The Hippocampal Latent Diffusion Engine: A Computational Framework for Memory, Perception, and Cognitive Dysfunction

The hippocampus is a cognitive hub whose functions are disrupted in most major neurodegenerative dementias. Despite substantial knowledge of its anatomy, physiology, and circuitry, a unifying account that links hippocampal computations, functions and clinical manifestations is lacking. Drawing on recent advances in generative artificial intelligence and systems neuroscience, we conceptualize the hippocampus as a latent diffusion engine that compresses sensory, internal, and cognitive inputs into low-dimensional representations and then regenerates percepts, episodic memories, and imagined scenes for cortical integration. Travelling waves of cortico-hippocampal oscillations, aligned with large-scale functional gradients, schedule and structure this generative process, organizing distributed neural activity into coherent, semantically grounded constructs. Specifically, we propose a stochastic latent oscillatory diffusion (SLOD) framework that maps specific hippocampal–cortical computations onto biological substrates and dynamical processes. The computational architecture mirrors the dominant text-to-image generative AI algorithms (specifically latent diffusion models), adapted and translated into the biological embedding of the cortex and hippocampus. Finally, we demonstrate how major neurodegenerative dementias - including the Alzheimer’s disease spectrum, dementia with Lewy bodies, and the frontotemporal dementia spectrum - can be interpreted as selective breakdowns of the anatomical and computational components of this proposed architecture.