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The importance of mixed selectivity in complex cognitive tasks

Nature volume 497, pages 585–590 (2013)Cite this article

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Abstract

Single-neuron activity in the prefrontal cortex (PFC) is tuned to mixtures of multiple task-related aspects. Such mixed selectivity is highly heterogeneous, seemingly disordered and therefore difficult to interpret. We analysed the neural activity recorded in monkeys during an object sequence memory task to identify a role of mixed selectivity in subserving the cognitive functions ascribed to the PFC. We show that mixed selectivity neurons encode distributed information about all task-relevant aspects. Each aspect can be decoded from the population of neurons even when single-cell selectivity to that aspect is eliminated. Moreover, mixed selectivity offers a significant computational advantage over specialized responses in terms of the repertoire of input–output functions implementable by readout neurons. This advantage originates from the highly diverse nonlinear selectivity to mixtures of task-relevant variables, a signature of high-dimensional neural representations. Crucially, this dimensionality is predictive of animal behaviour as it collapses in error trials. Our findings recommend a shift of focus for future studies from neurons that have easily interpretable response tuning to the widely observed, but rarely analysed, mixed selectivity neurons.

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Figure 1: Low and high-dimensional neural representations, and mixed selectivity.
Figure 2: Behavioural task from ref. 3.
Figure 3: Mixed selectivity in recorded single-cell activity and population decoding.
Figure 4: The recorded neural representations are high-dimensional.
Figure 5: The dimensionality of the neural representations predicts animal behaviour.

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Acknowledgements

We are grateful to L.F. Abbott for comments on the manuscript and for discussions. Work supported by the Gatsby Foundation, the Swartz Foundation and the Kavli Foundation. M.R. is supported by Swiss National Science Foundation grant PBSKP3-133357 and the Janggen-Poehn Foundation; N.D.D. is supported by the McKnight Foundation and the McDonnell Foundation; E.K.M. is supported by NIMH grant 5-R37-MH087027-04 and The Picower Foundation; M.R.W. from the Brain & Behavior Research Foundation and the NARSAD Young Investigator grant.

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Author notes

  1. Omri Barak

    Present address: Present address: Department of Physiology, Technion Medical School, Haifa, 31096, Israel.,

Authors and Affiliations

  1. Center for Theoretical Neuroscience, Columbia University College of Physicians and Surgeons, New York, 10032, New York, USA

    Mattia Rigotti, Omri Barak & Stefano Fusi

  2. Center for Neural Science, New York University, New York, 10003, New York, USA

    Mattia Rigotti, Xiao-Jing Wang & Nathaniel D. Daw

  3. Department of Psychology, New York University, New York, 10003, New York, USA

    Mattia Rigotti & Nathaniel D. Daw

  4. The Picower Institute for Learning and Memory & Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, 02139, Massachusetts, USA

    Melissa R. Warden & Earl K. Miller

  5. Department of Bioengineering, Stanford University, Stanford, 94305, California, USA

    Melissa R. Warden

  6. Department of Neurobiology, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, 06525, Connecticut, USA

    Xiao-Jing Wang

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Contributions

M.R.W. and E.K.M. performed the experiments and collected the data. M.R., O.B., X.-J.W. and S.F. developed the theoretical framework. M.R., O.B., N.D.D. and S.F. conceived the data analyses. M.R. performed the data analyses. M.R., O.B. and S.F. wrote the paper.

Corresponding author

Correspondence to Stefano Fusi.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Methods M1-M8, which includes Supplementary Figures M1-M8, Supplementary Sections S1-S20, which includes Supplementary Figures S1-S22 and additional references. (PDF 2918 kb)

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Rigotti, M., Barak, O., Warden, M. et al. The importance of mixed selectivity in complex cognitive tasks. Nature 497, 585–590 (2013). https://doi.org/10.1038/nature12160

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