Definition
Predictive processing accounts model the brain as an active prediction system: rather than passively receiving sensory input, the brain constantly generates predictions and updates itself in response to prediction errors — the mismatch between what was expected and what arrived.
Why it matters
This framework reorganizes many otherwise puzzling phenomena — pain, placebo, hallucinations, chronic anxiety, interoception — into a coherent picture. It also has real clinical implications for how change happens.
The Science
Developed and elaborated by Karl Friston, Andy Clark, Jakob Hohwy, Lisa Feldman Barrett, Anil Seth, and others, predictive processing draws on Bayesian statistics, information theory, and free-energy principles. It has strong support in perception and action, growing evidence in emotion and interoception, and remains under active investigation for more complex phenomena.
The NSI Perspective
NSI treats predictive processing as a working, powerful framework — not as settled cosmology. It illuminates without claiming to explain everything.
Clinical Implications
Framing therapy as prediction updating aligns with what many effective interventions actually do.
Practical Application
Your brain is not a camera. It is a forecaster. What you perceive is partly what your brain expected. That is not a flaw — it is design.
References
- 1.Clark A. Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behav Brain Sci. 2013;36(3):181–204.
- 2.Friston K. The free-energy principle: a unified brain theory? Nat Rev Neurosci. 2010;11(2):127–138.