Brains as Prediction Machines

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The brain forms perceptions based on sparse sensory data and is considered a prediction machine. This concept traces back to ancient philosophy, viewing perception as an interpretation of reality that is ultimately unknowable. In psychology, the brain is likened to an inference engine, perceiving through a process of unconscious inference. Sensory signals received by the brain are ambiguous and noise-filled, prompting the brain to engage in Bayesian inference to determine the most likely causes of the signals.

Those of us who think that that the laws of physics underlying everyday life are completely known tend to also think that consciousness is an emergent phenomenon that must be compatible with those laws. To hold such a position in a principled way, it’s important to have a clear understanding of “emergence” and when it happens. Anil Seth is a leading researcher in the neuroscience of consciousness, who has also done foundational work (often in collaboration with Lionel Barnett) on what emergence means. We talk about information theory, entropy, and what they have to do with how things emerge.

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Anil Seth received his D.Phil in Computer Science and Artificial Intelligence from the University of Sussex. He is currently a professor of cognitive and computational neuroscience at Sussex, as well as co-director of the Sackler Centre for Consciousness Science. He has served as the president of the Psychology Section of the British Science Association, and is Editor-in-Chief of the journal Neuroscience of Consciousness. His new book is Being You: A New Science of Consciousness.

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