Abstract
Simultaneous neural recordings taken from multiple areas of the rodent brain are garnering growing interest because of the insight they can provide about spatially distributed neural circuitry. The promise of such recordings has inspired great progress in methods for surgically implanting large numbers of metal electrodes into intact rodent brains. However, methods for localizing the precise location of these electrodes have remained severely lacking. Traditional histological techniques that require slicing and staining of physical brain tissue are cumbersome and become increasingly impractical as the number of implanted electrodes increases. Here we solve these problems by describing a method that registers 3D computed tomography (CT) images of intact rat brains implanted with metal electrode bundles to a magnetic resonance imaging histology (MRH) atlas. Our method allows accurate visualization of each electrode bundle’s trajectory and location without removing the electrodes from the brain or surgically implanting external markers. In addition, unlike physical brain slices, once the 3D images of the electrode bundles and the MRH atlas are registered, it is possible to verify electrode placements from many angles by “reslicing” the images along different planes of view. Furthermore, our method can be fully automated and easily scaled to applications with large numbers of specimens. Our digital imaging approach to efficiently localizing metal electrodes offers a substantial addition to currently available methods, which, in turn, may help accelerate the rate at which insights are gleaned from rodent network neuroscience.
Footnotes
↵1 The authors declare no competing financial interests.
↵3 This work is supported by Duke University Exploratory Research Fund (C.B. and G.A.J.), NIA K01-AG041211 (A.B.), Duke Center for In Vivo Microscopy (National Institutes of Health–National Institute of Biomedical Imaging and Bioengineering P41 EB015897), IMHRO RSA (K.D.), Duke University SOM startup funds (K.D.), and National Science Foundation (NSF) DGF1106401 (M.-A.V.). This work also used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by NSF grant ACI-1053575. We thank James Cook (Center for In Vivo Microscopy, Duke University) for his help with scanning and Rainbo Hultman and Stephen Mague (Duke University) for providing their anatomical expertise to evaluate the described registration method.
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
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