Towards the neural population doctrine.

Journal: Current opinion in neurobiology
Published Date:

Abstract

Across neuroscience, large-scale data recording and population-level analysis methods have experienced explosive growth. While the underlying hardware and computational techniques have been well reviewed, we focus here on the novel science that these technologies have enabled. We detail four areas of the field where the joint analysis of neural populations has significantly furthered our understanding of computation in the brain: correlated variability, decoding, neural dynamics, and artificial neural networks. Together, these findings suggest an exciting trend towards a new era where neural populations are understood to be the essential unit of computation in many brain regions, a classic idea that has been given new life.

Authors

  • Shreya Saxena
    Department of Statistics, Grossman Center for the Statistics of Mind Zuckerman Mind, Brain Behavior Institute, Center for Theoretical Neuroscience, Columbia University, New York City, United States.
  • John P Cunningham
    Department of Statistics, Grossman Center for the Statistics of Mind Zuckerman Mind, Brain Behavior Institute, Center for Theoretical Neuroscience, Columbia University, New York City, United States. Electronic address: jpc2181@columbia.edu.