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Nat Neurosci. 2020 Jan 6. doi: 10.1038/s41593-019-0555-4. [Epub ahead of print]

Long-term stability of cortical population dynamics underlying consistent behavior.

Author information

1
Neural and Cognitive Engineering Group, Center for Automation and Robotics, Spanish National Research Council, Arganda del Rey, Spain. gallego.juanalvaro@gmail.com.
2
Department of Physiology, Northwestern University, Chicago, IL, USA. gallego.juanalvaro@gmail.com.
3
Department of Bioengineering, Imperial College London, London, UK. gallego.juanalvaro@gmail.com.
4
Department of Fundamental Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
5
Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
6
Department of Physiology, Northwestern University, Chicago, IL, USA.
7
Department of Physics and Astronomy, Northwestern University, Evanston, IL, USA.
8
Department of Physiology, Northwestern University, Chicago, IL, USA. lm@northwestern.edu.
9
Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA. lm@northwestern.edu.
10
Department of Physical Medicine and Rehabilitation, Northwestern University, and Shirley Ryan Ability Lab, Chicago, IL, USA. lm@northwestern.edu.

Abstract

Animals readily execute learned behaviors in a consistent manner over long periods of time, and yet no equally stable neural correlate has been demonstrated. How does the cortex achieve this stable control? Using the sensorimotor system as a model of cortical processing, we investigated the hypothesis that the dynamics of neural latent activity, which captures the dominant co-variation patterns within the neural population, must be preserved across time. We recorded from populations of neurons in premotor, primary motor and somatosensory cortices as monkeys performed a reaching task, for up to 2 years. Intriguingly, despite a steady turnover in the recorded neurons, the low-dimensional latent dynamics remained stable. The stability allowed reliable decoding of behavioral features for the entire timespan, while fixed decoders based directly on the recorded neural activity degraded substantially. We posit that stable latent cortical dynamics within the manifold are the fundamental building blocks underlying consistent behavioral execution.

PMID:
31907438
DOI:
10.1038/s41593-019-0555-4

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