Figure 2.

This figure summarizes the hierarchical neuronal message passing that underlies predictive coding. The basic idea is that neuronal activity encodes expectations about the causes of sensory input, where these expectations minimize prediction error. Prediction error is the difference between (ascending) sensory input and (descending) predictions of that input. This minimization rests upon recurrent neuronal interactions between different levels of the cortical hierarchy. Current interpretations suggest that superficial pyramidal cells (red triangles) compare the expectations (at each level) with top-down predictions from deep pyramidal cells (black triangles) of higher levels [22,23]. On the left: this schematic shows a simple cortical hierarchy with ascending prediction errors and descending predictions. This graphic includes neuromodulatory gating or gain control (blue) of superficial pyramidal cells that determines their relative influence on deep pyramidal cells encoding expectations through modulation of expected precision (see below and text for details). On the right: this provides a schematic example in the visual system. It shows the putative cells of origin of ascending or forward connections that convey prediction errors (red arrows) and descending or backward connections (black arrows) that construct predictions. The prediction errors are weighted by their expected precision that we have associated with the activity of neuromodulatory systems—here projections from ventral tegmental area (VTA) and substantia nigra (STN). In this example, the frontal eye fields send predictions to primary visual cortex, which it projects to the lateral geniculate body. However, the frontal eye fields also send proprioceptive predictions to pontine nuclei, which are passed to the oculomotor system to cause movement through classical reflexes. These descending predictions are also passed to the lateral geniculate body and constitute corollary discharge. Every top-down prediction is reciprocated with a bottom-up prediction error to ensure predictions are constrained by sensory information. The resolution of proprioceptive prediction error is particularly important because this enables descending predictions—about the state of the body—to cause movement by dynamically resetting the equilibrium or set-point of classical reflexes. Resolving sensory prediction errors through action is known as active inference (see the text). Adapted from Friston [26]. (Online version in colour.)