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Neural ensemble dynamics underlying a long-term associative memory
Open accessAbstract
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 Ca 2+ 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.
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“To further explore whether mating or fighting could also induce changes in neuronal activity, we performed a Mahalanobis population vector distance (PVD) analysis (Grewe et al., 2017) and found that the difference in response to female and male cues after the initiation of mating/fighting decreases by 40% from the initial level (Figures S4C–S4F; STAR Methods).”
From Neuronal Representation of Social Information in the Medial Amygdala of Awake Behaving Mice (2017) · cites this paper as Grewe et al., 2017
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MethodContributions of associative and non-associative learning to the dynamics of defensive ethogramsPreprint
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“This fear response happens because the neurons in the amygdala link the unconditioned and conditioned stimuli [69].”
BackgroundPastore, J., Mayer, J., Steinhauser, J., Shuler, K., Bailey, T. W., Speigel, J. H., Papalexakis, E. E., & Korzus, E. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114926 · Cited by 1
Park, S., & Choi, S. (2020) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2020.02.077 · Cited by 1
Psychological Dynamics of Forming Cognitive Map Arabic Translation in Student
Mahsus, M., & Kusumaputri, E. S. (2022) · International Journal of Islamic Educational Psychology · doi:10.18196/ijiep.v3i2.15954 · Cited by 1
“The scheme of the systematic organization of knowledge in the human brain is revealed by Grewe et al. (2017) mentioned that the representation of the relationship between objects could be known through coding in synaptic weights.”
BackgroundA Novel Design Method of Uniformity Energy Distribution Lens for Miniscopes
Zhang, J., & Xin, X. (2023) · IEEE photonics journal · doi:10.1109/jphot.2023.3306806 · Cited by 1
“which neural circuit activities can be extracted out underling different types of behaviors [4], such as motor control [5], [6], sensitive behaviors [7], [8], learning and memories [9], [10], social behaviors [11] and hippocampal coding [12] and so on.”
BackgroundA novel mechanism for amplification of sensory responses by the amygdala-TRN projectionsPreprint
Aizenberg, M., Rolón‐Martínez, S., Pham, T. D., Rao, W., Haas, J. S., & Geffen, M. N. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/623868 · Cited by 1
Basal amygdala inputs to the medial prefrontal cortex mediate fear memory strengtheningPreprint
Einarsson, E. Ö., Flores, Á., Jercog, D., & Herry, C. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.01.20.477064 · Cited by 1
Population-level neural correlates of flexible avoidance learning in medial prefrontal cortexPreprint
Ehret, B., Boehringer, R., Amadei, E. A., Cervera, M. R., Henning, C., Galgali, A. R., Mante, V., & Grewe, B. F. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.31.522384 · Cited by 1
Hippocampal contextualization of social rewardsPreprint
Duarte, J. M., Li, K., Nguyen, R., & Ciocchi, S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.05.12.540475 · Cited by 1
Contributions of associative and non-associative learning to the dynamics of defensive ethogramsPreprint
Le, Q.-S. E., Hereford, D., Borkar, C. D., Aldaco, Z., Klar, J., Resendez, A., & Fadok, J. P. (2023) · eLife · doi:10.7554/elife.90414.1 · Cited by 1
Code Multiplexed Nanocapacitor Arrays for Scalable Neural RecordingsPreprint
Weaver, S. M., Chen, Y., Renz, A. F., Choi, W., Vyza, Y., Schlotter, T., Vulić, K., Kim, D., Atzeni, G., Momotenko, D., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.22.581578 · Cited by 1
Negative-Valence Neurons in the Larval Zebrafish PalliumPreprint
Smith, C. D., Du, Z., Dempsey, W. P., Fraser, S. E., Truong, T. V., & Arnold, D. B. (2025) · eLife · doi:10.1101/2025.11.21.689820 · Cited by 3
“In mammals, several lines of evidence suggest that this process involves the basolateral amygdala, where distinct ensembles encode negative and positive value (Beyeler et al., 2018; Grewe et al., 2017; Namburi et al., 2015; Tye, 2018; Xiu et al., 2014).”
Neural and Computational Mechanisms of Reward and Aversion
Mollick, J. (2017) · CU Scholar (University of Colorado Boulder)
Anterior cingulate and putamen neurons flexibly learn whether a hot dog is a sandwich
Morrow, J. K., & Costa, V. D. (2021) · Neuron · doi:10.1016/j.neuron.2021.02.015
Robert, B., Kimchi, E. Y., Watanabe, Y. L., Chakoma, T. L., Jing, M., Li, Y., & Polley, D. B. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.16.439895
“signal could belie striking shifts in the representational dominance of antagonistically related cellular ensembles that would not be captured by changes in net signal amplitude (Grewe et al., 2017; Gründemann, 2021; Taylor et al., 2021).”
BackgroundZona Incerta activity dynamics underlying associative fear learning and fear generalizationPreprint
Li, Z., Rizzi, G., & Tan, K. R. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.31.454576 · Cited by 1
Research on emergent physical properties of integrated nanomaterials
リ, チ., & Li, Q. (2020)
Khalsa, S. S. (2020) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.737215703.793571553
State Space Models for Spike Data
Yousefi, A., & Eden, U. T. (2022) · Handbook of Neuroengineering · doi:10.1007/978-981-15-2848-4_109-1
Milton, A. L. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734996995.793567218
Sajikumar, S., & Raghuraman, R. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734996995.793556932
Milton, A. L. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735427704.793564748
Maren, S. (2020) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.737243829.793570180
An arbiter model of motivational selectionPreprint
McNally, G. P. (2019) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/b7eux
Sajikumar, S., & Raghuraman, R. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735427704.793559127
Maren, S. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735427704.793561357
Basal Amygdala Inputs to the Medial Prefrontal Cortex Mediate Fear Memory StrengtheningPreprint
Herry, C., Einarsson, E. Ö., Flores, Á., & Jercog, D. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4099079
Turan, A. S., & Kayıkçıoğlu, T. (2022) · Research Square · doi:10.21203/rs.3.rs-2073831/v1
Eppler, J.-B. (2022) · Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) · doi:10.21248/gups.69221
The role of Neuroligin-2 in fear circuits
Marth, L. (2023) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-9631
Metadata
- Authors
- Grewe, B. F., Gründemann, J., Kitch, L. J., Lecoq, J. A., Parker, J. G., Marshall, J. D., Larkin, M. C., Jercog, P. E., Grenier, F., Li, J. Z., Lüthi, A., & Schnitzer, M. J.
- Affiliations
- Howard Hughes Medical Institute (US)
- Friedrich Miescher Institute (CH)
- Pfizer (United States) (US)
- Stanford University (US)
- University of Basel (CH)
- Corresponding author
- Schnitzer, Mark J.
- ORCID
- Venue
- Nature
- Published
- 2017-03
- Volume
- 543
- Issue
- 7647
- Pages
- 670-675
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5378308
- OpenAlex
- W2602668040
- Cited by
- 351
- References
- 47
- Citations by year
- 2026: 27 · 2025: 31 · 2024: 44 · 2023: 45 · 2022: 27 · 2021: 34 · 2020: 42 · 2019: 46 · 2018: 36 · 2017: 19
- FWCI
- 22.17
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- associative memory, neuronal ensembles, basal amygdala, lateral amygdala, fear conditioning, fear extinction, calcium dynamics, supervised learning, conditioned stimulus, unconditioned stimulus, microendoscopy
- MeSH terms
- Amygdala, Animals, Calcium, Conditioning, Classical, Extinction, Psychological, Fear, Male, Microscopy, Fluorescence, Neuronal Plasticity, Neurons, Calcium Signaling, Mice, Memory, Long-Term
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