Cognitive biases as an adaptive strategy in autism and schizophrenia spectrum: the compensation perspective on neurodiversity

Recent public discussions suggest that there is much disagreement about the way autism is and should be described. This study sought to elicit the views and preferences of UK autism community members - autistic people, parents and their broader support network - about the terms they use to describe autism. In all, 3470 UK residents responded to an online survey on their preferred ways of describing autism and their rationale for such preferences. The results clearly show that people use many terms to describe autism. The most highly endorsed terms were 'autism' and 'on the autism spectrum', and to a lesser extent, 'autism spectrum disorder', for which there was consensus across community groups. The groups disagreed, however, on the use of several terms. The term 'autistic' was endorsed by a large percentage of autistic adults, family members/friends and parents but by considerably fewer professionals; 'person with autism' was endorsed by almost half of professionals but by fewer autistic adults and parents. Qualitative analysis of an open-ended question revealed the reasons underlying respondents' preferences. These findings demonstrate that there is no single way of describing autism that is universally accepted and preferred by the UK's autism community and that some disagreements appear deeply entrenched.

To use sensory information efficiently to make judgments and guide action in the world, the brain must represent and use information about uncertainty in its computations for perception and action. Bayesian methods have proven successful in building computational theories for perception and sensorimotor control, and psychophysics is providing a growing body of evidence that human perceptual computations are "Bayes' optimal". This leads to the "Bayesian coding hypothesis": that the brain represents sensory information probabilistically, in the form of probability distributions. Several computational schemes have recently been proposed for how this might be achieved in populations of neurons. Neurophysiological data on the hypothesis, however, is almost non-existent. A major challenge for neuroscientists is to test these ideas experimentally, and so determine whether and how neurons code information about sensory uncertainty.

Several studies and meta-analyses have shown that mortality in people with schizophrenia is higher than that in the general population but have used relative measures, such as standardised mortality ratios. We did a systematic review and meta-analysis to estimate years of potential life lost and life expectancy in schizophrenia, which are more direct, absolute measures of increased mortality.