Diagnosis and treatment of neuropsychiatric disorders

Extracting interpretable signatures of whole-brain dynamics through systematic comparison

The brain's complex distributed dynamics are typically quantified using a limited set of manually selected statistical properties, leaving the possibility that alternative dynamical properties may outperform those reported for a given application. Here, we address this limitation by systematically comparing diverse, interpretable features of both intra-regional activity and inter-regional functional coupling from resting-state functional magnetic resonance imaging (rs-fMRI) data, demonstrating our method using case-control comparisons of four neuropsychiatric disorders. Our findings generally support the use of linear time-series analysis techniques for rs-fMRI case-control analyses, while also identifying new ways to quantify informative dynamical fMRI structures. While simple statistical representations of fMRI dynamics performed surprisingly well (e.g., properties within a single brain region), combining intra-regional properties with inter-regional coupling generally improved performance, underscoring the distributed, multifaceted changes to fMRI dynamics in neuropsychiatric disorders. The comprehensive, data-driven method introduced here enables systematic identification and interpretation of quantitative dynamical signatures of multivariate time-series data, with applicability beyond neuroimaging to diverse scientific problems involving complex time-varying systems.

Proteomic analysis of peripheral blood mononuclear cells in first episode psychosis - Protein and peptide-centered approaches to elucidate potential diagnostic biomarkers

Diagnosing patients suffering from psychotic disorders is far from being achieved with molecular support, despite all the efforts to study these disorders from different perspectives. Characterizing the proteome of easily obtainable blood specimens, such as the peripheral blood mononuclear cells (PBMCs), has particular interest in biomarker discovery and generating pathophysiological knowledge. This approach has been explored in psychiatry, and while generating valuable information, it has not translated into meaningful biomarker discovery. In this project, we report the proof-of-concept of a methodology that aims to explore further information obtained with classical proteomics approaches that is easily overlooked. PBMC samples from first-episode psychosis and control subjects were subjected to a SWATH-MS approach, and the classical protein relative quantification was performed, where 389 proteins were found to be important to distinguish the two groups. Individual analysis of the quantified peptides was also performed, highlighting peptides of unchanged proteins that were significantly altered. With the combination of protein- and peptide-centered proteomics approaches, it is possible to highlight that information about proteoforms, namely regulation at the peptide level possibly due to post-translational modifications, is routinely overlooked and that its diagnostic potential should be further explored. SIGNIFICANCE: Our exploratory findings highlight the potential of MS-based proteomics strategies, combining protein- and peptide-centered approaches, to aid clinical decision-making in first-episode psychosis, helping to establish early biomarkers for schizophrenia and other psychotic disorders. Particularly, the less popular peptide-centered approach allows the identification/measurement of overlooked modulated peptides that may have potential biomarker characteristics. The application in parallel of protein- and peptide-centered strategies is transversal to research of other diseases, potentially allowing a more comprehensive characterization of the metabolic/pathophysiological alterations related to a specific disease.

Extracting interpretable signatures of whole-brain dynamics through systematic comparison

The brain's complex distributed dynamics are typically quantified using a limited set of manually selected statistical properties, leaving the possibility that alternative dynamical properties may outperform those reported for a given application. Here, we address this limitation by systematically comparing diverse, interpretable features of both intra-regional activity and inter-regional functional coupling from resting-state functional magnetic resonance imaging (rs-fMRI) data, demonstrating our method using case-control comparisons of four neuropsychiatric disorders. Our findings generally support the use of linear time-series analysis techniques for rs-fMRI case-control analyses, while also identifying new ways to quantify informative dynamical fMRI structures. While simple statistical representations of fMRI dynamics performed surprisingly well (e.g., properties within a single brain region), combining intra-regional properties with inter-regional coupling generally improved performance, underscoring the distributed, multifaceted changes to fMRI dynamics in neuropsychiatric disorders. The comprehensive, data-driven method introduced here enables systematic identification and interpretation of quantitative dynamical signatures of multivariate time-series data, with applicability beyond neuroimaging to diverse scientific problems involving complex time-varying systems.

Chronic Opioid Treatment Arrests Neurodevelopment and Alters Synaptic Activity in Human Midbrain Organoids

Understanding the impact of long-term opioid exposure on the embryonic brain is critical due to the surging number of pregnant mothers with opioid dependency. However, this has been limited by human brain inaccessibility and cross-species differences in animal models. Here, a human midbrain model is established that uses hiPSC-derived midbrain organoids to assess cell-type-specific responses to acute and chronic fentanyl treatment and fentanyl withdrawal. Single-cell mRNA sequencing of 25,510 cells from organoids in different treatment groups reveals that chronic fentanyl treatment arrests neuronal subtype specification during early midbrain development and alters synaptic activity and neuron projection. In contrast, acute fentanyl treatment increases dopamine release but does not significantly alter gene expression related to cell lineage development. These results provide the first examination of the effects of opioid exposure on human midbrain development at the single-cell level.

The role of Toll-like receptors in neuropsychiatric disorders: Immunopathology, treatment, and management

Neuropsychiatric disorders denote a broad range of illnesses involving neurology and psychiatry. These disorders include depressive disorders, anxiety, schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorders, headaches, and epilepsy. In addition to their main neuropathology that lies in the central nervous system (CNS), lately, studies have highlighted the role of immunity and neuroinflammation in neuropsychiatric disorders. Toll-like receptors (TLRs) are innate receptors that act as a bridge between the innate and adaptive immune systems via adaptor proteins (e.g., MYD88) and downstream elements; TLRs are classified into 13 families that are involved in normal function and illnesses of the CNS. TLRs expression affects the course of neuropsychiatric disorders, and is influenced during their pharmacotherapy; For example, the expression of multiple TLRs is normalized during the major depressive disorder pharmacotherapy. Here, the role of TLRs in neuroimmunology, treatment, and management of neuropsychiatric disorders is discussed. We recommend longitudinal studies to comparatively assess the cell-type-specific expression of TLRs during treatment, illness progression, and remission. Also, further research should explore molecular insights into TLRs regulation and related pathways.

Neuropsychiatric disorders, chronotype and sleep: A narrative review of GWAS findings and the application of Mendelian randomization to investigate causal relationships

Genome-wide association studies (GWAS) have been important for characterizing the genetic component and enhancing our understanding of the biological aetiology of both neuropsychiatric disorders and sleep-related phenotypes such as chronotype, which is our preference for morning or evening time. Mendelian randomization (MR) is a post-GWAS analysis that is used to infer causal relationships between potential risk factors and outcomes. MR uses genetic variants as instrumental variants for exposures to study the effect on outcomes. This review details the main results from GWAS of neuropsychiatric disorders and sleep-related phenotypes, and the application of MR to investigate their bidirectional relationship. The main results from MR studies of neuropsychiatric disorders and sleep-related phenotypes are summarized. These MR studies have identified 37 causal relationships between neuropsychiatric disorders and sleep-related phenotypes. MR studies identified evidence of a causal role for five neuropsychiatric disorders and symptoms (attention deficit hyperactivity disorder, bipolar disorder, depressive symptoms, major depressive disorder and schizophrenia) on sleep-related phenotypes and evidence of a causal role for five sleep-related phenotypes (daytime napping, insomnia, morning person, long sleep duration and sleep duration) on risk for neuropsychiatric disorders. These MR results show a bidirectional relationship between neuropsychiatric disorders and sleep-related phenotypes and identify potential risk factors for follow-up studies.

Predictive modelling of brain disorders with magnetic resonance imaging: A systematic review of modelling practices, transparency, and interpretability in the use of convolutional neural networks

Brain disorders comprise several psychiatric and neurological disorders which can be characterized by impaired cognition, mood alteration, psychosis, depressive episodes, and neurodegeneration. Clinical diagnoses primarily rely on a combination of life history information and questionnaires, with a distinct lack of discriminative biomarkers in use for psychiatric disorders. Symptoms across brain conditions are associated with functional alterations of cognitive and emotional processes, which can correlate with anatomical variation; structural magnetic resonance imaging (MRI) data of the brain are therefore an important focus of research, particularly for predictive modelling. With the advent of large MRI data consortia (such as the Alzheimer's Disease Neuroimaging Initiative) facilitating a greater number of MRI-based classification studies, convolutional neural networks (CNNs)-deep learning models well suited to image processing tasks-have become increasingly popular for research into brain conditions. This has resulted in a myriad of studies reporting impressive predictive performances, demonstrating the potential clinical value of deep learning systems. However, methodologies can vary widely across studies, making them difficult to compare and/or reproduce, potentially limiting their clinical application. Here, we conduct a qualitative systematic literature review of 55 studies carrying out CNN-based predictive modelling of brain disorders using MRI data and evaluate them based on three principles-modelling practices, transparency, and interpretability. We propose several recommendations to enhance the potential for the integration of CNNs into clinical care.

Apolipoprotein D as a Potential Biomarker in Neuropsychiatric Disorders

Neuropsychiatric disorders (NDs) are a diverse group of pathologies, including schizophrenia or bipolar disorders, that directly affect the mental and physical health of those who suffer from them, with an incidence that is increasing worldwide. Most NDs result from a complex interaction of multiple genes and environmental factors such as stress or traumatic events, including the recent Coronavirus Disease (COVID-19) pandemic. In addition to diverse clinical presentations, these diseases are heterogeneous in their pathogenesis, brain regions affected, and clinical symptoms, making diagnosis difficult. Therefore, finding new biomarkers is essential for the detection, prognosis, response prediction, and development of new treatments for NDs. Among the most promising candidates is the apolipoprotein D (Apo D), a component of lipoproteins implicated in lipid metabolism. Evidence suggests an increase in Apo D expression in association with aging and in the presence of neuropathological processes. As a part of the cellular neuroprotective defense machinery against oxidative stress and inflammation, changes in Apo D levels have been demonstrated in neuropsychiatric conditions like schizophrenia (SZ) or bipolar disorders (BPD), not only in some brain areas but in corporal fluids, i.e., blood or serum of patients. What is not clear is whether variation in Apo D quantity could be used as an indicator to detect NDs and their progression. This review aims to provide an updated view of the clinical potential of Apo D as a possible biomarker for NDs.

Multi-modal intermediate integrative methods in neuropsychiatric disorders: A review

The etiology of neuropsychiatric disorders involves complex biological processes at different omics layers, such as genomics, transcriptomics, epigenetics, proteomics, and metabolomics. The advent of high-throughput technology, as well as the availability of large open-source datasets, has ushered in a new era in system biology, necessitating the integration of various types of omics data. The complexity of biological mechanisms, the limitations of integrative strategies, and the heterogeneity of multi-omics data have all presented significant challenges to computational scientists. In comparison to early and late integration, intermediate integration may transform each data type into appropriate intermediate representations using various data transformation techniques, allowing it to capture more complementary information contained in each omics and highlight new interactions across omics layers. Here, we reviewed multi-modal intermediate integrative techniques based on component analysis, matrix factorization, similarity network, multiple kernel learning, Bayesian network, artificial neural networks, and graph transformation, as well as their applications in neuropsychiatric domains. We depicted advancements in these approaches and compared the strengths and weaknesses of each method examined. We believe that our findings will aid researchers in their understanding of the transformation and integration of multi-omics data in neuropsychiatric disorders.

Neurological Complications of COVID-19: A Review of the Literature

Coronavirus disease 2019 (COVID-19) has caused the most unprecedented health crisis since the 1918 H1N1 pandemic. Whilst COVID-19 is traditionally considered to be a respiratory disease, it is important to understand that this virus has the potential to disseminate throughout the body causing multi-organ failure. Both peripheral and central neurological systems have been shown to be greatly affected. This review aims to look at the available literature published on COVID-19 and summarize the main neurological complications seen so far.

Systematic Review and Meta-Analysis of Mass Spectrometry Proteomics Applied to Human Peripheral Fluids to Assess Potential Biomarkers of Schizophrenia

Mass spectrometry (MS)-based techniques can be a powerful tool to identify neuropsychiatric disorder biomarkers, improving prediction and diagnosis ability. Here, we evaluate the efficacy of MS proteomics applied to human peripheral fluids of schizophrenia (SCZ) patients to identify disease biomarkers and relevant networks of biological pathways. Following PRISMA guidelines, a search was performed for studies that used MS proteomics approaches to identify proteomic differences between SCZ patients and healthy control groups (PROSPERO database: CRD42021274183). Nineteen articles fulfilled the inclusion criteria, allowing the identification of 217 differentially expressed proteins. Gene ontology analysis identified lipid metabolism, complement and coagulation cascades, and immune response as the main enriched biological pathways. Meta-analysis results suggest the upregulation of FCN3 and downregulation of APO1, APOA2, APOC1, and APOC3 in SCZ patients. Despite the proven ability of MS proteomics to characterize SCZ, several confounding factors contribute to the heterogeneity of the findings. In the future, we encourage the scientific community to perform studies with more extensive sampling and validation cohorts, integrating omics with bioinformatics tools to provide additional comprehension of differentially expressed proteins. The produced information could harbor potential proteomic biomarkers of SCZ, contributing to individualized prognosis and stratification strategies, besides aiding in the differential diagnosis.

Brain SPECT as an Imaging Biomarker for Evaluating Effects of Novel Treatments in Psychiatry-A Case Series

The difficulties of evaluating patients with complex neuropsychiatric conditions and prescribing appropriate treatments are well known. Imaging complements clinical assessments and allows a clinician to narrow the differential diagnosis by facilitating accurate and efficient evaluation. This is particularly relevant to neuropsychiatric conditions that are often diagnosed using a trial-and error process of exclusion. Single Photon Emission Computed Tomography (SPECT) is a functional brain imaging procedure that allows practitioners to measure the functional changes of gray matter structures based on regional cerebral blood flow (rCBF). The accurate diagnosis and treatment selection in psychiatry is challenging due to complex cases and frequent comorbidities. However, such complex neuropsychiatric conditions are increasingly benefitting from new treatment approaches, in addition to established medications. Among these are combination transcranial magnetic stimulation with ketamine infusions (CTK), hyperbaric oxygen therapy (HBOT) and perispinal administration of etanercept (PSE). This article provides readers with six case study examples that demonstrate how brain SPECT imaging can be used, both as a diagnostic tool, and as a potential biomarker for monitoring and evaluating novel treatments for patients with complex neuropsychiatric conditions. Six patients were assessed in our clinic and baseline brain SPECT imagesTourettes and a long history of alcohol were visually compared with SPECT images collected after periods of treatment with CTK or HBOT followed by PSE. This retrospective review demonstrates the clinical utility of these novel treatments and describes how SPECT imaging can complement standard diagnostic assessments. A novel display technique for SPECT images is described and we argue that SPECT imaging can be used for monitoring biomarker for clinical change.

Dendritic spine membrane proteome and its alterations in autistic spectrum disorder

Dendritic spines are small protrusions stemming from the dendritic shaft that constitute the primary specialization for receiving and processing excitatory neurotransmission in brain synapses. The disruption of dendritic spine function in several neurological and neuropsychiatric diseases leads to severe information-processing deficits with impairments in neuronal connectivity and plasticity. Spine dysregulation is usually accompanied by morphological alterations to spine shape, size and/or number that may occur at early pathophysiological stages and not necessarily be reflected in clinical manifestations. Autism spectrum disorder (ASD) is one such group of diseases involving changes in neuronal connectivity and abnormal morphology of dendritic spines on postsynaptic neurons. These alterations at the subcellular level correlate with molecular changes in the spine proteome, with alterations in the copy number, topography, or in severe cases in the phenotype of the molecular components, predominantly of those proteins involved in spine recognition and adhesion, reflected in abnormally short lifetimes of the synapse and compensatory increases in synaptic connections. Since cholinergic neurotransmission participates in the regulation of cognitive function (attention, memory, learning processes, cognitive flexibility, social interactions) brain acetylcholine receptors are likely to play an important role in the dysfunctional synapses in ASD, either directly or indirectly via the modulatory functions exerted on other neurotransmitter receptor proteins and spine-resident proteins.

Protocol for a systematic review on the role of the gut microbiome in paediatric neurological disorders

INTRODUCTION

The gut-brain axis refers to the bidirectional communication that occurs between the intestinal tract and central nervous system (CNS). Through a series of neural, immune, endocrine, and metabolic signalling pathways, commensal microbiota are able to influence CNS development and neurological function. Alterations in gut microbiota have been implicated in various neuropathologies. The purpose of this review is to evaluate and summarise existing literature assessing the role of specific bacterial taxa on the development of neurodevelopmental, neuropsychiatric, and neurodegenerative pathologies of childhood. We will also discuss microbiota-based therapies dietary interventions and their efficacy.

METHODS AND ANALYSIS

We will search PubMed, Cochrane Library, and OVID electronic databases for articles published between January 1980 and February 2021. A search method involving two rounds of reviewing the literature using a three-step method in each round will be performed. Two researchers will be selected, and screen titles and abstracts independently. The full text of selected articles will be assessed against inclusion criteria. Data will be extracted and evaluated using the appropriate Critical Appraisal Skills Programme (CASP) checklist.

ETHICS AND DISSEMINATION

Findings from this study will be shared across relevant paediatric neurology and gastroenterology societies and submitted for peer review. This study did not require institutional ethics approval.

Repurposing of Anti-Diabetic Agents as a New Opportunity to Alleviate Cognitive Impairment in Neurodegenerative and Neuropsychiatric Disorders

Cognitive impairment is a shared abnormality between type 2 diabetes mellitus (T2DM) and many neurodegenerative and neuropsychiatric disorders, such as Alzheimer’s disease (AD) and schizophrenia. Emerging evidence suggests that brain insulin resistance plays a significant role in cognitive deficits, which provides the possibility of anti-diabetic agents repositioning to alleviate cognitive deficits. Both preclinical and clinical studies have evaluated the potential cognitive enhancement effects of anti-diabetic agents targeting the insulin pathway. Repurposing of anti-diabetic agents is considered to be promising for cognitive deficits prevention or control in these neurodegenerative and neuropsychiatric disorders. This article reviewed the possible relationship between brain insulin resistance and cognitive deficits. In addition, promising therapeutic interventions, especially current advances in anti-diabetic agents targeting the insulin pathway to alleviate cognitive impairment in AD and schizophrenia were also summarized.

National Institutes of Mental Health Data Archive: Privacy, Consent, and Diversity Considerations and Options for Improvement

Data sharing is essential to further advance the field of neuropsychiatry. However, it raises significant ethical issues in the domains of privacy, consent, and diversity. We begin by considering the sensitive nature of much neuropsychiatric data. Next, we review relevant policies of the National Institutes of Mental Health (NIMH), a prominent funder in this field. Because data sharing in neuropsychiatry is in its infancy and rapidly evolving, the NIMH policies serve as a helpful starting point for examining ethical considerations related to the collection and distribution of neuropsychiatric data. However, we find gaps in their guidance in each of the three key ethical domains. Finally, we illustrate how examination of lessons and strategies from other contexts where sustained attention has already been given to these ethical issues may add value by suggesting specific opportunities for improvement. In particular, we highlight approaches including a three-tiered data access scheme, use of technology to enhance the data sharing component of the informed consent process, and evidence-based, targeted recruitment of underrepresented populations to support diverse data resources. Assessment of current policy and potentially helpful innovations in other fields is a necessary step in moving the field forward in an ethically responsible manner.

Psychometric analysis of the behavioral assessment screening tool (BAST) in adults with stroke

PURPOSE

The purpose of this study was to examine the initial psychometric properties of the Behavioral Assessment Screening Tool (BAST), a self-reported measure of neurobehavioral symptoms, in adults with stroke.

METHODS

We assessed subscale and item-level reliabilities of the five BAST subscales in 75 community-dwelling adults with stroke. We further assessed the known-groups validity of the BAST to differentiate individuals with and without self-reported lifetime stroke history (n = 47 with stroke and n = 1843 neurologically healthy controls).

RESULTS

Cronbach's alpha coefficients of all subscales were >0.7, demonstrating acceptable to good internal consistency reliabilities, and corrected item-total correlations were all >.30 demonstrating good item-level reliabilities. ROC curves demonstrated strong known-groups validity of the negative affect, executive function, and fatigue subscales for classifying stroke versus healthy controls (AUC = .669-.758, p < .001).

CONCLUSION

The BAST demonstrates good initial psychometric properties as a screening tool to identify neurobehavioral symptoms in community-dwelling adults with stroke. Future work will add stroke-specific items, further assess the validity of the BAST, and employ item response theory or Rasch analyses to identify highly discriminative items for potential smart device-based ecological momentary assessments.

Modeling SARS-CoV-2 infection in individuals with opioid use disorder with brain organoids

The COVID-19 pandemic has aggravated a preexisting epidemic: the opioid crisis. Much literature has shown that the circumstances imposed by COVID-19, such as social distancing regulations, medical and financial instability, and increased mental health issues, have been detrimental to those with opioid use disorder (OUD). In addition, unexpected neurological sequelae in COVID-19 patients suggest that COVID-19 compromises neuroimmunity, induces hypoxia, and causes respiratory depression, provoking similar effects as those caused by opioid exposure. Combined conditions of COVID-19 and OUD could lead to exacerbated complications. With limited human in vivo options to study these complications, we suggest that iPSC-derived brain organoid models may serve as a useful platform to investigate the physiological connection between COVID-19 and OUD. This mini-review highlights the advances of brain organoids in other neuropsychiatric and infectious diseases and suggests their potential utility for investigating OUD and COVID-19, respectively.

Repairing blood-CNS barriers: Future therapeutic approaches for neuropsychiatric disorders

Central nervous system (CNS) drug development faces significant difficulties that translate into high rates of failure and lack of innovation. The pathophysiology of neurological and psychiatric disorders often results in the breakdown of blood-CNS barriers, disturbing the CNS microenvironment and worsening disease progression. Therefore, restoring the integrity of blood-CNS barriers may have a beneficial influence in several CNS disorders and improve treatment outcomes. In this review, pathways that may be modulated to protect blood-CNS barriers from neuroinflammatory and oxidative insults are featured. First, the participation of the brain endothelium and glial cells in disruption processes is discussed. Then, the relevance of regulatory systems is analysed, specifically the hypothalamic-pituitary axis, the renin-angiotensin system, sleep and circadian rhythms, and glutamate neurotransmission. Lastly, compounds of endogenous and exogenous origin that are known to mediate the repair of blood-CNS barriers are presented. We believe that enhancing the protection of blood-CNS barriers is a promising therapeutic strategy to pursue in the future.

Dendritic structural plasticity and neuropsychiatric disease

The structure of neuronal circuits that subserve cognitive functions in the brain is shaped and refined throughout development and into adulthood. Evidence from human and animal studies suggests that the cellular and synaptic substrates of these circuits are atypical in neuropsychiatric disorders, indicating that altered structural plasticity may be an important part of the disease biology. Advances in genetics have redefined our understanding of neuropsychiatric disorders and have revealed a spectrum of risk factors that impact pathways known to influence structural plasticity. In this Review, we discuss the importance of recent genetic findings on the different mechanisms of structural plasticity and propose that these converge on shared pathways that can be targeted with novel therapeutics.

Psychiatric manifestations of neurologic diseases: Etiology, phenomenology, and treatment

Understanding the etiology and meaning of behavioral symptomatology in the context of neurologic disease, and choosing the most effective intervention is a vexing task. This introduction summarizes the history of our understanding of the relationship between behavioral symptoms and primary neurologic conditions, and considers the ways in which both psychiatric and neurologic disorders occurring simultaneously may inform both knowledge of etiology and treatment decisions.

Ablative stereotactic neurosurgery for irreducible neuroaggressive disorder in pediatric patients

INTRODUCTION AND OBJECTIVES

The irreducible neuroaggressive disorder (IND) is a well-described entity known to be associated with impulsive and aggressive behavior. While various studies have assessed available pharmacological and non-pharmacological treatment regimens, patients with IND continue to pose a major threat to themselves and society. While targeted stereotactic therapy for IND has gained traction in recent years, there is a paucity of information describing comparative effectiveness of different validated anatomic regions. In this paper, we discuss the surgical results for patients with IND following targeted lesional therapy with a special focus on selection criteria and operative methods. The objective is to analyze the efficacy and safety of the different described targets for this disorder in pediatric patients.

MATERIALS AND METHODS

Eight pediatric patients met strict criteria for IND and were enrolled in this study. Electroencephalography (EEG), video electroencephalography (VEEG) and magnetic resonance imaging (MRI) were performed in all patients prior to surgery. Irreducible neuroagressive symptom was approached by lesional therapy based on most described targets for this disorder and assessed by The Overt Agressive Scale (OAS) pre-operatively and 6 months following surgery, using Wilcoxon test for statistical analysis.

RESULTS AND CONCLUSIONS

The average patient age was 13 years 2 months. 7 of the 8 patients enrolled had intellectual disabilities, 1 patient suffered neurologic sequelae referable to Dandy Walker syndrome and 7 patients had no preoperative anatomical alterations. Following surgery, patients with IND noted improvement in their OAS. On average, the OAS improved by 39.29% (P=.0156), a figure similar in comparison to studies assessing treatment of IND in adult patients. The most satisfactory results were achieved in patients whose ablative therapy involved the Amygdala in their targets. There were no deaths or permanent neurological deficits attributable to procedure. To the author's knowledge, this is the largest series described in the literature for pediatric patients with IND treated with lesional stereotactic therapy.

Disruption of Ninjurin1 Leads to Repetitive and Anxiety-Like Behaviors in Mice

Over the last few decades, molecular neurobiology has uncovered many genes whose deficiency in mice results in behavioral traits associated with human neuropsychiatric disorders such as autism, obsessive-compulsive disorder (OCD), and schizophrenia. However, the etiology of these common diseases remains enigmatic with the potential involvement of a battery of genes. Here, we report abnormal behavioral phenotypes of mice deficient in a cell adhesion molecule Ninjurin 1 (Ninj1), which are relevant to repetitive and anxiety behaviors of neuropsychiatric disorders. Ninj1 knockout (KO) mice exhibit compulsive grooming-induced hair loss and self-made lesions as well as increased anxiety-like behaviors. Histological analysis reveals that Ninj1 is predominantly expressed in cortico-thalamic circuits, and neuron-specific Ninj1 conditional KO mice manifest aberrant phenotypes similar to the global Ninj1 KO mice. Notably, the brains of Ninj1 KO mice display altered synaptic transmission in thalamic neurons as well as a reduced number of functional synapses. Moreover, the disruption of Ninj1 leads to glutamatergic abnormalities, including increased ionotropic glutamate receptors but reduced glutamate levels. Furthermore, chronic treatment with fluoxetine, a drug reportedly ameliorates compulsive behaviors in mice, prevents progression of hair loss and alleviates the compulsive grooming and anxiety-like behavior of Ninj1 KO mice. Collectively, our results suggest that Ninj1 could be involved in neuropsychiatric disorders associated with impairments of repetitive and anxiety behaviors.

Opportunities for bioinformatics in the classification of behavior and psychiatric disorders

A bioinformatics approach to behavioral neuroscience provides both unique opportunities and challenges for research on behavior. A major challenge has been to describe, define, and discriminate among abstract behavioral processes, in large part by distinguishing among the biological mechanisms of unique but not entirely discrete, entities of behavior. Understanding the complexity of neurobiology and behavior requires integration of data across diverse biological systems, types of data, and levels of scale. With the perspective and application of bioinformatics, we can uncover the relationships among these systems and take steps forward in realizing the common and distinct bases of psychiatric disease.

Implantable stimulator for epileptic seizure suppression with loading impedance adaptability

The implantable stimulator for epileptic seizure suppression with loading impedance adaptability was proposed in this work. The stimulator consisted of the high voltage generator, output driver, adaptor, and switches, can constantly provide the required 40-μA stimulus currents, as the loading impedance varied within 10 kΩ -300 kΩ. The performances of this design have been successfully verified in silicon chip fabricated by a 0.35- μm 3.3-V/24-V CMOS process. The power consumption of this work was only 1.1 mW-1.4 mW. The animal test results with the fabricated chip of proposed design have successfully verified in the Long-Evans rats with epileptic seizures.

Neurobehavioral disorders

Neurobehavioral disorders are composed of a large group of behavioral impairments seen in association with brain disease (e.g., stroke, multiple sclerosis, dementia, and neuro-oncological conditions), transient as well as permanent brain impairments (e.g., metabolic and toxic encephalopathies), and/or injury (e.g., trauma, hypoxia, and/or ischemia). The neurorehabilitative assessment and management of such disorders is often poorly addressed in the context of overall neurological, psychiatric, and rehabilitative care. Too often, more basic, yet critical, aspects of behavioral assessment and treatment are not addressed or only superficially addressed by evaluating clinicians. Physicians often overly rely on pharmacological interventions as initial and/or sole treatment approaches rather than taking a pragmatic biopsychosocial approach that focuses on holistic disease state management. This chapter provides readers with an overview of the common behavioral impairments associated with brain dysfunction due to disease, injury, or toxicity. Details regarding the nature of impairments such as localization-related syndromes, affective disorders and personality disorders, among others are expounded. Principles of neurobehavioral assessment and treatment are examined including general guidelines for eliciting a history and physical, behavioral analysis, and functional behavioral assessment. General treatment caveats are provided including discussion of impairment and disability adaptation, and creation of positive behavioral supports. The topic of pharmacological management of neurobehavioral disorders is covered in numerous other references including Chapter 33 of this text.

Modular networks involving the medial frontal cortex: towards the development of neuropsychiatry

OBJECTIVES

The pathophysiology of mental disorders is largely unresolved. We propose that the identification of abnormalities in brain modular networks will provide a promising approach for the understanding of mental disorders.

METHODS

We review the current discussion on the neuroscientific basis of psychiatric diseases and review recent studies in functional neuroimaging and systems physiology on mental functions of the human brain.

RESULTS

We propose that brain functional units are organized in modular networks. Modular networks allow for flexibility within the modular processing units and across interconnected modules affording optimization of task performance and deficit compensation in disease. As an example it will be shown that differentiated modules in medial frontal cortex play a critical role for the control of behaviour. This will be contrasted to recent studies in neurological and psychiatric patients revealing behavioural abnormalities due to lesions or reversibly deprived functions in the medial frontal cortex.

CONCLUSIONS

These findings are conceptualized as starting points for a neuroscience based diagnosis and treatment of brain diseases at the border of psychiatry and neurology.