<p>Perceptual multistability, where constant sensory input yields alternating interpretations, reveals the brain’s inferential processes under ambiguity. Here we review evidence positioning multistability within the predictive coding framework, which models perception as hierarchical inference minimizing prediction errors between sensory input and top-down expectations. Neuroimaging, electrophysiology, and computational models indicate that perceptual alternations arise from dynamic cycles of prediction and error correction, mediated by oscillatory cortical interactions. Individual differences in switching dynamics correlate with cognitive traits and clinical conditions, reflecting variability in the precision weighting of sensory evidence and prior information. These findings suggest that multistable perception provides a valuable paradigm to investigate the neural and computational mechanisms of perception, cognition, and psychopathology. Understanding these dynamics may inform unified models bridging neuroscience, psychology, and clinical research, and guide future studies employing falsifiable predictive coding hypotheses.</p>