Abstract
A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 μm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware.
Highlights
Microelectrode arrays (MEAs) are a powerful tool to record large populations of neurons and monitor local neural networks as a whole
To our knowledge, not been adapted for mapping MEA data, here we present NeuroMap, an interactive Matlab-based software for mapping MEA data based on spline interpolation
Examples of 2D mapping using experimental data from a 60-electrode rectangular MEA and from a 256-electrode nonrectangular MEA are provided in Figures 2B,C, respectively
Summary
Microelectrode arrays (MEAs) are a powerful tool to record large populations of neurons and monitor local neural networks as a whole. This approach provides scattered information at recording sites only, and does not provide any estimate of activity between electrode sites While these methods are satisfactory for electrode pitch small enough for information to become redundant across neighboring electrodes, the coverage of large neural structures with a limited number of electrodes would benefit from methods that estimate data continuously across the array. Such methods would be of particular interest for mapping local field potentials (LFPs), which have a spatial frequency lower than action potentials and can be appropriately interpolated between recording sites
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
