Predictions, perception, and a sense of self

Abstract

In recent years there has been a paradigm shift in theoretical neuroscience in which the brain-as a passive processor of sensory information-is now considered an active organ of inference, generating predictions and hypotheses about the causes of its sensations. In this commentary, we try to convey the basic ideas behind this perspective, describe their neurophysiologic underpinnings, and highlight the potential importance of this formulation for clinical neuroscience. The formalism it provides-and the implementation of active inference in the brain-may have the potential to reveal aspects of functional neuroanatomy that are compromised in conditions ranging from Parkinson disease to schizophrenia. In particular, many neurologic and neuropsychiatric conditions may be understandable in terms of a failure to modulate the postsynaptic gain of neuronal populations reporting prediction errors during action and perception. From the perspective of the predictive brain, this represents a failure to encode the precision of-or confidence in-sensory information. We propose that the predictive or inferential perspective on brain function offers novel insights into brain diseases.

Figure. Hierarchical message passing in the brain

(A) This figure summarizes the architecture of neuronal message passing that underlies predictive coding in the brain.^, The postulate is that neuronal activity encodes expectations about the causes of sensory input and these expectations attempt to minimize prediction error. Prediction error is simply the difference between (bottom-up) sensory input and (top-down) predictions of that input. This minimization rests on recurrent neuronal interactions between different levels of the cortical hierarchy in which bottom-up signals relay prediction error to higher levels, which respond by changing expectations to provide better top-down predictions (optimization of the posterior expectations or beliefs). This is a relatively simple and neuronally plausible scheme for which there is a large amount of circumstantial evidence. This evidence suggests that superficial pyramidal cells in the upper layers of cortex (green triangles) compare expectations at each hierarchical level (or sensory input at the lowest level) with top-down predictions from deep pyramidal cells (black triangles) of higher levels. The resulting prediction error is then returned to the deep pyramidal cells so that they can change their predictions. (B) This schematic shows a simple segment of the cortical hierarchy with ascending prediction errors and descending predictions. Here we have included neuromodulatory gating or gain control (red) on superficial pyramidal cells that determines their relative influence on deep pyramidal cells encoding expectations. (C) This provides a particular example focusing on the visual system. The black arrows denote descending (or backward) connections that convey predictions. The green arrows denote ascending (or forward) driving connections from cells of a lower area to a higher area that convey prediction errors. The prediction errors are weighted by their expected precision, which depends on neuromodulatory input—here from ventral tegmental area (VTA) and substantia nigra (SN). Predictions try to cancel (or at least reduce) prediction errors in lower levels. In this example, extrastriate visual cortex sends (top-down) predictions to primary visual cortex, which then sends predictions to the lateral geniculate body. Extrastriate visual cortex also sends (proprioceptive) predictions to the pontine nuclei. These predictions are transmitted to the oculomotor system to produce movement through classical reflexes. Predictions from the pontine nuclei are also sent to the lateral geniculate body (c.f., corollary discharge). Every top-down (descending) prediction is reciprocated with a bottom-up (ascending) prediction error to ensure that predictions are constrained by sensations. Thus the minimization of prediction error occurs at all levels of the cortical and subcortical hierarchy and at the level of peripheral reflexes. 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. In other words, the proprioceptive prediction errors about the oculomotor system eliminate themselves directly through peripheral motor reflexes.