PLoS Computational BiologyNeurosciencePeer-reviewed journal article
Parameterization of intraoperative human microelectroderecordings: Linking action potential morphology to brainanatomy
Matthew R. BakeriD, Bryan T. KlasseniD, Michael A. JenseniD, Gabriela Ojeda ValenciaiD, Hossein Heydari, Nuri F. InceiD, K. Robert Müller, Kai Joshua MilleriD
Abstract
Deep brain stimulation (DBS) is a targeted manipulation of brain circuitry to treat neurological and neuropsychiatric conditions. Optimal DBS lead placement is essential for treatment efficacy. Current targeting practice is based on preoperative and intraoperative brain imaging, intraoperative electrophysiology, and stimulation mapping. Electrophysiological mapping using extracellular microelectrode recordings aids in identifying functional subdomains, anatomical boundaries, and disease-correlated physiology. The shape of single-unit action potentials may differ due to different biophysical properties between cell-types and brain regions. Here, we describe a technique to parameterize the structure and duration of sorted spike units using a novel algorithmic approach based on canonical response parameterization, and illustrate how it may be used on DBS microelectrode recordings. Isolated spike shapes are parameterized then compared using a spike similarity metric and grouped by hierarchical clustering. When spike morphology is associated with anatomy, we find regional clustering in the human globus pallidus. This method is widely applicable for spike removal and single-unit characterization and could be integrated into intraoperative array-based technologies to enhance targeting and clinical outcomes in DBS lead placement. Author summaryWe developed a new algorithmic approach to capture the structure of single neuron electrophysiology from microelectrode recordings during deep brain stimulation surgery. This method has broad applications for spike characterization, clustering, removal from the background field potential, and comparison across recording sites. Using this technique, we illustrate regional clustering of spike morphologies in the human globus pallidus.
- organism: human
- assay: electronic health records
- research focus: clustering
- approach: statistical model
- Citations
- 4
- FWCI
- 2.44
- Field percentile
- top 11%
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