UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Actionable Neural Representations: Grid Cells from Minimal Constraints

Dorrell, Will; Latham, Peter; Behrens, Timothy EJ; Whittington, James CR; (2023) Actionable Neural Representations: Grid Cells from Minimal Constraints. In: Proceedings of the Eleventh International Conference on Learning Representations. (pp. pp. 1-47). ICLR (In press). Green open access

[thumbnail of 6321_actionable_neural_representati.pdf]
Preview
Text
6321_actionable_neural_representati.pdf - Accepted Version

Download (12MB) | Preview

Abstract

To afford flexible behaviour, the brain must build internal representations that mirror the structure of variables in the external world. For example, 2D space obeys rules: the same set of actions combine in the same way everywhere (step north, then south, and you won’t have moved, wherever you start). We suggest the brain must represent this consistent meaning of actions across space, as it allows you to find new short-cuts and navigate in unfamiliar settings. We term this representation an ‘actionable representation’. We formulate actionable representations using group and representation theory, and show that, when combined with biological and functional constraints - non-negative firing, bounded neural activity, and precise coding - multiple modules of hexagonal grid cells are the optimal representation of 2D space. We support this claim with intuition, analytic justification, and simulations. Our analytic results normatively explain a set of surprising grid cell phenomena, and make testable predictions for future experiments. Lastly, we highlight the generality of our approach beyond just understanding 2D space. Our work characterises a new principle for understanding and designing flexible internal representations: they should be actionable, allowing animals and machines to predict the consequences of their actions, rather than just encode.

Type: Proceedings paper
Title: Actionable Neural Representations: Grid Cells from Minimal Constraints
Event: The Eleventh International Conference on Learning Representations
Location: Kigali, Rwanda
Dates: 1 May 2023 - 5 May 2023
Open access status: An open access version is available from UCL Discovery
Publisher version: https://iclr.cc/
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neurosci Unit
URI: https://discovery.ucl.ac.uk/id/eprint/10169383
Downloads since deposit
27Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item