Long-Term Depression Learning in Spinal Cord Networks

Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul:2018:2667-2670. doi: 10.1109/EMBC.2018.8512871.

Abstract

Investigating learning in networks of spinal cord neurons can provide insight into the dynamics of connectivity in human spinal cords. It may also hold implications for developing neural prosthetics and neurocomputers. Culturing neural networks on microelectrode arrays (MEAs) allows for the repeated observation and stimulation of electrophysiological activity in vitro. Here we used MEAs to demonstrate learning in networks of spinal cord neurons. This was done by exposing E17 mouse spinal cord cultures to high frequency artificial spike trains, or tetanization. Unexpectedly, when comparing the networks' responses to low-frequency probing stimulations before and after tetanization, the cultures were found to demonstrate long-term depression (LTD). LTD was most significantly observed between 500-1000 ms after low-frequency probing. These results indicate that periodic high-frequency excitation of spinal cord networks can result in decreased synaptic efficacy.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Action Potentials
  • Animals
  • Long-Term Synaptic Depression*
  • Mice
  • Microelectrodes*
  • Nerve Net*
  • Neurons / physiology*
  • Spinal Cord / physiology*