Neural Networks And Psychopathology

Research on connectionist models is one of the most exciting areas in cognitive science, and neural network models of psychopathology have immediate theoretical and empirical appeal. The contributors to this study review theoretical, historical and clinical issues, including the contribution of neural network models to diagnosis, pharmacotherapy and psychotherapy. Models are presented for a range of disorders, including schizophrenia, obsessive-compulsive disorder, dissociative phenomena, autism and Alzheimer's disease. This book will appeal to a broad audience. On the one hand, it will be read with interest by psychiatrists, psychologists and other clinicians and researchers in psychopathology. On the other, it will appeal to those working in cognitive science and artificial intelligence, and particularly those interested in neural network or connectionist models.

This book provides a comprehensive review of new developments in the study of language processing and related neural networks in schizophrenia by addressing the complex link between psychopathology, language and evolution at different levels of analysis. Psychopathological symptoms in schizophrenia are mainly characterized by thought and language disorders, which are strictly intertwined. In particular, language is the distinctive dimension of human beings and is ontologically related to brain development. Although normal at the levels of segmental phonology and morphological organization, the speech of patients suffering from schizophrenia is often characterized by flattened intonation and word-finding difficulties. Furthermore, research suggests that the superior temporal gyrus and specific prefrontal areas which support language in humans are altered in people with schizophrenia. Brambilla and Marini bring together international contributors to explore the link between brain evolution and the psychopathological features of schizophrenia, with a focus on language and its neural underpinnings. Divided into three sections the book covers: • brain evolution and language phylogenesis • brain abnormalities in schizophrenia • psychopathology and schizophrenia. This theoretical approach will appeal to professionals including clinical psychologists, cognitive neuroscientists, neuropsychiatrists, neuropsychologists, neurolinguists, and researchers considering the links between brain evolution, language and psychopathology in schizophrenia.

"This encyclopedia distills an amazing amount of information into a book that is easy to read and navigateÖ.This would serve as a great reference for anyone with an interest in depression." Score: 96, 4 stars --Doody's Depression is the second most disabling disorder in the world. On a daily basis, virtually all mental health professionals confront patients with primary or secondary depression. The wealth of information available globally on depression is enormous, but has not been summarized into a comprehensive encyclopedia-until now. Experts from around the globe have been selected to present interdisciplinary coverage of all the essential issues related to depression, including use of medication, treatment therapies and models, symptoms of Depression, related disorders, and more. Entries are conveniently organized into subcategories in order to provide the most in-depth coverage of each subject. Entries include: Adolescent Depression Behavioral Treatment Cognitive therapy Dopamine Double Depression Heredity Human Immuno-deficiency Virus (HIV) Personality Disorders Smoking Suicide Warning Signs In summarizing the vast amount of information on depression, The International Encyclopedia of Depression serves as an authoritative resource for researchers, patients, students, and laypeople.

Cognition and artificial intelligence are entering a new era in which the aspects of symbolic manipulation and of connectionism begin to come together. This leads to a dialog of truly interdisciplinary character. The book covers aspects of fuzzy logic, case based reasoning, learning as well as meaning, language, and consciousness. The authors of this topical volume have their background in logic, computer science, physics and mathematics, philosophy, psychology and neurobiology.

There is a growing appreciation that many psychiatric (and neurological) conditions can be understood as functional disconnection syndromes – as reflected in aberrant functional integration and synaptic connectivity. This Research Topic considers recent advances in understanding psychopathology in terms of aberrant effective connectivity – as measured noninvasively using functional magnetic resonance imaging (fMRI). Recently, there has been increasing interest in inferring directed connectivity (effective connectivity) from fMRI data. Effective connectivity refers to the influence that one neural system exerts over another and quantifies the directed coupling among brain regions – and how they change with pathophysiology. Compared to functional connectivity, effective connectivity allows one to understand how brain regions interact with each other in terms of context sensitive changes and directed coupling – and therefore may provide mechanistic insights into the neural basis of psychopathology. Established models of effective connectivity include psychophysiological interaction (PPI), structural equation modeling (SEM) and dynamic causal modelling (DCM). DCM is unique because it explicitly models the interaction among brain regions in terms of latent neuronal activity. Moreover, recent advances in DCM such as stochastic and spectral DCM, make it possible to characterize the interaction between different brain regions both at rest and during a cognitive task.

This innovative work explores integrating emerging research into how the brain processes information in applied therapeutic interventions. Typically, clinicians select therapeutic interventions based on their own training, personal experience or preference. This book aims to provide a new model, based upon the neural networks, to both understand the development of mental health issues and their persistence, and how and why to apply therapeutic interventions to impact the systems which are maintaining them. This work begins with a short and accessible overview of the neural network model, and the general aims of therapy. It elucidates components of the neural network model of learning such as reward recognition, automaticity, and memory reconsolidation, and how they apply to both general learning and new learning through the process in therapy. Next, the authors explore how the neural network model can be integrated across existing systems of therapy, including Cognitive Behavior therapy (CBT), Dialectical Behavior Therapy (DBT), third wave therapies and analytic therapies. Therapy and the Neural Network Model is an exciting resource for researchers and practitioners interested in understanding more about the applications of a neural network model for therapy and the how and why of building new mentally healthy cognitions, behaviors and emotions. Therapy and the Neural Network Model is also an essential theoretical foundation for both researchers and practitioners who wish to base their therapeutic practice on neuroscience and integrate their work with related fields such as behavioral medicine, health psychology, social work and public health.