Predictive Processing in the Brain: A Comprehensive Review

AbstractThis paper explores the hypothesis that human perception is not merely a response to sensory input but a proactive predictive process governed by dynamic neural mechanisms. Drawing on evidence from neuroimaging studies (fMRI, EEG) and predictive coding theory, we introduce the Unified Dynamic Model of Mind (UDMM) as a comprehensive framework that reconceptualizes perception through a Top-Down Processing approach.In this model, the brain operates as an active simulator, generating expectations about reality before receiving sensory input. These expectations are then tested and refined based on Prediction Error Signals, adjusting cognitive models accordingly. Findings from schizophrenia and autism research indicate that deficits in updating predictions may underlie atypical perceptual experiences.This paper provides an analytical review of the neurophysiological and behavioral evidence supporting UDMM, comparing it with traditional Bottom-Up Processing models. Finally, we discuss potential applications of UDMM in artificial intelligence, clinical psychology, and the design of machine learning systems that mimic human perception.1. IntroductionPerception has long been understood as a process by which the brain passively receives and interprets sensory information. Traditional Bottom-Up models suggest that perception begins with raw sensory inputs, which are then processed hierarchically to construct a coherent representation of reality. However, recent advancements in neuroscience challenge this notion, proposing instead that perception is fundamentally predictive—a hypothesis supported by growing evidence from neuroimaging, computational modeling, and psychopathology research (Clark, 2013; Friston, 2018).2. Theoretical BackgroundPredictive coding theory posits that the brain continuously generates expectations about incoming sensory data, using these predictions to minimize prediction error signals—discrepancies between expected and actual sensory input. This framework suggests that perception is not merely reactive but proactive, driven by the brain’s attempts to confirm or revise its internal models of the world (Friston, 2010; Knill & Pouget, 2004).