Simultaneous glutamate recordings in the frontal cortex network with multisite biomorphic microelectrodes: New tools for ADHD research.

J Neurosci Methods

Department of Anatomy & Neurobiology, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA; Department of Pediatrics, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA; Department of Psychiatry, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA; Center for Microelectrode Technology, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA; Parkinson's Disease Translational Research Center of Excellence, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA. Electronic address:

Published: August 2015

Background: The aberrant regulation of glutamate has been implicated in numerous psychiatric disorders including drug addiction and attention-deficit/hyperactivity disorder. To understand glutamate signaling and its role in facilitating disease, tools to directly measure glutamate in a complex, neural network are needed.

New Method: The development of a ceramic-based, dual-sided, biomorphic microelectrode array with four recording sites on each side to facilitate a more detailed measurement of glutamate in awake, behaving rodents.

Results: In vitro calibrations of these biosensors showed selective and specific responses to glutamate. In awake rats, these biomorphic electrode arrays enabled the concurrent evaluation of glutamate in a network, the frontal cortex: including the cingulate, prelimbic, infralimbic and dorsal peduncle regions. Regions within the frontal cortex exhibited varying phasic glutamate patterns in awake animals.Comparison with existing method: Existing methodologies to measure glutamate neurotransmission employ single-sided biosensors or biosensors capable of measuring neurochemicals at only one location in space.

Conclusions: Multi-site, biomorphic neurochemical biosensors provide a method for simultaneously measuring glutamate in multiple areas of a neural network in the brain.

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Source
http://dx.doi.org/10.1016/j.jneumeth.2015.01.018DOI Listing

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