Collection Thirteen: Predictive Processing

Sensory Uncertainty

Sensory Uncertainty within predictive processing — the science, the human experience, and why it belongs inside a Nervous System Intelligence framework.

Article #243·● Published·8 min read·Foundational

Definition

Sensory uncertainty is the noise, ambiguity, and incompleteness of the signals reaching the brain. Perception is the brain’s best inference under uncertainty, not a direct readout of the world.

Why it matters

Recognizing uncertainty as intrinsic to perception explains hallucinations, illusions, dreams, and the ordinary way in which two people can honestly see the same event differently.

The Science

Bayesian models of perception show that percepts weight priors and sensory data by their relative precision. When sensory data are noisy, priors dominate; when data are precise, they dominate.

The NSI Perspective

NSI holds sensory uncertainty as a normal condition. Perception is inference, not photography.

Clinical Implications

Understanding hallucinations and misperceptions in this framework reduces stigma and improves conversations about symptoms.

Practical Application

The gap between what you see and what is there is not evidence of failure. It is the ordinary condition of a predicting brain.

References

  1. 1.Körding KP, Wolpert DM. Bayesian integration in sensorimotor learning. Nature. 2004;427(6971):244–247.