Abstract
Research into the biological basis of emotional and motivational disorders is in danger of riding roughshod over a patient-centered psychiatry and falling into the dualist errors of the past, i.e., by treating mind and brain as conceptually distinct. We argue that a psychiatry informed by computational neuroscience, computational psychiatry, can obviate this danger. Through a focus on the reasoning processes by which humans attempt to maximize reward (and minimize punishment), and how such reasoning is expressed neurally, computational psychiatry can render obsolete the polarity between biological and psychosocial conceptions of illness. Here, the term ‘psychological’ comes to refer to information processing performed by biological agents, seen in light of underlying goals. We reflect on the implications of this perspective for a definition of mental disorder, including what is entailed in asserting that a particular disorder is ‘biological’ or ‘psychological’ in origin. We propose that a computational approach assists in understanding the topography of mental disorder, while cautioning that the point at which eccentric reasoning constitutes disorder often remains a matter of cultural judgment.
Highlights
The idea that reward processing is important in emotional and motivational psychiatric disorders comes from a view of the mind-as-decision-maker
This idea has been developed within the nascent field of computational psychiatry, the clinical offshoot of computational neurobiology
In this article we argue that computational psychiatry has already
Summary
The idea that reward processing is important in emotional and motivational psychiatric disorders comes from a view of the mind-as-decision-maker. This idea has been developed within the nascent field of computational psychiatry, the clinical offshoot of computational neurobiology. Within this framework, ‘psychiatric disorder’ entails a breakdown in the brain’s inability to optimize decisions. As an approach computational psychiatry promises much by way of future diagnostic and therapeutic applications (Huys et al, 2011; Montague et al, 2012). We are mindful that psychiatry has seen many promising directions that have delivered much less than hoped. In this article we argue that computational psychiatry has already
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