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Machine-learning approaches to classify and understand emotion states in mice

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References

  1. 1.

    Anderson DJ, Adolphs R. A framework for studying emotions across species. Cell 2014;157:187–200.

    CAS  Article  PubMed  Google Scholar 

  2. 2.

    Dolensek N, Gehrlach DA, Klein AS, Gogolla N. Facial expressions of emotion states and their neuronal correlates in mice. Science. 2020;368:89–94.

    CAS  Article  PubMed  Google Scholar 

  3. 3.

    Grill HJ, Norgren R. The taste reactivity test. I. Mimetic responses to gustatory stimuli in neurologically normal rats. Brain Res. 1978;143:263–79.

    CAS  Article  Google Scholar 

  4. 4.

    Langford DJ, et al. Coding of facial expressions of pain in the laboratory mouse. Nat Methods 2010;7:447–9.

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    Goodwin NL, Nilsson SRO, Golden SA. Rage against the machine: advancing the study of aggression ethology via machine learning. Psychopharmacology. 2020. https://doi.org/10.1007/s00213-020-05577-x.

  6. 6.

    Datta SR, Anderson DJ, Branson K, Perona P, Leifer A. Computational neuroethology: a call to action. Neuron 2019;104:11–24.

    CAS  Article  PubMed  Google Scholar 

Download references

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ND and NG wrote this manuscript.

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Correspondence to Nadine Gogolla.

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Dolensek, N., Gogolla, N. Machine-learning approaches to classify and understand emotion states in mice. Neuropsychopharmacol. 46, 250–251 (2021). https://doi.org/10.1038/s41386-020-00857-8

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