The hippocampus as a “Tolman-Eichenbaum Machine” https://pubmed.ncbi.nlm.nih.gov/33181068/Neuroskeptic on Twitter: “The hippocampus as a “Tolman-Eichenbaum Machine” https://t.co/9FBX2d0WEz https://t.co/v15ougEKtf” / Twitter
Cell. 2020 Nov 5;S0092-8674(20)31388-X. doi: 10.1016/j.cell.2020.10.024. Online ahead of print.
The Tolman-Eichenbaum Machine: Unifying Space and Relational Memory through Generalization in the Hippocampal Formation
- PMID: 33181068
- DOI: 10.1016/j.cell.2020.10.024
The hippocampal-entorhinal system is important for spatial and relational memory tasks. We formally link these domains, provide a mechanistic understanding of the hippocampal role in generalization, and offer unifying principles underlying many entorhinal and hippocampal cell types. We propose medial entorhinal cells form a basis describing structural knowledge, and hippocampal cells link this basis with sensory representations. Adopting these principles, we introduce the Tolman-Eichenbaum machine (TEM). After learning, TEM entorhinal cells display diverse properties resembling apparently bespoke spatial responses, such as grid, band, border, and object-vector cells. TEM hippocampal cells include place and landmark cells that remap between environments. Crucially, TEM also aligns with empirically recorded representations in complex non-spatial tasks. TEM also generates predictions that hippocampal remapping is not random as previously believed; rather, structural knowledge is preserved across environments. We confirm this structural transfer over remapping in simultaneously recorded place and grid cells.
Keywords: entorhinal cortex; generalization; grid cells; hippocampus; neural networks; non-spatial reasoning; place cells; representation learning.