Neural ensemble dynamics underlying a long-term associative memory

Benjamin F. Grewe, Jan Gründemann, Lacey J. Kitch, Jerome A. Lecoq, Jones G. Parker, Jesse D. Marshall, Margaret C. Larkin, Pablo E. Jercog, Francois Grenier, Jin Zhong Li, Andreas Lüthi and Mark J. Schnitzer ()
Additional contact information
Benjamin F. Grewe: James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
Jan Gründemann: Friedrich Miescher Institute for Biomedical Research
Lacey J. Kitch: James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
Jerome A. Lecoq: James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
Jones G. Parker: CNC Program, Stanford University
Jesse D. Marshall: James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
Margaret C. Larkin: James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
Pablo E. Jercog: James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
Francois Grenier: Friedrich Miescher Institute for Biomedical Research
Jin Zhong Li: James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
Andreas Lüthi: Friedrich Miescher Institute for Biomedical Research
Mark J. Schnitzer: James H. Clark Center for Biomedical Engineering & Sciences, Stanford University

Nature, 2017, vol. 543, issue 7647, 670-675

Abstract: Abstract The brain’s ability to associate different stimuli is vital for long-term memory, but how neural ensembles encode associative memories is unknown. Here we studied how cell ensembles in the basal and lateral amygdala encode associations between conditioned and unconditioned stimuli (CS and US, respectively). Using a miniature fluorescence microscope, we tracked the Ca2+ dynamics of ensembles of amygdalar neurons during fear learning and extinction over 6 days in behaving mice. Fear conditioning induced both up- and down-regulation of individual cells’ CS-evoked responses. This bi-directional plasticity mainly occurred after conditioning, and reshaped the neural ensemble representation of the CS to become more similar to the US representation. During extinction training with repetitive CS presentations, the CS representation became more distinctive without reverting to its original form. Throughout the experiments, the strength of the ensemble-encoded CS–US association predicted the level of behavioural conditioning in each mouse. These findings support a supervised learning model in which activation of the US representation guides the transformation of the CS representation.

Date: 2017
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DOI: 10.1038/nature21682

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