TY - JOUR
T1 - Place cell maps slowly develop via competitive learning and conjunctive coding in the dentate gyrus
AU - Kim, Soyoun
AU - Jung, Dajung
AU - Royer, Sébastien
N1 - Funding Information:
This work was supported by the Korea Institute of Science and Technology Institutional Program (Project No. 2E27850) and Institute for Basic Science, grant IBS-R015-D1.
Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12/1
Y1 - 2020/12/1
N2 - Place cells exhibit spatially selective firing fields that collectively map the continuum of positions in environments; how such activity pattern develops with experience is largely unknown. Here, we record putative granule cells (GCs) and mossy cells (MCs) from the dentate gyrus (DG) over 27 days as mice repetitively run through a sequence of objects fixed onto a treadmill belt. We observe a progressive transformation of GC spatial representations, from a sparse encoding of object locations and spatial patterns to increasingly more single, evenly dispersed place fields, while MCs show little transformation and preferentially encode object locations. A competitive learning model of the DG reproduces GC transformations via the progressive integration of landmark-vector cells and spatial inputs and requires MC-mediated feedforward inhibition to evenly distribute GC representations, suggesting that GCs slowly encode conjunctions of objects and spatial information via competitive learning, while MCs help homogenize GC spatial representations.
AB - Place cells exhibit spatially selective firing fields that collectively map the continuum of positions in environments; how such activity pattern develops with experience is largely unknown. Here, we record putative granule cells (GCs) and mossy cells (MCs) from the dentate gyrus (DG) over 27 days as mice repetitively run through a sequence of objects fixed onto a treadmill belt. We observe a progressive transformation of GC spatial representations, from a sparse encoding of object locations and spatial patterns to increasingly more single, evenly dispersed place fields, while MCs show little transformation and preferentially encode object locations. A competitive learning model of the DG reproduces GC transformations via the progressive integration of landmark-vector cells and spatial inputs and requires MC-mediated feedforward inhibition to evenly distribute GC representations, suggesting that GCs slowly encode conjunctions of objects and spatial information via competitive learning, while MCs help homogenize GC spatial representations.
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U2 - 10.1038/s41467-020-18351-6
DO - 10.1038/s41467-020-18351-6
M3 - Article
C2 - 32917862
AN - SCOPUS:85090785964
SN - 2041-1723
VL - 11
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 4550
ER -