nausea and vomiting in pregnancy (extending after the second trimester and termed SNVP), psychiatric and cognitive problems, and brain morphology, from the Adolescent Brain Cognitive Development (ABCD) study, from 10,710 children aged 9–11 years. We validated the emotional including psychiatric findings using the Danish National Cohort Study with 2,092,897 participants. Results SNVP was significantly associated with emotional and psychiatric problems (t = 8.89, Cohen’s d = 0.172, p = 6.9 × 10−19) and reduced global cognitive performance (t = − 4.34, d = − 0.085, p = 1.4 × 10−5) in children. SNVP was associated with low cortical area and volume, especially in the cingulate cortex, precuneus, and superior medial prefrontal cortex. These lower cortical areas and volumes significantly mediated the relation between SNVP and the psychiatric and cognitive problems in children. In the Danish National Cohort, severe nausea and vomiting in pregnancy were significantly associated with increased risks of behavioral and emotional disorders in children (hazard ratio, 1.24; 95% confidence interval, 1.16–1.33). Conclusions SNVP is strongly associated with psychiatric and cognitive problems in children, with mediation by brain structure. These associations highlight the clinical importance and potential benefits of the treatment of SNVP, which could reduce the risk of psychiatric disorder in the next generation.

Background:\ud The objective was a large-scale analysis of the relation between hypertension, memory problems, and brain function.\ud \ud Methods:\ud The study design was to measure the association between a history of hypertension, and the functional connectivity between 94 brain regions, and prospective and numeric memory, in 19,507 participants from the UK Biobank, with cross-validation in 1,002 participants in the Human Connectome Project, and 13,441 individuals in the second release of the UK Biobank. A history of hypertension was measured by whether individuals were admitted to hospital for the treatment of hypertension, with the control group admissions for other reasons.\ud \ud Findings:\ud A history of hypertension was associated with reduced functional connectivity of the hippocampus, and with reduced prospective memory score (FDR correction p

Schizophrenia is a neurocognitive illness of synaptic and brain network-level dysconnectivity that often reaches a persistent chronic stage in many patients. Subtle language deficits are a core feature even in the early stages of schizophrenia. However, the primacy of language network dysconnectivity and language-related genetic variants in the observed phenotype in early stages of illness remains unclear. This study used two independent schizophrenia dataset consisting of 138 and 53 drug-naïve first-episode schizophrenia (FES) patients, and 112 and 56 healthy controls, respectively. A brain-wide voxel-level functional connectivity analysis was conducted to investigate functional dysconnectivity and its relationship with illness duration. We also explored the association between critical language-related genetic (such as FOXP2) mutations and the altered functional connectivity in patients. We found elevated functional connectivity involving Broca’s area, thalamus and temporal cortex that were replicated in two FES datasets. In particular, Broca’s area - anterior cingulate cortex dysconnectivity was more pronounced for patients with shorter illness duration, while thalamic dysconnectivity was predominant in those with longer illness duration. Polygenic risk scores obtained from FOXP2-related genes were strongly associated with functional dysconnectivity identified in patients with shorter illness duration. Our results highlight the criticality of language network dysconnectivity, involving the Broca’s area in early stages of schizophrenia, and the role of language-related genes in this aberration, providing both imaging and genetic evidence for the association between schizophrenia and the determinants of language.

Sensation-seeking is a multifaceted personality trait with components that include experience-seeking, thrill and adventure seeking, disinhibition, and susceptibility to boredom, and is an aspect of impulsiveness. We analysed brain regions involved in sensation-seeking in a large-scale study with 414 participants and showed that the sensation-seeking score could be optimally predicted from the functional connectivity with typically (in different participants) 18 links between brain areas (measured in the resting state with fMRI) with correlation r ​= ​0.34 (p ​= ​7.3 ​× ​10−13) between the predicted and actual sensation-seeking score across all participants. Interestingly, 8 of the 11 links that were common for all participants were between the medial orbitofrontal cortex and the anterior cingulate cortex and yielded a prediction accuracy r ​= ​0.30 (p ​= ​4.8 ​× ​10−10). We propose that this important aspect of personality, sensation-seeking, reflects a strong effect of reward (in which the medial orbitofrontal cortex is implicated) on promoting actions to obtain rewards (in which the anterior cingulate cortex is implicated). Risk-taking was found to have a moderate correlation with sensation-seeking (r ​= ​0.49, p ​= ​3.9 ​× ​10−26), and three of these functional connectivities were significantly correlated (p ​< ​0.05) with the overall risk-taking score. This discovery helps to show how the medial orbitofrontal and anterior cingulate cortices influence behaviour and personality, and indicate that sensation-seeking can involve in part the medial orbitofrontal cortex reward system, which can thereby become associated with risk-taking and a type of impulsiveness.

Neuroimaging data from 1890 adolescents implicated an orbitofronto-amygdalo-periaqueductal gray network in early alcohol abuse., Prompted by recent evidence of neural circuitry in rodent models, functional magnetic resonance imaging and functional connectivity analyses were conducted for a large adolescent population at two ages, together with alcohol abuse measures, to characterize a neural network that may underlie the onset of alcoholism. A network centered on the medial orbitofrontal cortex (mOFC), as well as including the dorsal periaqueductal gray (dPAG), central nucleus of the amygdala, and nucleus accumbens, was identified, consistent with the rodent models, with evidence of both inhibitory and excitatory coregulation by the mOFC over the dPAG. Furthermore, significant relationships were detected between raised baseline excitatory coregulation in this network and impulsivity measures, supporting a role for negative urgency in alcohol dependence.

Object detection from 3D point clouds remains a challenging task, though recent studies pushed the envelope with the deep learning techniques. Owing to the severe spatial occlusion and inherent variance of point density with the distance to sensors, appearance of a same object varies a lot in point cloud data. Designing robust feature representation against such appearance changes is hence the key issue in a 3D object detection method. In this paper, we innovatively propose a domain adaptation like approach to enhance the robustness of the feature representation. More specifically, we bridge the gap between the perceptual domain where the feature comes from a real scene and the conceptual domain where the feature is extracted from an augmented scene consisting of non-occlusion point cloud rich of detailed information. This domain adaptation approach mimics the functionality of the human brain when proceeding object perception. Extensive experiments demonstrate that our simple yet effective approach fundamentally boosts the performance of 3D point cloud object detection and achieves the state-of-the-art results., Comment: 8 pages, 5 figures, CVPR 2020

BACKGROUND: The orbitofrontal cortex (OFC) is implicated in depression. The hypothesis investigated was whether the OFC sensitivity to reward and nonreward is related to the severity of depressive symptoms.METHODS: Activations in the monetary incentive delay task were measured in the IMAGEN cohort at ages 14 years (n = 1877) and 19 years (n = 1140) with a longitudinal design. Clinically relevant subgroups were compared at ages 19 (high-severity group: n = 116; low-severity group: n = 206) and 14.RESULTS: The medial OFC exhibited graded activation increases to reward, and the lateral OFC had graded activation increases to nonreward. In this general population, the medial and lateral OFC activations were associated with concurrent depressive symptoms at both ages 14 and 19 years. In a stratified high-severity depressive symptom group versus control group comparison, the lateral OFC showed greater sensitivity for the magnitudes of activations related to nonreward in the high-severity group at age 19 (p = .027), and the medial OFC showed decreased sensitivity to the reward magnitudes in the high-severity group at both ages 14 (p = .002) and 19 (p = .002). In a longitudinal design, there was greater sensitivity to nonreward of the lateral OFC at age 14 for those who exhibited high depressive symptom severity later at age 19 (p = .003).CONCLUSIONS: Activations in the lateral OFC relate to sensitivity to not winning, were associated with high depressive symptom scores, and at age 14 predicted the depressive symptoms at ages 16 and 19. Activations in the medial OFC were related to sensitivity to winning, and reduced reward sensitivity was associated with concurrent high depressive symptom scores.

Bumetanide has been reported to alter synaptic excitation–inhibition (E-I) balance by potentiating the action of γ-aminobutyric acid (GABA), thereby attenuating the severity of autism spectrum disorder (ASD) in animal models. However, clinical evidence of its efficacy in young patients with ASD is limited. This was investigated in the present clinical trial of 83 patients, randomised to the bumetanide group (bumetanide treatment, 0.5 mg twice daily) or the control group (no bumetanide treatment). Primary [Children Autism Rating Scale (CARS)], secondary [Clinical Global Impressions (CGI)], and exploratory [inhibitory (γ-aminobutyric acid, GABA) and excitatory (glutamate, Glx) neurotransmitter concentrations measured in the insular cortex (IC) and visual cortex (VC) by magnetic resonance spectroscopy (MRS)] outcome measures were evaluated at baseline and at the 3-month follow-up. Side effects were monitored throughout the treatment course. Compared with the control group, the bumetanide group showed significant reduction in symptom severity, as indicated by both total CARS score and number of items assigned a score ≥ 3. The improvement in clinical symptoms was confirmed by CGI. GABA/Glx ratio in both the IC and VC decreased more rapidly over the 3-month period in the bumetanide group than that in the control group. This decrease in the IC was associated with the symptom improvement in the bumetanide group. Our study confirmed the clinical efficacy of bumetanide on alleviating the core symptoms of ASD in young children and it is the first demonstration that the improvement is associated with reduction in GABA/Glx ratios. This study suggests that the GABA/Glx ratio measured by MRS may provide a neuroimaging biomarker for assessing treatment efficacy for bumetanide.

Background Mental disorders are typically defined as distinct diagnostic entities, but similar patterns of clinical and cognitive impairments are frequently found across diagnostic groups. We investigated whether these transdiagnostic deficits result from common neural substrates across disorders or various illness-specific mechanisms, or a combination of both. Methods Functional magnetic resonance imaging data were collected from clinically stable patients with major depressive disorder (n = 53), bipolar disorder (n = 78), or schizophrenia (n = 100) and matched healthy control subjects (n = 109) using a single scanner. Group comparisons were conducted to identify transdiagnostic and illness-specific features, and possible confounding effects of medication were considered. A multivariate approach with cross-validation was used to associate dysconnectivity features with shared cognitive deficits. Results Transdiagnostic dysconnectivities were identified within somatomotor (Cohen’s d = 0.50–0.58) and salience (Cohen’s d = 0.52–0.58) networks and between subcortical-limbic (Cohen’s d = 0.55–0.69) and subcortical-dorsal attention (Cohen’s d = 0.56–0.61) networks. The executive control network was found to be illness-specifically disconnected from the prefrontal-limbic-pallidal circuit in major depressive disorder (Cohen’s d = 0.57–0.58), prefronto-striato-parietal circuit in bipolar disorder (Cohen’s d = 0.48–0.53), and default mode network in schizophrenia (Cohen’s d = 0.47–0.56). Working memory deficits were associated with a linear combination of 11 transdiagnostic and 5 illness-specific dysconnectivities (r = .322, p = 9.7 × 10−4, n = 340). The associations of the identified dysconnectivities with medication dosage were nonsignificant. Conclusions Disconnectivity in the somatomotor network was a common transdiagnostic profile, while there were illness-specific patterns in different parts of the prefrontal cortex for different disorders. These findings suggest that prominent psychiatric disorders share common impairments, possibly linked to perception and motor output, as well as unique dysconnectivity profiles that hypothetically mediate the more distinctive features of the disorder-specific psychopathology.

Creative thinking plays a vital role in almost all aspects of human life. However, little is known about the neural and genetic mechanisms underlying creative thinking. Based on a cross-validation based predictive framework, we searched from the whole-brain connectome (34,716 functional connectivities) and whole genome data (309,996 SNPs) in two datasets (all collected by Southwest University, Chongqing) consisting of altogether 236 subjects, for a better understanding of the brain and genetic underpinning of creativity. Using the Torrance Tests of Creative Thinking score, we found that high figural creativity is mainly related to high functional connectivity between the executive control, attention, and memory retrieval networks (strong top-down effects); and to low functional connectivity between the default mode network, the ventral attention network, and the subcortical and primary sensory networks (weak bottom-up processing) in the first dataset (consisting of 138 subjects). High creativity also correlates significantly with mutations of genes coding for both excitatory and inhibitory neurotransmitters. Combining the brain connectome and the genomic data we can predict individuals' creativity scores with an accuracy of 78.4%, which is significantly better than prediction using single modality data (gene or functional connectivity), indicating the importance of combining multi-modality data. Our neuroimaging prediction model built upon the first dataset was cross-validated by a completely new dataset of 98 subjects (r = 0.267, p = 0.0078) with an accuracy of 64.6%. In addition, the creativity-related functional connectivity network we identified in the first dataset was still significantly correlated with the creativity score in the new dataset (p

Schizophrenia is genetic in origin and associated with a fecundity disadvantage. The deficits in schizophrenia have been attributed to variation related to the human capacity for language or brain laterality. How sex influences the relative connectivity of the 2 hemispheres is a route to understanding these 2 functions. Using resting-state functional magnetic resonance imaging (fMRI) we searched for sex- and hemisphere-specific changes in whole-brain functional-connectivity in multi-site datasets (altogether 672 subjects including 286 patients, all right-handed) in the first-episode schizophrenia (illness duration ≤ 1 year, mostly drug naive) and in chronic stages of schizophrenia (illness duration > 1 year), respectively. We used meta-analyses to integrate data from different sources concerning individuals at the same illness stage. We found first-episode male patients are predominantly left-lateralized in aberrant connectivity with a focus on Broca's area. Female patients show a lesser degree of lateralization than males, but to the right particularly in orbital frontal cortex. In the chronic stage, the focus of aberrant connectivity shifted from anterior to posterior structures with prominent involvement of the thalamus and pre- and post-central gyri bilaterally and in both sexes. While the "deviant connectivity" is right-sided in both the first-episode and the chronic stages in females, in males there is a shift between stages from the left to the right hemisphere. We hypothesized that the pathophysiology of schizophrenia may lie in the interaction between sex and lateralization, ie, in genetic mechanisms located on the X and Y chromosomes, intrinsic to the evolution of language.

To analyze the functioning of the amygdala in depression, we performed the first voxel-level resting state functional-connectivity neuroimaging analysis of depression of voxels in the amygdala with all other voxels in the brain, with 336 patients with major depressive disorder and 350 controls. Amygdala voxels had decreased functional connectivity with the orbitofrontal cortex, temporal lobe areas, including the temporal pole, inferior temporal gyrus, and the parahippocampal gyrus. The reductions in the strengths of the functional connectivity of the amygdala voxels with the medial orbitofrontal cortex and temporal lobe voxels were correlated with increases in the Beck Depression Inventory score and in the duration of illness measures of depression. Parcellation analysis in 350 healthy controls based on voxel-level functional connectivity showed that the basal division of the amygdala has high functional connectivity with medial orbitofrontal cortex areas, and the dorsolateral amygdala has strong functional connectivity with the lateral orbitofrontal cortex and related ventral parts of the inferior frontal gyrus. In depression, the basal amygdala division had especially reduced functional connectivity with the medial orbitofrontal cortex which is involved in reward; and the dorsolateral amygdala subdivision had relatively reduced functional connectivity with the lateral orbitofrontal cortex which is involved in non-reward.

Background Whether there are distinct subtypes of schizophrenia is an important issue to advance understanding and treatment of schizophrenia. Aims To understand and treat individuals with schizophrenia, the aim was to advance understanding of differences between individuals, whether there are discrete subtypes, and how first-episode patients (FEP) may differ from multiple episode patients (MEP). Method These issues were analysed in 687 FEP and 1880 MEP with schizophrenia using the Positive and Negative Syndrome Scale for (PANSS) schizophrenia before and after antipsychotic medication for 6 weeks. Results The seven Negative Symptoms were correlated with each other and with P2 (conceptual disorganisation), G13 (disturbance of volition), and G7 (motor retardation). The main difference between individuals was in the cluster of seven negative symptoms, which had a continuous unimodal distribution. Medication decreased the PANSS scores for all the symptoms, which were similar in the FEP and MEP groups. Conclusions The negative symptoms are a major source of individual differences, and there are potential implications for treatment. Declaration of interests L.P. received speaker fees from Otsuka Canada and educational grant from Janssen Canada in 2017. Copyright and usage © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity.

In this paper, we propose a new weakly supervised 3D brain lesion segmentation approach using attentional representation learning. Our approach only requires image-level labels, and is able to produce accurate segmentation of the 3D lesion volumes. To achieve that, we design a novel dimensional independent attention mechanism on top of the Class Activation Maps (CAMs), which refines the 3D CAMs to obtain better estimates of the lesion volumes, without introducing significantly more trainable variables. The generated attentional CAMs are then used as a source of weak supervision signals to learn a representation model, which can reliably separate the voxels belong to the lesion volumes from those of the normal tissues. The proposed approach has been evaluated on the publicly available BraTS and ISLES datasets. We show with comprehensive experiments that our approach significantly outperforms the competing weakly-supervised methods in both initial lesion localization and the final segmentation, and is able to achieve comparable Dice scores in segmentation comparing to the fully supervised baselines.

The orbitofrontal cortex extends into the laterally adjacent inferior frontal gyrus. We analyzed how voxel-level functional connectivity of the inferior frontal gyrus and orbitofrontal cortex is related to depression in 282 people with major depressive disorder (125 were unmedicated) and 254 controls, using FDR correction P

Low sleep duration in adults is correlated with psychiatric and cognitive problems. We performed for the first time a large-scale analysis of sleep duration in children, and how this relates to psychiatric problems including depression, to cognition, and to brain structure. Structural MRI was analyzed in relation to sleep duration, and psychiatric and cognitive measures in 11,067 9–11-year-old children from the Adolescent Brain Cognitive Development (ABCD) Study, using a linear mixed model, mediation analysis, and structural equation methods in a longitudinal analysis. Dimensional psychopathology (including depression, anxiety, impulsive behavior) in the children was negatively correlated with sleep duration. Dimensional psychopathology in the parents was also correlated with short sleep duration in their children. The brain areas in which higher volume was correlated with longer sleep duration included the orbitofrontal cortex, prefrontal and temporal cortex, precuneus, and supramarginal gyrus. Longitudinal data analysis showed that the psychiatric problems, especially the depressive problems, were significantly associated with short sleep duration 1 year later. Further, mediation analysis showed that depressive problems significantly mediate the effect of these brain regions on sleep. Higher cognitive scores were associated with higher volume of the prefrontal cortex, temporal cortex, and medial orbitofrontal cortex. Public health implications are that psychopathology in the parents should be considered in relation to sleep problems in children. Moreover, we show that brain structure is associated with sleep problems in children, and that this is related to whether or not the child has depressive problems.

The first voxel-level resting-state functional connectivity (FC) neuroimaging analysis of depression of the anterior cingulate cortex (ACC) showed in 282 patients with major depressive disorder compared with 254 controls, some higher, and some lower FCs. However, in 125 unmedicated patients, primarily increases of FC were found: of the subcallosal anterior cingulate with the lateral orbitofrontal cortex, of the pregenual/supracallosal anterior cingulate with the medial orbitofrontal cortex, and of parts of the anterior cingulate with the inferior frontal gyrus, superior parietal lobule, and with early cortical visual areas. In the 157 medicated patients, these and other FCs were lower than in the unmedicated group. Parcellation was performed based on the FC of individual ACC voxels in healthy controls. A pregenual subdivision had high FC with medial orbitofrontal cortex areas, and a supracallosal subdivision had high FC with lateral orbitofrontal cortex and inferior frontal gyrus. The high FC in depression between the lateral orbitofrontal cortex and the subcallosal parts of the ACC provides a mechanism for more non-reward information transmission to the ACC, contributing to depression. The high FC between the medial orbitofrontal cortex and supracallosal ACC in depression may also contribute to depressive symptoms.

Dynamical changes have recently been tracked in functional connectivity (FC) calculated from resting-state functional magnetic resonance imaging (R-fMRI), when a person is conscious but not carrying out a directed task during scanning. Diverse dynamical FC states (dFC) are believed to represent different internal states of the brain, in terms of brain-regional interactions. In this paper, we propose a novel protocol, the signed community clustering with the optimized modularity by two-step procedures, to track dynamical whole brain functional connectivity (dWFC) states. This protocol is assumption free without a priori threshold for the number of clusters. By applying our method on sliding window based dWFC’s with automated anatomical labeling 2 (AAL2), three main dWFC states were extracted from R-fMRI datasets in Human Connectome Project, that are independent on window size. Through extracting the FC features of these states, we found the functional links in state 1 (WFC-C1) mainly involved visual, somatomotor, attention and cerebellar (posterior lobe) modules. State 2 (WFC-C2) was similar to WFC-C1, but more FC’s linking limbic, default mode, and frontoparietal modules and less linking the cerebellum, sensory and attention modules. State 3 had more FC’s linking default mode, limbic, and cerebellum, compared to WFC-C1 and WFC-C2. With tests of robustness and stability, our work provides a solid, hypothesis-free tool to detect dWFC states for the possibility of tracking rapid dynamical change in FCs among large data sets.

Following a first version AAL of the automated anatomical labeling atlas (Tzourio-Mazoyer et al., 2002), a second version (AAL2) (Rolls et al., 2015) was developed that provided an alternative parcellation of the orbitofrontal cortex following the description provided by Chiavaras, Petrides, and colleagues. We now provide a third version, AAL3, which adds a number of brain areas not previously defined, but of interest in many neuroimaging investigations. The 26 new areas in the third version are subdivision of the anterior cingulate cortex into subgenual, pregenual and supracallosal parts; subdivision of the thalamus into 15 parts; the nucleus accumbens, substantia nigra, ventral tegmental area, red nucleus, locus coeruleus, and raphe nuclei. The new atlas is available as a toolbox for SPM, and can be used with MRIcron.

Background Binge eating and other forms of disordered eating behavior (DEB) are associated with failed inhibitory control. This study investigated the neural correlates of failed inhibitory control as a potential biomarker for DEB. Methods The study used prospective longitudinal data from the European IMAGEN study adolescent cohort. Participants completed baseline assessments (questionnaires and a brain scan [functional magnetic resonance imaging]) at 14 years of age and a follow-up assessment (questionnaires) at 16 years of age. Self-reported binge eating and/or purging were used to indicate presence of DEB. Neural correlates of failed inhibition were assessed using the stop signal task. Participants were categorized as healthy control subjects (reported no DEB at both time points), maintainers (reported DEB at both time points), recoverers (reported DEB at baseline only), and developers (reported DEB at follow-up only). Forty-three individuals per group with complete scanning data were matched on gender, age, puberty, and intelligence (N = 172). Results At baseline, despite similar task performance, incorrectly responding to stop signals (failed inhibitory control) was associated with greater recruitment of the medial prefrontal cortex and anterior cingulate cortex in the developers compared with healthy control subjects and recoverers. Conclusions Greater recruitment of the medial prefrontal and anterior cingulate regions during failed inhibition accords with abnormal evaluation of errors contributing to DEB development. As this precedes symptom onset and is evident despite normal task performance, neural responses during failed inhibition may be a useful biomarker of vulnerability for DEB. This study highlights the potential value of prospective neuroimaging studies for identifying markers of illness before the emergence of behavior changes.

In a group of 831 participants from the general population in the Human Connectome Project, smokers exhibited low overall functional connectivity, and more specifically of the lateral orbitofrontal cortex which is associated with non-reward mechanisms, the adjacent inferior frontal gyrus, and the precuneus. Participants who drank a high amount had overall increases in resting state functional connectivity, and specific increases in reward-related systems including the medial orbitofrontal cortex and the cingulate cortex. Increased impulsivity was found in smokers, associated with decreased functional connectivity of the non-reward-related lateral orbitofrontal cortex; and increased impulsivity was found in high amount drinkers, associated with increased functional connectivity of the reward-related medial orbitofrontal cortex. The main findings were cross-validated in an independent longitudinal dataset with 1176 participants, IMAGEN. Further, the functional connectivities in 14-year-old non-smokers (and also in female low-drinkers) were related to who would smoke or drink at age 19. An implication is that these differences in brain functional connectivities play a role in smoking and drinking, together with other factors., eLife digest To understand why people become addicted to alcohol or smoking, it is important to look at how the brains of people who use these substances may be different than those who abstain. Many studies show that substance use activates the reward systems in the brain via a chemical called dopamine. Changes or differences in parts of the brain that control decision-making and restraint also have been implicated in substance use. Functional magnetic resonance imaging (fMRI) is one tool scientists can use to explore such differences. It can measure how well different parts of the brain are communicating with each other by measuring their activity when a person is at rest. The patterns of activity reveal which parts of the brain are working closely together or have high functional connectivity and which parts are less well connected, or have low functional connectivity. Cheng, Rolls et al. measured the functional connectivity between different parts of the brain in people who smoke and people who drink alcohol. Smokers had a low overall functional connectivity between brain regions. Specifically, they had weaker connections involving two brain regions that help people change or stop a behavior, the lateral orbitofrontal cortex and inferior frontal gyrus. These differences may make people more impulsive and less able to resist smoking. The stimulating effects of nicotine may enhance communication between different parts of the brain, so people also may use it to overcome some underlying communication deficits. Those who drink alcohol had high overall functional connectivity. Reward-related systems, including the medial orbitofrontal cortex and the cingulate cortex, were especially strongly connected. This may make them more sensitive to the rewarding aspects of drinking, or more impulsive. To confirm their results, Cheng, Rolls et al. analyzed fMRI data from another study. These showed that the characteristic differences in brain connectivity were already present in 14-year olds who would go on to drink or smoke at age 19. This suggests that these functional connectivity differences in the brain make people more likely to smoke or drink.

Adolescent binge drinking has been associated with higher risks for the development of many health problems throughout the lifespan. Adolescents undergo multiple changes that involve the co-development processes of brain, personality and behavior; therefore, certain behavior, such as alcohol consumption, can have disruptive effects on both brain development and personality maturation. However, these effects remain unclear due to the scarcity of longitudinal studies. In the current study, we used multivariate approaches to explore discriminative features in brain functional architecture, personality traits, and genetic variants in 19-year-old individuals (n = 212). Taking advantage of a longitudinal design, we selected features that were more drastically altered in drinkers with an earlier onset of binge drinking. With the selected features, we trained a hierarchical model of support vector machines using a training sample (n = 139). Using an independent sample (n = 73), we tested the model and achieved a classification accuracy of 71.2%. We demonstrated longitudinally that after the onset of binge drinking the developmental trajectory of improvement in impulsivity slowed down. This study identified the disrupting effects of adolescent binge drinking on the developmental trajectories of both brain and personality., Highlights • History of binge drinking could be identified by multivariate features at age 19. • Adolescent binge drinking disrupted frontal connectivity maturation in the brain. • Impulsivity improvement slowed down after the onset of adolescent binge drinking.

Significance We characterize in humans a coordinated network of brain activity describing neurobehavioral correlates of reward anticipation. The network involves nodes in striatal and cortical brain regions, which are preferentially associated with distinct externalizing behaviors—hyperactivity and alcohol consumption—suggesting that the heterogeneity of reward-related behaviors might be accounted for by different association patterns of nodes and their connecting links. In a genome-wide association study of the striatal node with subsequent functional validation in Drosophila , we identify molecular genetic mechanisms involving vacuolar protein sorting-associated protein 4A ( VPS4A ) in dopamine regulation, reward anticipation, and hyperactivity. Our approach might facilitate the identification of causal neural mechanisms, important for the identification of previously unidentified targets and the establishment of neurobehaviorally informed end points for clinical trials.