Space is a latent sequence: A theory of the hippocampus

被引:3
|
作者
Raju, Rajkumar Vasudeva [1 ]
Guntupalli, J. Swaroop [1 ]
Zhou, Guangyao [1 ]
Wendelken, Carter [1 ]
Lazaro-Gredilla, Miguel [1 ]
George, Dileep [1 ]
机构
[1] Google DeepMind, Mountain View, CA 94043 USA
来源
SCIENCE ADVANCES | 2024年 / 10卷 / 31期
关键词
PLACE CELLS; FIRING PROPERTIES; ENVIRONMENT; REPRESENTATION; INFERENCE; CONTEXT; MEMORY; TRIAL; MAPS; TIME;
D O I
10.1126/sciadv.adm8470
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:16
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