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      Research Domain Criteria as Psychiatric Nosology

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      Cambridge Quarterly of Healthcare Ethics
      Cambridge University Press (CUP)

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          Abstract:

          Diagnostic classification systems in psychiatry have continued to rely on clinical phenomenology, despite limitations inherent in that approach. In view of these limitations and recent progress in neuroscience, the National Institute of Mental Health (NIMH) has initiated the Research Domain Criteria (RDoC) project to develop a more neuroscientifically based system of characterizing and classifying psychiatric disorders. The RDoC initiative aims to transform psychiatry into an integrative science of psychopathology in which mental illnesses will be defined as involving putative dysfunctions in neural nodes and networks. However, conceptual, methodological, neuroethical, and social issues inherent in and/or derived from the use of RDoC need to be addressed before any attempt is made to implement their use in clinical psychiatry. This article describes current progress in RDoC; defines key technical, neuroethical, and social issues generated by RDoC adoption and use; and posits key questions that must be addressed and resolved if RDoC are to be employed for psychiatric diagnoses and therapeutics. Specifically, we posit that objectivization of complex mental phenomena may raise ethical questions about autonomy, the value of subjective experience, what constitutes normality, what constitutes a disorder, and what represents a treatment, enablement, and/or enhancement. Ethical issues may also arise from the (mis)use of biomarkers and phenotypes in predicting and treating mental disorders, and what such definitions, predictions, and interventions portend for concepts and views of sickness, criminality, professional competency, and social functioning. Given these issues, we offer that a preparatory neuroethical framework is required to define and guide the ways in which RDoC-oriented research can—and arguably should—be utilized in clinical psychiatry, and perhaps more broadly, in the social sphere.

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          How rich functionality emerges from the invariant structural architecture of the brain remains a major mystery in neuroscience. Recent applications of network theory and theoretical neuroscience to large-scale brain networks have started to dissolve this mystery. Network analyses suggest that hierarchical modular brain networks are particularly suited to facilitate local (segregated) neuronal operations and the global integration of segregated functions. Although functional networks are constrained by structural connections, context-sensitive integration during cognition tasks necessarily entails a divergence between structural and functional networks. This degenerate (many-to-one) function-structure mapping is crucial for understanding the nature of brain networks. The emergence of dynamic functional networks from static structural connections calls for a formal (computational) approach to neuronal information processing that may resolve this dialectic between structure and function.
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              MATERIALISM AND QUALIA: THE EXPLANATORY GAP

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                Author and article information

                Journal
                applab
                Cambridge Quarterly of Healthcare Ethics
                Camb Q Healthc Ethics
                Cambridge University Press (CUP)
                0963-1801
                1469-2147
                October 2017
                September 22 2017
                October 2017
                : 26
                : 04
                : 592-601
                Article
                10.1017/S096318011700010X
                5e8021f1-c867-4929-b48f-5e0c860b9e6e
                © 2017
                History

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