The Integrative Brain: Functional Units in Predictive Processing
Matthew C. L. Phillips · Journal of Integrative Neuroscience · 2025
Predictive processing asserts that the brain learns a generative model of the world, which it uses to make sensory-updated predictions about reality. While traditional views emphasize the cerebral cortex, prediction is a fundamental brain principle, which underscores the vital role of older subcortical structures. This review offers a framework for understanding the brain as an integrated system of semi-independent cortical and subcortical functional units that collectively enable predictive processing. The cerebral cortex is positioned as the primary driver of subconscious predictions, whereas the thalamus, hippocampal complex, amygdala, basal ganglia, and cerebellum contribute critical indirect roles by translating the predictions into conscious, cohesive, and coordinated experiences and behaviours. Specifically, the thalamus controls and establishes selective attention by synchronizing multiple cortical regions, enabling attended predictions to be expressed into conscious perception and cognition; the hippocampal complex captures novelty and constructs episodic simulations, which represent highly abstract or hypothetical predictions that contribute to the conscious cognitive experience; and the amygdala appraises motivational value and activates emotional states, which predict survival-critical events and prime the brain for action, contributing to a subjective emotional experience. During this translation, the basal ganglia and cerebellum contribute sculpting roles, with the basal ganglia chunking predictions into repertoires, facilitating the cohesive expression of actions, and potentially perceptual, cognitive, and emotional experiences, while the cerebellum generates and adjusts temporal predictions, enabling the coordinated expression of actions and experiences. This integrative framework highlights the essential, often-overlooked contributions of subcortical units to predictive processing, providing a unified model for future research.