A Neural Population Mechanism for Rapid Learning

Neuron. 2018 Nov 21;100(4):964-976.e7. doi: 10.1016/j.neuron.2018.09.030. Epub 2018 Oct 18.


Long-term learning of language, mathematics, and motor skills likely requires cortical plasticity, but behavior often requires much faster changes, sometimes even after single errors. Here, we propose one neural mechanism to rapidly develop new motor output without altering the functional connectivity within or between cortical areas. We tested cortico-cortical models relating the activity of hundreds of neurons in the premotor (PMd) and primary motor (M1) cortices throughout adaptation to reaching movement perturbations. We found a signature of learning in the "output-null" subspace of PMd with respect to M1 reflecting the ability of premotor cortex to alter preparatory activity without directly influencing M1. The output-null subspace planning activity evolved with adaptation, yet the "output-potent" mapping that captures information sent to M1 was preserved. Our results illustrate a population-level cortical mechanism to progressively adjust the output from one brain area to its downstream structures that could be exploited for rapid behavioral adaptation.

Keywords: functional connectivity; monkeys; motor cortex; motor learning; neural manifold; nonhuman primates; premotor cortex; single neurons.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adaptation, Physiological / physiology*
  • Animals
  • Learning / physiology*
  • Macaca mulatta
  • Male
  • Motor Cortex / physiology*
  • Neurons / physiology*
  • Photic Stimulation / methods*
  • Psychomotor Performance / physiology*
  • Time Factors