White matter injury,neural connectivity and the pathophysiology of psychiatric disorders

Psychiatric disorders are characterized by diverse clinical manifestations that include deficits in cognition, perception, mood and arousal. These complex processes are not mediated by any specific brain region but require the coordinated activity of several areas that are anatomically connected. Impairments in these neural circuits may therefore be expected to result in an attenuation of the functions regulated by them. The white matter provides the structural and physiological substrate of neural circuits in the central nervous system. We propose that injury to the white matter, from diverse biological sources, may compromise neural connectivity by associated axonal injury or impaired conductivity. Either mechanism could result in clusters of signs and symptoms that are currently recognized as psychiatric disorders. The role of white matter impairment in the pathophysiology of psychiatric illness is under-appreciated in the neurosciences. Focused translational research aimed at identifying the links between white matter compromise and specific behaviors are necessary for a more thorough understanding of the etiology of mental illness to emerge.     

Childhood maltreatment is associated with a sex‐dependent functional reorganization of a brain inhibitory control network

Childhood adversity represents a major risk factor for drug addiction and other mental disorders. However, the specific mechanisms by which childhood adversity impacts human brain organization to confer greater vulnerability for negative outcomes in adulthood is largely unknown. As an impaired process in drug addiction, inhibitory control of behavior was investigated as a target of childhood maltreatment (abuse and neglect). Forty adults without Axis‐I psychiatric disorders (21 females) completed a Childhood Trauma Questionnaire (CTQ) and underwent functional MRI (fMRI) while performing a stop‐signal task. A group independent component analysis identified a putative brain inhibitory control network. Graph theoretical analyses and structural equation modeling investigated the impact of childhood maltreatment on the functional organization of this neural processing network. Graph theory outcomes revealed sex differences in the relationship between network functional connectivity and inhibitory control which were dependent on the severity of childhood maltreatment exposure. A network effective connectivity analysis indicated that a maltreatment dose‐related negative modulation of dorsal anterior cingulate (dACC) activity by the left inferior frontal cortex (IFC) predicted better response inhibition and lesser attention deficit hyperactivity disorder (ADHD) symptoms in females, but poorer response inhibition and greater ADHD symptoms in males. Less inhibition of the right IFC by dACC in males with higher CTQ scores improved inhibitory control ability. The childhood maltreatment‐related reorganization of a brain inhibitory control network provides sex‐dependent mechanisms by which childhood adversity may confer greater risk for drug use and related disorders and by which adaptive brain responses protect individuals from this risk factor. Hum Brain Mapp 35:1654–1667, 2014. © 2013 Wiley Periodicals, Inc.     

Effects of enriched environment on animal models of neurodegenerative diseases and psychiatric disorders

Environmental stimulation throughout development adjusts the neurobehavioral systems involved in learning, memory and defensive responses. Environment-mediated phenotypic plasticity can be considered from two different, yet complementary, viewpoints. On one hand, the possibility that environmental interventions protect against the effects of genetic and/or acquired vulnerabilities, offers unprecedented avenues towards the elaboration and refinement of therapeutic strategies. On the other hand, an accurate understanding of the adaptive mechanisms regulating the interaction between an experimental subject and its environment may substantially benefit the quality of experimental data. Here we review experimental evidence showing that enriched environment can be beneficial in several psychiatric and neurodegenerative disorders implicating the monoamine systems where it can (i) compensate for impairments in animal models of schizophrenia, Huntington's, and Parkinson's diseases; (ii) increase resistance to the addictive properties of psychostimulant drugs; (iii) level-out the consequences of prenatal stress in animal models of depression. Additionally we discuss why some of the effects of environmental enrichment question the validity of current animal models of mental disorders.     

Triple-pulse TMS to study interactions between neural circuits in human cortex

Transcranial magnetic stimulation (TMS) is a widely used brain stimulation technique that allows noninvasive examination of different excitatory and inhibitory circuits at the systems level in the intact human brain. In recent years, considerable knowledge has been accumulated about the physiology of?several of these facilitatory and inhibitory processes individually. However, activity in the corresponding neural circuits is not independent of each other. This paper reviews the experiments using triple-pulse TMS that are specifically designed to study interactions between intracortical circuits. These studies have provided evidence for a complex network of interconnected neural circuits within and across cerebral hemispheres. The current knowledge about the functional organization of this network, its pharmacology and functional implications for human motor control are discussed in detail. These findings have clinical relevance because specific interactions between neural circuits may be impaired in neurologic and psychiatric disorders. We conclude that triple-pulse TMS studies will help to integrate and better understand the physiologic processes involved in human motor behavior.     

Biological rhythms, higher brain function, and behavior: Gaps, opportunities, and challenges

Increasing evidence suggests that disrupted temporal organization impairs behavior, cognition, and affect; further, disruption of circadian clock genes impairs sleep-wake cycle and social rhythms which may be implicated in mental disorders. Despite this strong evidence, a gap in understanding the neural mechanisms of this interaction obscures whether biological rhythms disturbances are the underlying causes or merely symptoms of mental disorder. Here, we review current understanding, emerging concepts, gaps, and opportunities pertinent to (1) the neurobiology of the interactions between circadian oscillators and the neural circuits subserving higher brain function and behaviors of relevance to mental health, (2) the most promising approaches to determine how biological rhythms regulate brain function and behavior under normal and pathological conditions, (3) the gaps and challenges to advancing knowledge on the link between disrupted circadian rhythms/sleep and psychiatric disorders, and (4) the novel strategies for translation of basic science discoveries in circadian biology to clinical settings to define risk, prevent or delay onset of mental illnesses, design diagnostic tools, and propose new therapeutic strategies. The review is organized around five themes pertinent to (1) the impact of molecular clocks on physiology and behavior, (2) the interactions between circadian signals and cognitive functions, (3) the interface of circadian rhythms with sleep, (4) a clinical perspective on the relationship between circadian rhythm abnormalities and affective disorders, and (5) the pre-clinical models of circadian rhythm abnormalities and mood disorders.     

Assessment and diagnosis of mental illness in persons with mental retardation. Methods and measures

The assessment and diagnosis of psychiatric disorders in individuals with mental retardation has been a neglected area of research. However, current research indicates that these individuals suffer from the same range of psychiatric disorders that is evident in those who are not mentally retarded. A model of assessment and diagnosis of mental illness in this population is presented that incorporates psychiatric as well as behavioral methods. The emphasis is on the comprehensive assessment of an individual's behavior, based on family history, self and informant clinical interviews, rating scales, direct observations, and an experimental analysis of the target behaviors. The model provides the basis for making differential diagnoses in terms of related psychiatric disorders and between psychiatric disorders and behavior problems. Depression and schizophrenia are used as illustrative disorders to describe the application of this model. Given the paucity of literature on the assessment and diagnosis of mental illness in individuals with mental retardation, a number of suggestions are made regarding future research and refinement of the model.     

Les analyses par réseau : vers une nouvelle conceptualisation et prise en charge des troubles mentaux ?

In a break with categorical and dimensional approaches and thus the classical medical model, the network approach applied to psychopathology constitutes a holistic approach to mental disorders. In this approach, mental disorders are conceived as an interconnected system of symptoms in which symptoms are the cause of each other. It is suggested that the interaction between the different symptoms would result in a feedback loop that leads to the installation and maintenance of these symptoms/disorders. In addition, this approach proposes that co-morbidities are the result of symptom-symptom interactions that cross the diagnostic boundary and interact with symptoms from other psychiatric disorders. A growing number of studies have applied the network approach to elucidate causal interactions within the symptoms of depression, post-traumatic stress disorder, schizophrenia, or anxiety disorders. The overall objective of this review is to raise awareness among researchers and clinicians in psychiatry and clinical psychology of the network approach applied to psychopathology. To do this, we present the main concepts and principles of the network approach and its application in post-traumatic stress disorder. We also discuss recent criticisms of this approach and its clinical applications.     

Case report of the treatment and experience of mental disorders due to chronic viral encephalitis

Viral encephalitis is a common clinical condition. Its clinical manifestations are variable and include neurological symptoms and psychiatric abnormalities, which makes clinical diagnosis and treatment difficult. To date, there are only a few reported cases on mental symptoms of chronic viral encephalitis. We present a case of a 16-year-old male patient who was previously hospitalised and diagnosed with schizophrenia and treated with aripiprazole 15 mg/day but failed to respond. The patient was then given antiviral therapy and recovered after 2 weeks. Clinicians should be aware of the possbility that chronic mental disorders could be caused by viral encephalitis. In the future, diagnosis of chronic functional mental disorders should include viral encephalitis in the differential diagnosis.     

Staging,réseaux de symptômes : les nouvelles approches cliniques de la schizophrénie

Debate on the clinic of psychiatric disorders has been, for several decades, largely occupied by nosographic considerations resulting from the work which led to the publication of the DSM in its third version in 1980. However, DSM is a nomenclature, not a psychiatry manual and researches focusing on the clinic of mental disorders are essential in the progress of knowledge. Recently, in the field of psychotic disorders, new clinical approaches were developed, having heuristic value and having an impact on clinical practices. The staging model and the network theory of schizophrenia will be successively evoked, which are two fertile areas of these new clinical perspectives. Recent works to validate the staging model in schizophrenia, in large retrospective and prospective cohorts, found out two clinical models, conceptually congruent, in which, stages of the illness can be discriminated using symptoms, functioning and episodes. Each model would need to be tested in other independent samples to evaluate their reliability and accuracy. One of the findings of these works is that patients can improve or deteriorate from one stage to another, but prediction of the evolution remains uncertain. The next goals of research are to combine clinical evaluation with biomarkers, and also to develop the use of innovative statistical tools and methodologies in the field, to operationalize the concept of precision staging. On the other hand, regarding the network theory of schizophrenia, recent works highlight the interest of identifying networks of highly interrelated symptoms to focus on target symptoms and to develop specific treatment strategies. Clinical approaches are the counterpart of the physiopathological and etiopathogenic researches on mental disorders, carried out in particular by research in the field of genetics and brain imaging. The staging model and the network theory have a heuristic virtue and contribute to a new approach not only to schizophrenia but to all psychiatric disorders. In the daily clinical practice, they allow a new approach to patients and their care. Their interest has led to the development of professional recommendations for the management of schizophrenia, based on the staging model and particularly useful for clinicians.     

Hypersomnolence,Hypersomnia, and Mood Disorders

Relationships between symptoms of hypersomnolence, psychiatric disorders, and hypersomnia disorders (i.e., narcolepsy and idiopathic hypersomnia) are complex and multidirectional. Hypersomnolence is a common complaint across mood disorders; however, patients suffering from mood disorders and hypersomnolence rarely have objective daytime sleepiness, as assessed by the current gold standard test, the Multiple Sleep Latency Test. An iatrogenic origin of symptoms of hypersomnolence, and sleep apnea syndrome must be considered in a population of psychiatric patients, often overweight and treated with sedative drugs. On the other hand, psychiatric comorbidities, especially depression symptoms, are often reported in patients with hypersomnia disorders, and an endogenous origin cannot be ruled out. A great challenge for sleep specialists and psychiatrists is to differentiate psychiatric hypersomnolence and a central hypersomnia disorder with comorbid psychiatric symptoms. The current diagnostic tools seem to be limited in that condition, and further research in that field is warranted.     

Psychiatric diseases

The traditional boundary between primary psychiatric disorders, as “diseases of the mind”, and neurological conditions, as “diseases of the brain”, has been challenged since advances in brain imaging techniques have allowed the correlation of functional and structural brain abnormalities with the presence and severity of psychopathological symptoms in psychiatric illnesses, thus suggesting a neural basis for their onset and progression and providing an in vivo pathological anatomy of psychiatric diseases.     

Towards a brain‐based predictome of mental illness

Neuroimaging‐based approaches have been extensively applied to study mental illness in recent years and have deepened our understanding of both cognitively healthy and disordered brain structure and function. Recent advancements in machine learning techniques have shown promising outcomes for individualized prediction and characterization of patients with psychiatric disorders. Studies have utilized features from a variety of neuroimaging modalities, including structural, functional, and diffusion magnetic resonance imaging data, as well as jointly estimated features from multiple modalities, to assess patients with heterogeneous mental disorders, such as schizophrenia and autism. We use the term “predictome” to describe the use of multivariate brain network features from one or more neuroimaging modalities to predict mental illness. In the predictome, multiple brain network‐based features (either from the same modality or multiple modalities) are incorporated into a predictive model to jointly estimate features that are unique to a disorder and predict subjects accordingly. To date, more than 650 studies have been published on subject‐level prediction focusing on psychiatric disorders. We have surveyed about 250 studies including schizophrenia, major depression, bipolar disorder, autism spectrum disorder, attention‐deficit hyperactivity disorder, obsessive–compulsive disorder, social anxiety disorder, posttraumatic stress disorder, and substance dependence. In this review, we present a comprehensive review of recent neuroimaging‐based predictomic approaches, current trends, and common shortcomings and share our vision for future directions.     

基于人工神经网络与人工智能的计算机系统在儿童心理障碍诊断领域的应用

背景：将人工智能和人工神经网络二者相结合应用于精神卫生领域的文献在国内外还未见报道,更未见将人工神经网络与人工智能相结合用于模拟人类医学专家大脑诊断思维模式诊断儿童心理障碍的相关报道。 目的：用计算机模拟人脑诊断思维模式,建立一套基于人工神经网络与专家系统的儿童心理障碍标准化诊断与防治的人工智能专家系统。 方法：儿童心理障碍标准化诊断与防治的人工智能专家系统涉及儿童心理学、儿童精神病学、心理测量、心理治疗、计算机科学等诸多学科,诊断系统结合了ICD-10、DSM IV及CCMD-2等诊断标准、大规模流行病学调查数据、资深精神医学专家的丰富临床经验和临床资料。临床资料来源于全国14 家医院流调及门诊收集的原始病例,共回收有效资料1 125份,用基于神经网络与专家系统相结合的方法进行智能诊断系统的编制。 结果与结论：诊断系统能诊断61种儿童心理障碍,它包括95%以上的儿童心理障碍,在诊断之后,计算机将给出一个治疗方法建议。将195例计算机系统诊断结果与资深儿童心理精神医学专家的诊断结果进行双盲比较,诊断符合率是99%,有助于年轻医生学习资深儿童心理精神医学专家丰富的临床经验,也能帮助全国各地的心理障碍患儿,更好地为儿童心理卫生事业服务。     

Microanatomy of dendritic spines: emerging principles of synaptic pathology in psychiatric and neurological disease.

Psychiatric and neurologic disorders ranging from mental retardation to addiction are accompanied by structural and functional alterations of synaptic connections in the brain. Such alterations include abnormal density and morphology of dendritic spines, synapse loss, and aberrant synaptic signaling and plasticity. Recent work is revealing an unexpectedly complex biochemical and subcellular organization of dendritic spines. In this review, we highlight the molecular interplay between functional domains of the spine, including the postsynaptic density, the actin cytoskeleton, and membrane trafficking domains. This research points to an emerging level of analysis--a microanatomical understanding of synaptic physiology--that will be critical for discerning how synapses operate in normal physiologic states and for identifying and reversing microscopic changes in psychiatric and neurologic disease.     

Identification of common neural substrates with connectomic abnormalities in four major psychiatric disorders: A connectome-wide association study

BackgroundRecent imaging studies of large datasets suggested that psychiatric disorders have common biological substrates. This study aimed to identify all the common neural substrates with connectomic abnormalities across four major psychiatric disorders by using the data-driven connectome-wide association method of multivariate distance matrix regression (MDMR).MethodsThis study analyzed a resting functional magnetic resonance imaging dataset of 100 patients with schizophrenia, 100 patients with bipolar I disorder, 100 patients with bipolar II disorder, 100 patients with major depressive disorder, and 100 healthy controls (HCs). We calculated a voxel-wise 4,330 × 4,330 matrix of whole-brain functional connectivity (FC) with 8-mm isotropic resolution for each participant and then performed MDMR to identify structures where the overall multivariate pattern of FC was significantly different between each patient group and the HC group. A conjunction analysis was performed to identify common neural regions with FC abnormalities across these four psychiatric disorders.ResultsThe conjunction of the MDMR maps revealed that the four groups of patients shared connectomic abnormalities in distributed cortical and subcortical structures, which included bilateral thalamus, cerebellum, frontal pole, supramarginal gyrus, postcentral gyrus, lingual gyrus, lateral occipital cortex, and parahippocampus. The follow-up analysis based on pair-wise FC of these regions demonstrated that these psychiatric disorders also shared similar patterns of FC abnormalities characterized by sensory/subcortical hyperconnectivity, association/subcortical hypoconnectivity, and sensory/association hyperconnectivity.ConclusionsThese findings suggest that major psychiatric disorders share common connectomic abnormalities in distributed cortical and subcortical regions and provide crucial support for the common network hypothesis of major psychiatric disorders.     

An update on selected organic mental syndromes

The authors review recent literature on four medical conditions that constitute important examples of organic mental disorders: AIDS dementia complex, cocaine abuse, cerebrovascular accident, and traumatic brain injury. These disorders are of particular interest because they are frequently the result of high-risk behaviors and the patients are often young adults. Progress in classification and diagnosis, along with greater understanding of pathophysiological mechanisms, has facilitated therapies to ameliorate some symptoms. More specific classification of organic mental disorders should facilitate the examination of biological factors believed responsible for functional psychiatric disturbances.     

Computational neuroscience approach to biomarkers and treatments for mental disorders

Psychiatry research has long experienced a stagnation stemming from a lack of understanding of the neurobiological underpinnings of phenomenologically defined mental disorders. Recently, the application of computational neuroscience to psychiatry research has shown great promise in establishing a link between phenomenological and pathophysiological aspects of mental disorders, thereby recasting current nosology in more biologically meaningful dimensions. In this review, we highlight recent investigations into computational neuroscience that have undertaken either theory‐ or data‐driven approaches to quantitatively delineate the mechanisms of mental disorders. The theory‐driven approach, including reinforcement learning models, plays an integrative role in this process by enabling correspondence between behavior and disorder‐specific alterations at multiple levels of brain organization, ranging from molecules to cells to circuits. Previous studies have explicated a plethora of defining symptoms of mental disorders, including anhedonia, inattention, and poor executive function. The data‐driven approach, on the other hand, is an emerging field in computational neuroscience seeking to identify disorder‐specific features among high‐dimensional big data. Remarkably, various machine‐learning techniques have been applied to neuroimaging data, and the extracted disorder‐specific features have been used for automatic case–control classification. For many disorders, the reported accuracies have reached 90% or more. However, we note that rigorous tests on independent cohorts are critically required to translate this research into clinical applications. Finally, we discuss the utility of the disorder‐specific features found by the data‐driven approach to psychiatric therapies, including neurofeedback. Such developments will allow simultaneous diagnosis and treatment of mental disorders using neuroimaging, thereby establishing ‘theranostics’ for the first time in clinical psychiatry.     

Stress coercitif en unité de soins intensifs psychiatrique : quel lien avec l’insight ?

The aim of this work was to study the correlations between the coercive experience level in patients in a psychiatric intensive care unit and clinical insight. We included 40 patients without specific diagnosis criteria at the end of their hospitalization in the intensive care unit. We assessed patients with the Coercion Experience Scale (CES) to measure their coercive stress level, and the Scale to Assess Unawareness of Mental Disorder (SUMD) which measures clinical insight. A total of 42.5 % of our sample suffered from mood disorders, 50 % suffered from psychotic disorders and 7.5 % from other disorders. On the one hand, we found that patients’ coercive stress level was neither correlated with the awareness of their mental disorder nor with the awareness of social consequences of their mental disorder. On the other hand, we found that coercive stress level was significantly correlated with patients’ awareness of treatment efficacy and that the specific CES factor measuring coercion showed a strong trend to significantly correlate with patients’ awareness of treatment efficacy. These results seem to show that education about benefits of treatment is a key point to improve patients’ coercive stress in a psychiatric intensive care unit, more than an education about awareness of the mental disorder itself.     

Structure and function of complex brain networks

An increasing number of theoretical and empirical studies approach the function of the human brain from a network perspective. The analysis of brain networks is made feasible by the development of new imaging acquisition methods as well as new tools from graph theory and dynamical systems. This review surveys some of these methodological advances and summarizes recent findings on the architecture of structural and functional brain networks. Studies of the structural connectome reveal several modules or network communities that are interlinked by hub regions mediating communication processes between modules. Recent network analyses have shown that network hubs form a densely linked collective called a “rich club,” centrally positioned for attracting and dispersing signal traffic. In parallel, recordings of resting and task-evoked neural activity have revealed distinct resting-state networks that contribute to functions in distinct cognitive domains. Network methods are increasingly applied in a clinical context, and their promise for elucidating neural substrates of brain and mental disorders is discussed.