Predictive Coding in Neuroscience & Generative AI Cognitive Architecture: Bayesian Brain Models, Active Inference, and Neural Networks Parallelism

# Predictive Coding in Neuroscience & Generative AI Cognitive Architecture: Bayesian Brain Models, Active Inference, and Neural Networks Parallelism

An exhaustive theoretical and computational breakdown of the predictive brain hypothesis: Helmholtz's unconscious inference, Karl Friston's Free Energy Principle and variational Bayesian mechanics, laminar cortical circuitry (layers 1-6), deep structural parallels with autoregressive Next-Token transformers and diffusion latent spaces, the neurobiology of illusions and dreams as controlled hallucinations, and future implications for ultra-low-power neuromorphic active inference robotics.