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Hippocampal Attractor Dynamics Predict Memory-Based Decision Making

Steemers, B; Vicente-Grabovetsky, A; Barry, C; Smulders, P; Schroder, TN; Burgess, N; Doeller, CF; (2016) Hippocampal Attractor Dynamics Predict Memory-Based Decision Making. Current Biology , 26 (13) pp. 1750-1757. 10.1016/j.cub.2016.04.063. Green open access

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Abstract

Memories are thought to be retrieved by attractor dynamics if a given input is sufficiently similar to a stored attractor state [1-5]. The hippocampus, a region crucial for spatial navigation [6-12] and episodic memory [13-18], has been associated with attractor-based computations [5, 9], receiving support from the way rodent place cells "remap" nonlinearly between spatial representations [19-22]. In humans, nonlinear response patterns have been reported in perceptual categorization tasks [23-25]; however, it remains elusive whether human memory retrieval is driven by attractor dynamics and what neural mechanisms might underpin them. To test this, we used a virtual reality [7, 11, 26-28] task where participants learned object-location associations within two distinct virtual reality environments. Participants were subsequently exposed to four novel intermediate environments, generated by linearly morphing the background landscapes of the familiar environments, while tracking fMRI activity. We show that linear changes in environmental context cause linear changes in activity patterns in sensory cortex but cause dynamic, nonlinear changes in both hippocampal activity pattern and remembered locations. Furthermore, the sigmoidal response in the hippocampus scaled with the strength of the sigmoidal pattern in spatial memory. These results indicate that mnemonic decisions in an ambiguous novel context relate to putative attractor dynamics in the hippocampus, which support the dynamic remapping of memories.

Type: Article
Title: Hippocampal Attractor Dynamics Predict Memory-Based Decision Making
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.cub.2016.04.063
Publisher version: http://dx.doi.org/10.1016/j.cub.2016.04.063
Language: English
Additional information: © 2016. This manuscript version is published under a Creative Commons Attribution Non-commercial Non-derivative 4.0 International licence (CC BY-NC-ND 4.0). This licence allows you to share, copy, distribute and transmit the work for personal and non-commercial use providing author and publisher attribution is clearly stated. Further details about CC BY licences are available at http://creativecommons.org/licenses/by/4.0. Access may be initially restricted by the publisher.
Keywords: Science & Technology, Life Sciences & Biomedicine, Biochemistry & Molecular Biology, Cell Biology, MEDIAL TEMPORAL-LOBE, COMPLEMENTARY-LEARNING-SYSTEMS, VOXEL PATTERN-ANALYSIS, SPATIAL NAVIGATION, RECOGNITION MEMORY, REAL-WORLD, REPRESENTATIONS, NETWORKS, CONTEXT, INTEGRATION
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 Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Experimental Epilepsy
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 > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Cell and Developmental Biology
URI: https://discovery.ucl.ac.uk/id/eprint/1538090
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