Manley, E. orcid.org/0000-0002-8904-0513 and McNamee, D.C. (2026) Brain-inspired representations of urban space. International Journal of Geographical Information Science (IJGIS). ISSN: 1365-8816
Abstract
Geography and neuroscience share a core interest in understanding human behaviour in spatial environments. Yet, interdisciplinary collaboration is often limited by differences in methodology and epistemological assumptions. To help bridge this divide, we introduce a translational link between cognitive models of spatial processing in neuroscience and representations of geographic space. Building on long-standing theories that the brain predicts possible futures, the predictive map hypothesis suggests that locations in space are encoded according to their association with possible locations in the future. Here, we adapt a formal instantiation of this idea, the successor representation (SR), to urban space resulting in the geographic successor representation (gSR). We show that this cognitive model of geographic representation produces compelling unique features of urban space while remaining closely aligned with brain mechanisms of spatial processing. We outline several promising directions for extending this work, and propose that the gSR and its variants may provide spatial representations capable of supporting deeper integration between geographic and neuroscientific research.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Spatial cognition; computational neurosci-ence; cognitive maps; spatial representation; street networks |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) |
| Funding Information: | Funder Grant number The Leverhulme Trust Not Known |
| Date Deposited: | 29 Apr 2026 13:45 |
| Last Modified: | 12 Aug 2026 13:38 |
| Status: | Published online |
| Publisher: | Taylor & Francis |
| Identification Number: | 10.1080/13658816.2026.2660988 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:240555 |
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