Sentence examples for minimising prediction errors from inspiring English sources

This perspective casts classical motor reflexes as minimising prediction errors and may provide a principled explanation for why motor cortex is agranular.

If both systems are minimising prediction error, descending hierarchical projections in the motor cortex should share the laminar, topographic and physiological characteristics of backward connections in exteroceptive (sensory) systems.

In the first section, we review the concept of perceptual inference from a Helmholtzian perspective, and describe how it can be instantiated by minimising prediction error using a hierarchical generative model.

The free energy principle itself explains why it is necessary to minimise prediction errors.

However, there is another way to minimise prediction errors; namely, by re-sampling sensory inputs so that they conform to predictions; in other words, changing sensory inputs by changing the world through action.

To minimise prediction error, the brain should use the occurrence of the intensity and frequency deviant to prompt a change in the dominant inference ("expect-the-standard") to anticipate the characteristics of the linked deviant.

The brain can minimise prediction error in one of two ways.

Mechanistically, descending proprioceptive predictions provide a target or set point for peripheral reflex arcs – that respond by minimising (proprioceptive) prediction errors.

So far, we have only considered the role of predictive coding in perception through minimising surprise or prediction errors.

In conclusion, we have argued that the cortex is best regarded as embodying a hierarchical generative model, whose descending (efferent) projections predict and explain sensory inputs, thus minimising ascending (afferent) prediction errors.

This means that minimising free energy through active inference implicitly minimises surprise (or prediction errors), which is the same as maximising Bayesian model evidence.