Space is a latent sequence: A theory of the hippocampus.
Rajkumar Vasudeva RajuJ Swaroop GuntupalliGuangyao ZhouCarter WendelkenMiguel Lázaro-GredillaDileep GeorgePublished in: Science advances (2024)
Fascinating phenomena such as landmark vector cells and splitter cells are frequently discovered in the hippocampus. Without a unifying principle, each experiment seemingly uncovers new anomalies or coding types. Here, we provide a unifying principle that the mental representation of space is an emergent property of latent higher-order sequence learning. Treating space as a sequence resolves numerous phenomena and suggests that the place field mapping methodology that interprets sequential neuronal responses in Euclidean terms might itself be a source of anomalies. Our model, clone-structured causal graph (CSCG), employs higher-order graph scaffolding to learn latent representations by mapping aliased egocentric sensory inputs to unique contexts. Learning to compress sequential and episodic experiences using CSCGs yields allocentric cognitive maps that are suitable for planning, introspection, consolidation, and abstraction. By explicating the role of Euclidean place field mapping and demonstrating how latent sequential representations unify myriad observed phenomena, our work positions the hippocampus in a sequence-centric paradigm, challenging the prevailing space-centric view.
Keyphrases
- induced apoptosis
- high resolution
- cell cycle arrest
- cerebral ischemia
- working memory
- mental health
- high density
- cognitive impairment
- prefrontal cortex
- signaling pathway
- amino acid
- convolutional neural network
- machine learning
- subarachnoid hemorrhage
- neural network
- cell death
- pi k akt
- blood brain barrier
- deep learning