4.6 Article

The neurobiology of functional neurological disorders characterised by impaired awareness

Journal

FRONTIERS IN PSYCHIATRY
Volume 14, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fpsyt.2023.1122865

Keywords

FND; Bayesian; theoretical neurobiology; predictive coding; brain modelling; resignation syndrome

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This article reviews the neurobiology of Functional Neurological Disorders (FND) and focuses on those with impaired awareness, particularly Resignation Syndrome (RS). By integrating clinical material and neuro-computational insights, a more coherent theory of FIAD is presented, considering factors such as stress, attention, uncertainty, and beliefs. The historical development and social context of FIAD are also explored. Future research directions and implications for clinical diagnosis and management are discussed.
We review the neurobiology of Functional Neurological Disorders (FND), i.e., neurological disorders not explained by currently identifiable histopathological processes, in order to focus on those characterised by impaired awareness (functionally impaired awareness disorders, FIAD), and especially, on the paradigmatic case of Resignation Syndrome (RS). We thus provide an improved more integrated theory of FIAD, able to guide both research priorities and the diagnostic formulation of FIAD. We systematically address the diverse spectrum of clinical presentations of FND with impaired awareness, and offer a new framework for understanding FIAD. We find that unraveling the historical development of neurobiological theory of FIAD is of paramount importance for its current understanding. Then, we integrate contemporary clinical material in order to contextualise the neurobiology of FIAD within social, cultural, and psychological perspectives. We thus review neuro-computational insights in FND in general, to arrive at a more coherent account of FIAD. FIAD may be based on maladaptive predictive coding, shaped by stress, attention, uncertainty, and, ultimately, neurally encoded beliefs and their updates. We also critically appraise arguments in support of and against such Bayesian models. Finally, we discuss implications of our theoretical account and provide pointers towards an improved clinical diagnostic formulation of FIAD. We suggest directions for future research towards a more unified theory on which future interventions and management strategies could be based, as effective treatments and clinical trial evidence remain limited.

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