TY - JOUR
T1 - Hippocampal pattern separation supports reinforcement learning
AU - Ballard, Ian C.
AU - Wagner, Anthony D.
AU - McClure, Samuel
N1 - Funding Information:
We thank the NSF GRFP (ICB), NSF 0801700 and Stanford Innovation Grants (ICB). We also thank Kim D’Ardenne for significant editing and Stephanie Gagnon, Karen LaRocque, Alex Gonzales, Anna Khazenzon and Yuan Chang Leong for their feedback.
Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - Animals rely on learned associations to make decisions. Associations can be based on relationships between object features (e.g., the three leaflets of poison ivy leaves) and outcomes (e.g., rash). More often, outcomes are linked to multidimensional states (e.g., poison ivy is green in summer but red in spring). Feature-based reinforcement learning fails when the values of individual features depend on the other features present. One solution is to assign value to multi-featural conjunctive representations. Here, we test if the hippocampus forms separable conjunctive representations that enables the learning of response contingencies for stimuli of the form: AB+, B−, AC−, C+. Pattern analyses on functional MRI data show the hippocampus forms conjunctive representations that are dissociable from feature components and that these representations, along with those of cortex, influence striatal prediction errors. Our results establish a novel role for hippocampal pattern separation and conjunctive representation in reinforcement learning.
AB - Animals rely on learned associations to make decisions. Associations can be based on relationships between object features (e.g., the three leaflets of poison ivy leaves) and outcomes (e.g., rash). More often, outcomes are linked to multidimensional states (e.g., poison ivy is green in summer but red in spring). Feature-based reinforcement learning fails when the values of individual features depend on the other features present. One solution is to assign value to multi-featural conjunctive representations. Here, we test if the hippocampus forms separable conjunctive representations that enables the learning of response contingencies for stimuli of the form: AB+, B−, AC−, C+. Pattern analyses on functional MRI data show the hippocampus forms conjunctive representations that are dissociable from feature components and that these representations, along with those of cortex, influence striatal prediction errors. Our results establish a novel role for hippocampal pattern separation and conjunctive representation in reinforcement learning.
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U2 - 10.1038/s41467-019-08998-1
DO - 10.1038/s41467-019-08998-1
M3 - Article
C2 - 30842581
AN - SCOPUS:85062625196
SN - 2041-1723
VL - 10
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 1073
ER -