The myth of the Bayesian brain
Madhur Mangalam
Abstract
The Bayesian brain hypothesis-the idea that neural systems implement or approximate Bayesian inference-has become a dominant framework in cognitive neuroscience over the past two decades. While mathematically elegant and conceptually unifying, this paper argues that the hypothesis occupies an ambiguous territory between useful metaphor and testable, biologically plausible mechanistic explanation. We critically examine the key claims of the Bayesian brain hypothesis, highlighting issues of unfalsifiability, biological implausibility, and inconsistent empirical support. The framework's remarkable flexibility in accommodating diverse findings raises concerns about its explanatory power, as models can often be adjusted post hoc to fit virtually any data pattern. We contrast the Bayesian approach with alternative frameworks, including dynamic systems theory, ecological psychology, and embodied cognition, which conceptualize prediction and adaptive behavior without recourse to probabilistic inference. Despite its limitations, the Bayesian brain hypothesis persists-driven less by empirical grounding than by its mathematical elegance, metaphorical power, and institutional momentum.