Neuroimaging distinction between neurological and psychiatric disorders

Me, Myself and My Insula: An Oasis in the Forefront of Self-Consciousness

The insula is a multiconnected brain region that centralizes a wide range of information, from the most internal bodily states, such as interoception, to high-order processes, such as knowledge about oneself. Therefore, the insula would be a core region involved in the self networks. Over the past decades, the question of the self has been extensively explored, highlighting differences in the descriptions of the various components but also similarities in the global structure of the self. Indeed, most of the researchers consider that the self comprises a phenomenological part and a conceptual part, in the present moment or extending over time. However, the anatomical substrates of the self, and more specifically the link between the insula and the self, remain unclear. We conducted a narrative review to better understand the relationship between the insula and the self and how anatomical and functional damages to the insular cortex can impact the self in various conditions. Our work revealed that the insula is involved in the most primitive levels of the present self and could consequently impact the self extended in time, namely autobiographical memory. Across different pathologies, we propose that insular damage could engender a global collapse of the self.

Palliative psychiatry in a narrow and in a broad sense: A concept clarification

Even with optimal treatment, some persons with severe and persistent mental illness do not achieve a level of mental health, psychosocial functioning and quality of life that is acceptable to them. With each unsuccessful treatment attempt, the probability of achieving symptom reduction declines while the probability of somatic and psychological side effects increases. This worsening benefit-harm ratio of treatment aiming at symptom reduction has motivated calls for implementing palliative approaches to care into psychiatry (palliative psychiatry). Palliative psychiatry accepts that some cases of severe and persistent mental illness can be irremediable and calls for a careful evaluation of goals of care in these cases. It aims at reducing harm, relieving suffering and thus improving quality of life directly, working around irremediable psychiatric symptoms. In a narrow sense, this refers to patients likely to die of their severe and persistent mental illness soon, but palliative psychiatry in a broad sense is not limited to end-of-life care. It can - and often should - be integrated with curative and rehabilitative approaches, as is the gold standard in somatic medicine. Palliative psychiatry constitutes a valuable addition to established non-curative approaches such as rehabilitative psychiatry (which focuses on psychosocial functioning instead of quality of life) and personal recovery (a journey that persons living with severe and persistent mental illness may undertake, not necessarily accompanied by mental health care professionals). Although the implementation of palliative psychiatry is met with several challenges such as difficulties regarding decision-making capacity and prognostication in severe and persistent mental illness, it is a promising new approach in caring for persons with severe and persistent mental illness, regardless of whether they are at the end of life.

Dynamic Interrogation of Stochastic Transcriptome Trajectories Using Disease Associated Genes Reveals Distinct Origins of Neurological and Psychiatric Disorders

The advent of open access to genomic data offers new opportunities to revisit old clinical debates while approaching them from a different angle. We examine anew the question of whether psychiatric and neurological disorders are different from each other by assessing the pool of genes associated with disorders that are understood as psychiatric or as neurological. We do so in the context of transcriptome data tracked as human embryonic stem cells differentiate and become neurons. Building upon probabilistic layers of increasing complexity, we describe the dynamics and stochastic trajectories of the full transcriptome and the embedded genes associated with psychiatric and/or neurological disorders. From marginal distributions of a gene’s expression across hundreds of cells, to joint interactions taken globally to determine degree of pairwise dependency, to networks derived from probabilistic graphs along maximal spanning trees, we have discovered two fundamentally different classes of genes underlying these disorders and differentiating them. One class of genes boasts higher variability in expression and lower dependencies (High Expression Variability-HEV genes); the other has lower variability and higher dependencies (Low Expression Variability-LEV genes). They give rise to different network architectures and different transitional states. HEV genes have large hubs and a fragile topology, whereas LEV genes show more distributed code during the maturation toward neuronal state. LEV genes boost differentiation between psychiatric and neurological disorders also at the level of tissue across the brain, spinal cord, and glands. These genes, with their low variability and asynchronous ON/OFF states that have been treated as gross data and excluded from traditional analyses, are helping us settle this old argument at more than one level of inquiry.

Interhemispheric co-alteration of brain homotopic regions

Asymmetries in gray matter alterations raise important issues regarding the pathological co-alteration between hemispheres. Since homotopic areas are the most functionally connected sites between hemispheres and gray matter co-alterations depend on connectivity patterns, it is likely that this relationship might be mirrored in homologous interhemispheric co-altered areas. To explore this issue, we analyzed data of patients with Alzheimer’s disease, schizophrenia, bipolar disorder and depressive disorder from the BrainMap voxel-based morphometry database. We calculated a map showing the pathological homotopic anatomical co-alteration between homologous brain areas. This map was compared with the meta-analytic homotopic connectivity map obtained from the BrainMap functional database, so as to have a meta-analytic connectivity modeling map between homologous areas. We applied an empirical Bayesian technique so as to determine a directional pathological co-alteration on the basis of the possible tendencies in the conditional probability of being co-altered of homologous brain areas. Our analysis provides evidence that: the hemispheric homologous areas appear to be anatomically co-altered; this pathological co-alteration is similar to the pattern of connectivity exhibited by the couples of homologues; the probability to find alterations in the areas of the left hemisphere seems to be greater when their right homologues are also altered than vice versa, an intriguing asymmetry that deserves to be further investigated and explained.

Dissection of the Genetic Association between Anorexia Nervosa and Obsessive-Compulsive Disorder at the Network and Cellular Levels

Anorexia nervosa (AN) and obsessive-compulsive disorder (OCD) exhibit a high co-morbidity rate, similar symptoms, and a shared genetic basis. However, an understanding of the specific underlying mechanisms of these commonalities is currently limited. Here, we collected Genome-Wide Association Analysis results for AN and OCD, and obtained genes hit by the top SNPs as the risk genes. We then carried out an integrative coexpression network analysis to explore the convergence and divergence of AN and OCD risk genes. At first, we observed that the AN risk genes were enriched in coexpression modules that involved extracellular matrix functions and highly are expressed in the postnatal brain, limbic system, and non-neuronal cell types, while the OCD risk genes were enriched in modules of synapse function, the prenatal brain, cortex layers, and neurons. Next, by comparing the expressions from the eating disorder and OCD postmortem patient brain tissues, we observed both disorders have similar prefrontal cortex expression alterations influencing the synapse transmission, suggesting that the two diseases could have similar functional pathways. We found that the AN and OCD risk genes had distinct functional and spatiotemporal enrichment patterns but carried similar expression alterations as a disease mechanism, which may be one of the key reasons they had similar but not identical clinical phenotypes.

Translational Application of a Neuro-Scientific Multi-Modal Approach Into Forensic Psychiatric Evaluation: Why and How?

A prominent body of literature indicates that insanity evaluations, which are intended to provide influential expert reports for judges to reach a decision "beyond any reasonable doubt," suffer from a low inter-rater reliability. This paper reviews the limitations of the classical approach to insanity evaluation and the criticisms to the introduction of neuro-scientific approach in court. Here, we explain why in our opinion these criticisms, that seriously hamper the translational implementation of neuroscience into the forensic setting, do not survive scientific scrutiny. Moreover, we discuss how the neuro-scientific multimodal approach may improve the inter-rater reliability in insanity evaluation. Critically, neuroscience does not aim to introduce a brain-based concept of insanity. Indeed, criteria for responsibility and insanity are and should remain clinical. Rather, following the falsificationist approach and the convergence of evidence principle, the neuro-scientific multimodal approach is being proposed as a way to improve reliability of insanity evaluation and to mitigate the influence of cognitive biases on the formulation of insanity opinions, with the final aim to reduce errors and controversies.

Idiopathic and acquired pedophilia as two distinct disorders: an insight from neuroimaging

Pedophilia is a disorder of public concern because of its association with child sexual offense and recidivism. Previous neuroimaging studies of potential brain abnormalities underlying pedophilic behavior, either in idiopathic or acquired (i.e., emerging following brain damages) pedophilia, led to inconsistent results. This study sought to explore the neural underpinnings of pedophilic behavior and to determine the extent to which brain alterations may be related to distinct psychopathological features in pedophilia. To this aim, we run a coordinate based meta-analysis on previously published papers reporting whole brain analysis and a lesion network analysis, using brain lesions as seeds in a resting state connectivity analysis. The behavioral profiling approach was applied to link identified regions with the corresponding psychological processes. While no consistent neuroanatomical alterations were identified in idiopathic pedophilia, the current results support that all the lesions causing acquired pedophilia are localized within a shared resting state network that included posterior midlines structures, right inferior temporal gyrus and bilateral orbitofrontal cortex. These regions are associated with action inhibition and social cognition, abilities that are consistently and severely impaired in acquired pedophiles. This study suggests that idiopathic and acquired pedophilia may be two distinct disorders, in line with their distinctive clinical features, including age of onset, reversibility and modus operandi. Understanding the neurobiological underpinnings of pedophilic behavior may contribute to a more comprehensive characterization of these individuals on a clinical ground, a pivotal step forward for the development of more efficient therapeutic rehabilitation strategies.

A biopsychosocial interpretation of the Neuropsychiatric Inventory - Nursing Home assessment: reconceptualising psychiatric symptom attributions

BACKGROUND

The Neuropsychiatric Inventory (NPI) is predicated on the assumption that psychiatric symptoms are manifestations of disease. Biopsychosocial theories suggest behavioural changes viewed as psychiatric may also arise as a result of external behavioural triggers. Knowing the causes of psychiatric symptoms is important since the treatment and management of symptoms relies on this understanding.

AIMS

This study sought to understand the causes of psychiatric symptoms recorded in care home settings by investigating qualitatively described symptoms in Neuropsychiatric Inventory-Nursing Home (NPI-NH) interviews.

METHOD

The current study examined the NPI-NH interviews of 725 participants across 50 care homes. The qualitatively described symptoms from each of the 12 subscales of the NPI were extracted: 347 interviews included at least one qualitatively described symptom (n = 651 descriptions). A biopsychosocial algorithm developed following a process of independent researcher coding (n = 3) was applied to the symptom descriptions. This determined whether the description had predominantly psychiatric features, or features that were cognitive or attributable to other causes (i.e. issues with orientation and memory; expressions of need; poor care and communication; or understandable reactions).

RESULTS

Our findings suggest that the majority (over 80%) of descriptions described symptoms with features that could be attributable to cognitive changes and external triggers (such as poor care and communication).

CONCLUSIONS

The finding suggest that in its current form the NPI-NH may over attribute the incidence of psychiatric symptoms in care homes by overlooking triggers for behavioural changes. Measures of psychiatric symptoms should determine the causes of behavioural changes in order to guide treatments more effectively.

The pathoconnectivity network analysis of the insular cortex: A morphometric fingerprinting

Brain disorders tend to impact on many different regions in a typical way: alterations do not spread randomly; rather, they seem to follow specific patterns of propagation that show a strong overlap between different pathologies. The insular cortex is one of the brain areas more involved in this phenomenon, as it seems to be altered by a wide range of brain diseases. On these grounds we thoroughly investigated the impact of brain disorders on the insular cortices analyzing the patterns of their structural co-alteration. We therefore investigated, applying a network analysis approach to meta-analytic data, 1) what pattern of gray matter alteration is associated with each of the insular cortex parcels; 2) whether or not this pattern correlates and overlaps with its functional meta-analytic connectivity; and, 3) the behavioral profile related to each insular co-alteration pattern. All the analyses were repeated considering two solutions: one with two clusters and another with three. Our study confirmed that the insular cortex is one of the most altered cerebral regions among the cortical areas, and exhibits a dense network of co-alteration including a prevalence of cortical rather than sub-cortical brain regions. Regions of the frontal lobe are the most involved, while occipital lobe is the less affected. Furthermore, the co-alteration and co-activation patterns greatly overlap each other. These findings provide significant evidence that alterations caused by brain disorders are likely to be distributed according to the logic of network architecture, in which brain hubs lie at the center of networks composed of co-altered areas. For the first time, we shed light on existing differences between insula sub-regions even in the pathoconnectivity domain.

The ethical, social, and cultural dimensions of screening for mental health in children and adolescents of the developing world

Despite their burden and high prevalence, mental health disorders of children and adolescents remain neglected in many parts of the world. In developing countries, where half of the population is younger than 18 years old, one of every five children and adolescents is estimated to suffer from a mental health disorder. It is then essential to detect these conditions through screening in a timely and accurate manner. But such screening is fraught with considerable ethical, social, and cultural challenges. This study systematically identifies, for the first time, these challenges, along with potential solutions to address them. We report on the results of an international multi- and inter-disciplinary three-round Delphi survey completed by 135 mental health experts from 37 countries. We asked these experts to identify and rank the main ethical, social, and cultural challenges of screening for child and adolescent mental health problems in developing nations, and to propose solutions for each challenge. Thirty-nine significant challenges emerged around eight themes, along with 32 potential solutions organized into seven themes. There was a high degree of consensus among the experts, but a few interesting disagreements arose between members of the panel from high-income countries and those from low- and middle-income nations. The panelists overwhelmingly supported mental health screening for children and adolescents. They recommended ensuring local acceptance and support for screening prior to program initiation, along with careful and comprehensive protection of human rights; integrating screening procedures into primary care; designing and implementing culturally appropriate screening tools, programs, and follow-up; securing long-term funding; expanding capacity building; and task-shifting screening to local non-specialists. These recommendations can serve as a guide for policy and decision-making, resource allocation, and international cooperation. They also offer a novel approach to reduce the burden of these disorders by encouraging their timely and context-sensitive prevention and management.

Translating research findings into clinical practice: a systematic and critical review of neuroimaging-based clinical tools for brain disorders

A pivotal aim of psychiatric and neurological research is to promote the translation of the findings into clinical practice to improve diagnostic and prognostic assessment of individual patients. Structural neuroimaging holds much promise, with neuroanatomical measures accounting for up to 40% of the variance in clinical outcome. Building on these findings, a number of imaging-based clinical tools have been developed to make diagnostic and prognostic inferences about individual patients from their structural Magnetic Resonance Imaging scans. This systematic review describes and compares the technical characteristics of the available tools, with the aim to assess their translational potential into real-world clinical settings. The results reveal that a total of eight tools. All of these were specifically developed for neurological disorders, and as such are not suitable for application to psychiatric disorders. Furthermore, most of the tools were trained and validated in a single dataset, which can result in poor generalizability, or using a small number of individuals, which can cause overoptimistic results. In addition, all of the tools rely on two strategies to detect brain abnormalities in single individuals, one based on univariate comparison, and the other based on multivariate machine-learning algorithms. We discuss current barriers to the adoption of these tools in clinical practice and propose a checklist of pivotal characteristics that should be included in an "ideal" neuroimaging-based clinical tool for brain disorders.

Innate Immunity: A Common Denominator between Neurodegenerative and Neuropsychiatric Diseases

The intricate relationships between innate immunity and brain diseases raise increased interest across the wide spectrum of neurodegenerative and neuropsychiatric disorders. Barriers, such as the blood–brain barrier, and innate immunity cells such as microglia, astrocytes, macrophages, and mast cells are involved in triggering disease events in these groups, through the action of many different cytokines. Chronic inflammation can lead to dysfunctions in large-scale brain networks. Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis, and frontotemporal dementia, are associated with a substrate of dysregulated immune responses that impair the central nervous system balance. Recent evidence suggests that similar phenomena are involved in psychiatric diseases, such as depression, schizophrenia, autism spectrum disorders, and post-traumatic stress disorder. The present review summarizes and discusses the main evidence linking the innate immunological response in neurodegenerative and psychiatric diseases, thus providing insights into how the responses of innate immunity represent a common denominator between diseases belonging to the neurological and psychiatric sphere. Improved knowledge of such immunological aspects could provide the framework for the future development of new diagnostic and therapeutic approaches.

Clinical and Therapeutic Challenges when Psychiatric Disorders Occur in Neurological Diseases: A Narrative Review

Background:

Over the course of the 20th century, neurology and psychiatry diverged and became two separate disciplines. Subsequently, the continuous progress of neurosciences confused their boundaries. However, with ‘the splitting’ and ‘the lumping’ approaches, relevant difficulties remain in targeting clinical and therapeutic goals, when psychiatric signs and symptoms co-occur with neurological diseases.

Objective:

The study summarize current evidence on psychiatric signs and symptoms comorbid with neurological diseases, with the aim to provide information on diagnostic problems and available therapeutic options.

Methods:

Finding from searches of publications on ‘PsycInfo’, ‘Medline’, and ‘Science Direct’, from January 1993 to December 2018 (25 years) is summarized in a narrative manner on six main neurological areas: congenital neurological illnesses (n=16), dementias (n=15), basal ganglia diseases (n=30), epilepsy (n=22), strokes/focal brain injuries (n=29), and neurological neoplastic/paraneoplastic diseases (n=15).

Results:

Clinical phenotypes of psychiatric syndromes are frequently described in neurological studies. Little evidence is provided on the most adequate therapeutic approaches.

Conclusion:

Psychiatric syndromes in comorbidity with neurological diseases are heterogeneous and severe; evidence-based treatments are scarce. Despite a model supporting an equal approach between psychiatric and neurological syndromes, psychiatric syndromes in neurological diseases have been described, to a relevant degree, as less important, leading to a hierarchical primate of the neurological manifestations, and thus, in our opinion, limiting the systematic studies on psychopharmacological treatments in this area.

A neural signature of metabolic syndrome

That metabolic syndrome (MetS) is associated with age-related cognitive decline is well established. The neurobiological changes underlying these cognitive deficits, however, are not well understood. The goal of this study was to determine whether MetS is associated with regional differences in gray-matter volume (GMV) using a cross-sectional, between-group contrast design in a large, ethnically homogenous sample. T1-weighted MRIs were sampled from the genetics of brain structure (GOBS) data archive for 208 Mexican-American participants: 104 participants met or exceeded standard criteria for MetS and 104 participants were age- and sex-matched metabolically healthy controls. Participants ranged in age from 18 to 74 years (37.3 ± 13.2 years, 56.7% female). Images were analyzed in a whole-brain, voxel-wise manner using voxel-based morphometry (VBM). Three contrast analyses were performed, a whole sample analysis of all 208 participants, and two post hoc half-sample analyses split by age along the median (35.5 years). Significant associations between MetS and decreased GMV were observed in multiple, spatially discrete brain regions including the posterior cerebellum, brainstem, orbitofrontal cortex, bilateral caudate nuclei, right parahippocampus, right amygdala, right insula, lingual gyrus, and right superior temporal gyrus. Age, as shown in the post hoc analyses, was demonstrated to be a significant covariate. A further functional interpretation of the structures exhibiting lower GMV in MetS reflected a significant involvement in reward perception, emotional valence, and reasoning. Additional studies are needed to characterize the influence of MetS's individual clinical components on brain structure and to explore the bidirectional association between GMV and MetS.

Brain structural alterations are distributed following functional, anatomic and genetic connectivity

The pathological brain is characterized by distributed morphological or structural alterations in the grey matter, which tend to follow identifiable network-like patterns. We analysed the patterns formed by these alterations (increased and decreased grey matter values detected with the voxel-based morphometry technique) conducting an extensive transdiagnostic search of voxel-based morphometry studies in a large variety of brain disorders. We devised an innovative method to construct the networks formed by the structurally co-altered brain areas, which can be considered as pathological structural co-alteration patterns, and to compare these patterns with three associated types of connectivity profiles (functional, anatomical, and genetic). Our study provides transdiagnostical evidence that structural co-alterations are influenced by connectivity constraints rather than being randomly distributed. Analyses show that although all the three types of connectivity taken together can account for and predict with good statistical accuracy, the shape and temporal development of the co-alteration patterns, functional connectivity offers the better account of the structural co-alteration, followed by anatomic and genetic connectivity. These results shed new light on the possible mechanisms at the root of neuropathological processes and open exciting prospects in the quest for a better understanding of brain disorders.

Coping, stress and negative psychological outcomes in parents of children admitted to a pediatric neurorehabilitation care unit

BACKGROUND

Parents' attitudes and psychological adjustment during their child's hospitalization in a pediatric neurorehabilitation care unit are key aspects for the child's adherence to care and the impact of the disease.

AIM

The aim of this study was to examine the relationship between parenting stress, coping style, and negative psychological outcomes in families of children admitted for the first time to a pediatric neurorehabilitation care unit.

DESIGN

This is an observational study.

SETTING

Pediatric neurorehabilitation care unit.

POPULATION

One hundred twenty-four parents of children diagnosed with neurodevelopmental or neurological conditions.

METHODS

Parents completed standardized questionnaires assessing parenting stress, coping style, anxiety and depressive symptoms.

RESULTS

We found that parents of children with neurodevelopmental conditions showed more emotion-focused coping strategies (P=0.016) and depressive symptoms (P=0.01) compared with parents of children with neurological conditions. Hierarchical regression analyses showed that emotion- and avoidance-oriented coping style and socioeconomic status are crucial factors in the adjustment process of parents of children with neurodevelopmental conditions. By contrast, parenting stress and child difficulties were the most significant predictors of negative psychological outcomes in parents with neurological conditions.

CONCLUSIONS

This study sought to develop more understanding of the relationship among parenting stress, coping, and anxiety or depressive symptoms in parent of children hospitalized in a pediatric neurorehabilitation care unit. We suggest that examining parents may increase our understanding of the interplay between child and parent functioning in families with children admitted for the first time to a pediatric neurorehabilitation care unit.

CLINICAL REHABILITATION IMPACT

Identify these predictors might help professionals to develop screening procedures to identify parent at high risk for anxiety or depression, and to conduct early interventions to reduce uncertainty and maladaptive coping strategies that may influences rehabilitation process.

Transcranial magnetic stimulation of the medial prefrontal cortex for psychiatric disorders: a systematic review

Objective:

The medial prefrontal cortex (mPFC) is a highly connected cortical region that acts as a hub in major large-scale brain networks. Its dysfunction is associated with a number of psychiatric disorders, such as schizophrenia, autism, depression, substance use disorder (SUD), obsessive-compulsive disorder (OCD), and anxiety disorders. Repetitive transcranial magnetic stimulation (rTMS) studies targeting the mPFC indicate that it may be a useful therapeutic resource in psychiatry due to its selective modulation of this area and connected regions.

Methods:

This review examines six mPFC rTMS trials selected from 697 initial search results. We discuss the main results, technical and methodological details, safety, tolerability, and localization strategies.

Results:

Six different protocols were identified, including inhibitory (1 Hz) and excitatory (5, 10, and 20 Hz) frequencies applied therapeutically to patient populations diagnosed with major depressive disorder, OCD, autistic spectrum disorder, SUD, specific phobia, and post-traumatic stress disorder (PTSD). In the OCD and acrophobia trials, rTMS significantly reduced symptoms compared to placebo.

Conclusion:

These protocols were considered safe and add interesting new evidence to the growing body of mPFC rTMS literature. However, the small number and low methodological quality of the studies indicate the need for further research.

Capgras' Delusion: A Systematic Review of 255 Published Cases

BACKGROUND

Capgras' delusion has captured psychiatrists' imaginations, but the clinical features of the delusion have rarely been studied and presented systematically.

AIMS

The present study systematically reviews all case reports on Capgras' delusion in the English language in order to better understand differences between organic and functional aetiologies.

METHODS

All medical and psychiatric databases were searched, as were the bibliographies of published case reports, narrative reviews, and book chapters.

RESULTS

A total of 258 cases were identified from 175 papers. Functional Capgras' delusion was more associated with a wider variety of imposters; multiple imposters; other misidentification syndromes; auditory hallucinations; other delusions; and formal thought disorder. Organic cases were associated with age; inanimate objects; memory and visual-spatial impairments; right hemispheric dysfunction; and visual hallucinations. Executive dysfunction and aggression were associated with both types.

CONCLUSIONS

Specific features of the -Capgras' delusional content and associated signs point to either organic or functional aetiology. The delusion is more amorphous than many theorists have supposed, which challenges their explanatory models.

The alteration landscape of the cerebral cortex

Growing evidence is challenging the assumption that brain disorders are diagnostically clear-cut categories. Transdiagnostic studies show that a set of cerebral areas is frequently altered in a variety of psychiatric as well as neurological syndromes. In order to provide a map of the altered areas in the pathological brain we devised a metric, called alteration entropy (A-entropy), capable of denoting the "structural alteration variety" of an altered region. Using the whole voxel-based morphometry database of BrainMap, we were able to differentiate the brain areas exhibiting a high degree of overlap between different neuropathologies (or high value of A-entropy) from those exhibiting a low degree of overlap (or low value of A-entropy). The former, which are parts of large-scale brain networks with attentional, emotional, salience, and premotor functions, are thought to be more vulnerable to a great range of brain diseases; while the latter, which include the sensorimotor, visual, inferior temporal, and supramarginal regions, are thought to be more informative about the specific impact of brain diseases. Since low A-entropy areas appear to be altered by a smaller number of brain disorders, they are more informative than the areas characterized by high values of A-entropy. It is also noteworthy that even the areas showing low values of A-entropy are substantially altered by a variety of brain disorders. In fact, no cerebral area appears to be only altered by a specific disorder. Our study shows that the overlap of areas with high A-entropy provides support for a transdiagnostic approach to brain disorders but, at the same time, suggests that fruitful differences can be traced among brain diseases, as some areas can exhibit an alteration profile more specific to certain disorders than to others.

Semantically defined subdomains of functional neuroimaging literature and their corresponding brain regions

The functional neuroimaging literature has become increasingly complex and thus difficult to navigate. This complexity arises from the rate at which new studies are published and from the terminology that varies widely from study-to-study and even more so from discipline-to-discipline. One way to investigate and manage this problem is to build a "semantic space" that maps the different vocabulary used in functional neuroimaging literature. Such a semantic space will also help identify the primary research domains of neuroimaging and their most commonly reported brain regions. In this work, we analyzed the multivariate semantic structure of abstracts in Neurosynth and found that there are six primary domains of the functional neuroimaging literature, each with their own preferred reported brain regions. Our analyses also highlight possible semantic sources of reported brain regions within and across domains because some research topics (e.g., memory disorders, substance use disorder) use heterogeneous terminology. Furthermore, we highlight the growth and decline of the primary domains over time. Finally, we note that our techniques and results form the basis of a "recommendation engine" that could help readers better navigate the neuroimaging literature.

The morphometric co-atrophy networking of schizophrenia, autistic and obsessive spectrum disorders

By means of a novel methodology that can statistically derive patterns of co-alterations distribution from voxel-based morphological data, this study analyzes the patterns of brain alterations of three important psychiatric spectra-that is, schizophrenia spectrum disorder (SCZD), autistic spectrum disorder (ASD), and obsessive-compulsive spectrum disorder (OCSD). Our analysis provides five important results. First, in SCZD, ASD, and OCSD brain alterations do not distribute randomly but, rather, follow network-like patterns of co-alteration. Second, the clusters of co-altered areas form a net of alterations that can be defined as morphometric co-alteration network or co-atrophy network (in the case of gray matter decreases). Third, within this network certain cerebral areas can be identified as pathoconnectivity hubs, the alteration of which is supposed to enhance the development of neuronal abnormalities. Fourth, within the morphometric co-atrophy network of SCZD, ASD, and OCSD, a subnetwork composed of eleven highly connected nodes can be distinguished. This subnetwork encompasses the anterior insulae, inferior frontal areas, left superior temporal areas, left parahippocampal regions, left thalamus and right precentral gyri. Fifth, the co-altered areas also exhibit a normal structural covariance pattern which overlaps, for some of these areas (like the insulae), the co-alteration pattern. These findings reveal that, similarly to neurodegenerative diseases, psychiatric disorders are characterized by anatomical alterations that distribute according to connectivity constraints so as to form identifiable morphometric co-atrophy patterns.

The hippocampal network model: A transdiagnostic metaconnectomic approach

Purpose

The hippocampus plays a central role in cognitive and affective processes and is commonly implicated in neurodegenerative diseases. Our study aimed to identify and describe a hippocampal network model (HNM) using trans-diagnostic MRI data from the BrainMap® database. We used meta-analysis to test the network degeneration hypothesis (NDH) (Seeley et al., 2009) by identifying structural and functional covariance in this hippocampal network.

Methods

To generate our network model, we used BrainMap's VBM database to perform a region-to-whole-brain (RtWB) meta-analysis of 269 VBM experiments from 165 published studies across a range of 38 psychiatric and neurological diseases reporting hippocampal gray matter density alterations. This step identified 11 significant gray matter foci, or nodes. We subsequently used meta-analytic connectivity modeling (MACM) to define edges of structural covariance between nodes from VBM data as well as functional covariance using the functional task-activation database, also from BrainMap. Finally, we applied a correlation analysis using Pearson's r to assess the similarities and differences between the structural and functional covariance models.

Key findings

Our hippocampal RtWB meta-analysis reported consistent and significant structural covariance in 11 key regions. The subsequent structural and functional MACMs showed a strong correlation between HNM nodes with a significant structural-functional covariance correlation of r = .377 (p = .000049).

Significance

This novel method of studying network covariance using VBM and functional meta-analytic techniques allows for the identification of generalizable patterns of functional and structural abnormalities pertaining to the hippocampus. In accordance with the NDH, this framework could have major implications in studying and predicting spatial disease patterns using network-based assays.

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We derived regions that structurally co-vary with the hippocampus in a network model using a transdiagnostic meta-analytic approach.

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We used meta-analytic connectivity mapping to assess inter-regional connectivity from BrainMap's structural and functional databases.

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We tested the network degeneration hypothesis by identifying network correlations between structural and functional networks.

Systemic inflammation enhances stimulant-induced striatal dopamine elevation

Changes in the mesolimbic dopamine (DA) system are implicated in a range of neuropsychiatric conditions including addiction, depression and schizophrenia. Dysfunction of the neuroimmune system is often comorbid with such conditions and affects similar areas of the brain. The goal of this study was to use positron emission tomography with the dopamine D₂ antagonist tracer, ¹¹C-raclopride, to explore the effect of acute immune activation on striatal DA levels. DA transmission was modulated by an oral methylphenidate (MP) challenge in order to reliably elicit DA elevation. Elevation in DA concentration due to MP was estimated via change in ¹¹C-raclopride binding potential from the baseline scan. Prior to the post-MP scan, subjects were pre-treated with either the immune activator lipopolysaccharide (LPS) or placebo (PBO) in a cross-over design. Immune activation was confirmed by measuring tumor necrosis factor alpha (TNFα), interleukin (IL)-6 and IL-8 concentration in plasma. Eight healthy subjects were scanned four times each to determine the MP-induced DA elevation under both LPS and PBO pre-treatment conditions. MP-induced DA elevation in the striatum was significantly greater (P<0.01) after LPS pre-treatment compared to PBO pre-treatment. Seven of eight subjects responded similarly. This effect was observed in the caudate and putamen (P<0.02), but was not present in ventral striatum. DA elevation induced by MP was significantly greater when subjects were pre-treated with LPS compared to PBO. The amplification of stimulant-induced DA signaling in the presence of systemic inflammation may have important implications for our understanding of addiction and other diseases of DA dysfunction.

Functional connectomics from a "big data" perspective

In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of "big data", which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field.

Meta-connectomics: human brain network and connectivity meta-analyses

Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

Are neurological and psychiatric disorders different?

There have been recent calls to abandon the distinction between neurological and psychiatric disorders on philosophical and moral grounds. Crossley and colleagues, in this issue, meta-analyse published structural brain imaging data and prove that they are different after all--or do they?