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Theoretical neuroscience has room to grow

The goal of theoretical neuroscience is to uncover principles of neural computation through careful design and interpretation of mathematical models. Here, I examine the use of top-down conceptual and bottom-up mechanistic models in theoretical neuroscience, exploring how they connect with experimental practice and where there is room for future growth.

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References

  1. Krakauer, J. W., Ghazanfar, A. A., Gomez-Marin, A., MacIver, M. A. & Poeppel, D. Neuroscience needs behavior: correcting a reductionist bias. Neuron 93, 480–490 (2017).

    Article  PubMed  CAS  Google Scholar 

  2. Datta, S. R., Anderson, D. J., Branson, K., Perona, P. & Leifer, A. Computational neuroethology: a call to action. Neuron 104, 11–24 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Anderson, D. J. & Adolphs, R. A framework for studying emotions across species. Cell 157, 187–200 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Kennedy, A. The what, how, and why of naturalistic behavior. Curr. Opin. Neurobiol. 74, 102549 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Aldarondo, D. et al. A virtual rodent predicts the structure of neural activity across behaviours. Nature 632, 594–602 (2024).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Merel, J., Botvinick, M. & Wayne, G. Hierarchical motor control in mammals and machines. Nat. Commun. 10, 5489 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Bialek, W. Emergence of brains. PRX Life 3, 037002 (2025).

    Article  Google Scholar 

  8. Vyas, S., Golub, M. D., Sussillo, D. & Shenoy, K. V. Computation through neural population dynamics. Annu. Rev. Neurosci. 43, 249–275 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Rigotti, M. et al. The importance of mixed selectivity in complex cognitive tasks. Nature 497, 585–590 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Flavell, S. W., Gogolla, N., Lovett-Barron, M. & Zelikowsky, M. The emergence and influence of internal states. Neuron 110, 2545–2570 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

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Correspondence to Ann Kennedy.

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Kennedy, A. Theoretical neuroscience has room to grow. Nat. Rev. Neurosci. 26, 585–586 (2025). https://doi.org/10.1038/s41583-025-00965-8

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