Binding in Hippocampal-entorhinal Circuits Enables Compositionality in Cognitive MapsShow others and affiliations
2024 (English)In: Advances in Neural Information Processing Systems 38 (NeurIPS 2024): Proceedings of the international conference "Neural Information Processing Systems 2024", Curran Associates, Inc., Neural Information Processing Systems Foundation Inc , 2024, Vol. 38Conference paper, Published paper (Refereed)
Abstract [en]
We propose a normative model for spatial representation in the hippocampal formation that combines optimality principles, such as maximizing coding range and spatial information per neuron, with an algebraic framework for computing in distributed representation. Spatial position is encoded in a residue number system, with individual residues represented by high-dimensional, complex-valued vectors. These are composed into a single vector representing position by a similarity-preserving, conjunctive vector-binding operation. Self-consistency between the vectors representing position and the individual residues is enforced by a modular attractor network whose modules correspond to the grid cell modules in entorhinal cortex. The vector binding operation can also be used to bind different contexts to spatial representations, yielding a model for entorhinal cortex and hippocampus. We provide model analysis of scaling, similarity preservation and convergence behavior as well as experiments demonstrating noise robustness, sub-integer resolution in representing position, and path integration. The model formalizes the computations in the cognitive map and makes testable experimental predictions.
Place, publisher, year, edition, pages
Curran Associates, Inc., Neural Information Processing Systems Foundation Inc , 2024. Vol. 38
Series
Advances in Neural Information Processing Systems, ISSN 1049-5258 ; 38
Keywords [en]
cognitive maps, compositionality, hippocampus, entorhinal cortex
National Category
Computer Sciences Neurosciences
Identifiers
URN: urn:nbn:se:oru:diva-117704OAI: oai:DiVA.org:oru-117704DiVA, id: diva2:1919547
Conference
38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, December 10-15, 2024
Funder
EU, Horizon 2020, 839179
Note
The work of CJK was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate (NDSEG) Fellowship Program. The work of SM was carried out as part of the ARPE program of ENS Paris-Saclay and supported by the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement HORIZON-INFRA-2022-SERV-B-01. The work of DK and BAO was supported in part by Intel’s THWAI program. The work of CJK and BAO was supported by the Center for the Co-Design of Cognitive Systems (CoCoSys), one of seven centers in JUMP 2.0, a Semiconductor Research Corporation (SRC) program sponsored by DARPA, as well as NSF awards 2147640 and 2313149. DK has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 839179. FTS discloses support for the research of this work from NIH grant 1R01EB026955-0.
2024-12-092024-12-092024-12-10Bibliographically approved