A Wireless EEG Recording Method for Rat Use inside the Water Maze

PLoS One. 2016 Feb 1;11(2):e0147730. doi: 10.1371/journal.pone.0147730. eCollection 2016.

Abstract

With the continued miniaturisation of portable embedded systems, wireless EEG recording techniques are becoming increasingly prevalent in animal behavioural research. However, in spite of their versatility and portability, they have seldom been used inside water-maze tasks designed for rats. As such, a novel 3D printed implant and waterproof connector is presented, which can facilitate wireless water-maze EEG recordings in freely-moving rats, using a commercial wireless recording system (W32; Multichannel Systems). As well as waterproofing the wireless system, battery, and electrode connector, the implant serves to reduce movement-related artefacts by redistributing movement-related forces away from the electrode connector. This implant/connector was able to successfully record high-quality LFP in the hippocampo-striatal brain regions of rats as they undertook a procedural-learning variant of the double-H water-maze task. Notably, there were no significant performance deficits through its use when compared with a control group across a number of metrics including number of errors and speed of task completion. Taken together, this method can expand the range of measurements that are currently possible in this diverse area of behavioural neuroscience, whilst paving the way for integration with more complex behaviours.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials
  • Animals
  • Artifacts
  • Behavior, Animal
  • Electroencephalography / methods*
  • Female
  • Maze Learning*
  • Rats, Sprague-Dawley
  • Skull / anatomy & histology
  • Task Performance and Analysis
  • Water*
  • Wireless Technology*

Substances

  • Water

Grants and funding

This work was supported by University of Strasbourg and Neurex—Neuroscience Upper Rhine Network (post-doc fellowship awarded to RCP), and BrainLinks-BrainTools Cluster of Excellence funded by the German Research Foundation (DFG, grant number EXC 1086).