Long-term stability of cortical population dynamics underlying consistent behavior.
- Gallego JA Neural and Cognitive Engineering Group, Center for Automation and Robotics, Spanish National Research Council, Arganda del Rey, Spain. gallego.juanalvaro@gmail.com.
- Perich MG Department of Fundamental Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
- Chowdhury RH Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
- Solla SA Department of Physiology, Northwestern University, Chicago, IL, USA.
- Miller LE Department of Physiology, Northwestern University, Chicago, IL, USA. lm@northwestern.edu.
- 2020-01-08
Published in:
- Nature neuroscience. - 2020
English
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.
- Language
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- English
- Open access status
- green
- Identifiers
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- DOI 10.1038/s41593-019-0555-4
- PMID 31907438
- Persistent URL
- https://sonar.ch/global/documents/46936
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