Flexible timing by temporal scaling of cortical responses

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Musicians can perform at different tempos, speakers can control the cadence of their speech, and children can flexibly vary their temporal expectations of events. To understand the neural basis of such flexibility, we recorded from the medial frontal cortex of nonhuman primates trained to produce different time intervals with different effectors. Neural responses were heterogeneous, nonlinear, and complex, and they exhibited a remarkable form of temporal invariance: firing rate profiles were temporally scaled to match the produced intervals. Recording from downstream neurons in the caudate and from thalamic neurons projecting to the medial frontal cortex indicated that this phenomenon originates within cortical networks. Recurrent neural network models trained to perform the task revealed that temporal scaling emerges from nonlinearities in the network and that the degree of scaling is controlled by the strength of external input. These findings demonstrate a simple and general mechanism for conferring temporal flexibility upon sensorimotor and cognitive functions.

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We thank M.S. Fee, J.J. DiCarlo, and R. Desimone for comments on the manuscript, and we thank D. Sussillo for advice on modeling. D.N. was supported by the Rubicon Grant (2015/446-14-008) from the Netherlands Scientific Organization (NWO). M.J. is supported by the NIH (NINDS-NS078127), the Sloan Foundation, the Klingenstein Foundation, the Simons Foundation, the Center for Sensorimotor Neural Engineering, and the McGovern Institute.

Author information

Author notes

    • Jing Wang
    • , Eghbal A. Hosseini
    •  & Mehrdad Jazayeri

    Present address: Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

  1. Jing Wang and Devika Narain contributed equally to this research.


  1. McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA

    • Jing Wang
    • , Devika Narain
    •  & Mehrdad Jazayeri
  2. Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    • Devika Narain
    • , Eghbal A. Hosseini
    •  & Mehrdad Jazayeri
  3. Netherlands Institute for Neuroscience, Amsterdam, The Netherlands

    • Devika Narain
  4. Department of Neuroscience, Erasmus Medical Center, Rotterdam, The Netherlands

    • Devika Narain


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J.W. was responsible for all aspects of experiments and analyses and developed the simplified model. D.N. was responsible for the development of the recurrent neural network model. E.A.H. helped with the data collection and analysis. M.J. was responsible for all aspects of the project. All authors helped with the interpretation of data and writing the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Mehrdad Jazayeri.

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