The latest neuroscience explores autism using the predictive processing framework. The core idea of this framework is that the human brain is a powerful prediction engine, constantly guessing what's happening inside and around us. It's a bit like a game of "What happens next?"—where the brain uses a layered system, predicting how our senses will experience the world. When things don’t match up, error signals shoot up from the senses, helping the brain fine-tune its guesses. Our perception of the world is driven by a learned model of reality, shaped by Bayesian logic, best guesses based on prior experiences.

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Autistic brains are different. We struggle to flexibly adjust and update our predictive models of the world, leading to more frequent and intense error signals, called prediction errors. As a result, the autistic brain overweights the importance  of current sensory information to explain things,  which creates big responses to changes in the environment and things like sound, smell and touch. Where the non-autistic brain asks "What happens next?", the autistic brain, anchored in the present by sensory stimuli and noticing everything, spends more time asking "What was that?". The traits and characteristics we see in autistics are the result of a brain searching for predictability.