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Abstract

Advances in cognitive neuroscience offer us new ways to understand the symptoms of mental illness by uniting basic neurochemical and neurophysiological observations with the conscious experiences that characterize these symptoms. Cognitive theories about the positive symptoms of schizophrenia--hallucinations and delusions--have tended to treat perception and belief formation as distinct processes. However, recent advances in computational neuroscience have led us to consider the unusual perceptual experiences of patients and their sometimes bizarre beliefs as part of the same core abnormality--a disturbance in error-dependent updating of inferences and beliefs about the world. We suggest that it is possible to understand these symptoms in terms of a disturbed hierarchical Bayesian framework, without recourse to separate considerations of experience and belief.

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Schizophrenia: a concise overview of incidence, prevalence, and mortality.

J. McGrath, S. Saha, D. CHANT … (2008)

Recent systematic reviews have encouraged the psychiatric research community to reevaluate the contours of schizophrenia epidemiology. This paper provides a concise overview of three related systematic reviews on the incidence, prevalence, and mortality associated with schizophrenia. The reviews shared key methodological features regarding search strategies, analysis of the distribution of the frequency estimates, and exploration of the influence of key variables (sex, migrant status, urbanicity, secular trend, economic status, and latitude). Contrary to previous interpretations, the incidence of schizophrenia shows prominent variation between sites. The median incidence of schizophrenia was 15.2/100,000 persons, and the central 80% of estimates varied over a fivefold range (7.7-43.0/100,000). The rate ratio for males:females was 1.4:1. Prevalence estimates also show prominent variation. The median lifetime morbid risk for schizophrenia was 7.2/1,000 persons. On the basis of the standardized mortality ratio, people with schizophrenia have a two- to threefold increased risk of dying (median standardized mortality ratio = 2.6 for all-cause mortality), and this differential gap in mortality has increased over recent decades. Compared with native-born individuals, migrants have an increased incidence and prevalence of schizophrenia. Exposures related to urbanicity, economic status, and latitude are also associated with various frequency measures. In conclusion, the epidemiology of schizophrenia is characterized by prominent variability and gradients that can help guide future research.

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A free energy principle for the brain.

Karl Friston, James M. Kilner, Lee C. Harrison (2006)

By formulating Helmholtz's ideas about perception, in terms of modern-day theories, one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts: using constructs from statistical physics, the problems of inferring the causes of sensory input and learning the causal structure of their generation can be resolved using exactly the same principles. Furthermore, inference and learning can proceed in a biologically plausible fashion. The ensuing scheme rests on Empirical Bayes and hierarchical models of how sensory input is caused. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of cortical organisation and responses. In this paper, we show these perceptual processes are just one aspect of emergent behaviours of systems that conform to a free energy principle. The free energy considered here measures the difference between the probability distribution of environmental quantities that act on the system and an arbitrary distribution encoded by its configuration. The system can minimise free energy by changing its configuration to affect the way it samples the environment or change the distribution it encodes. These changes correspond to action and perception respectively and lead to an adaptive exchange with the environment that is characteristic of biological systems. This treatment assumes that the system's state and structure encode an implicit and probabilistic model of the environment. We will look at the models entailed by the brain and how minimisation of its free energy can explain its dynamics and structure.