http://www.nitrc.org/forum/forum.php?forum_id=2958 <p class="abstract"><div class="Abstract" lang="en"><a name="Abs1"></a><span class="AbstractHeading">Abstract&nbsp;&nbsp;</span><div class="normal">The recent development of large multielectrode recording arrays has made it affordable for an increasing number of laboratories to record from multiple brain regions simultaneously. The development of analytical tools for array data, however, lags behind these technological advances in hardware. In this paper, we present a method based on forward modeling for estimating current source density from electrophysiological signals recorded on a two-dimensional grid using multi-electrode rectangular arrays. This new method, which we call two-dimensional inverse Current Source Density (iCSD 2D), is based upon and extends our previous one- and three-dimensional techniques. We test several variants of our method, both on surrogate data generated from a collection of Gaussian sources, and on model data from a population of layer 5 neocortical pyramidal neurons. We also apply the method to experimental data from the rat subiculum. The main advantages of the proposed method are the explicit specification of its assumptions, the possibility to include system-specific information as it becomes available, the ability to estimate CSD at the grid boundaries, and lower reconstruction errors when compared to the traditional approach. These features make iCSD 2D a substantial improvement over the approaches used so far and a powerful new tool for the analysis of multielectrode array data. We also provide a free GUI-based MATLAB toolbox to analyze and visualize our test data as well as user datasets. </div> </div></p><ul> <li><span class="labelName">Content Type </span><span class="labelValue">Journal Article</span></li><li>Category Original Article</li><li>Pages 401-425</li><li>DOI 10.1007/s12021-011-9111-4</li><li><span class="labelName">Authors</span><ul> <li>Szymon Łęski, Department of Neurophysiology, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, ul. Pasteura 3, 02–093 Warsaw, Poland</li><li>Klas H. Pettersen, Department of Mathematical Sciences and Technology and Center for Integrative Genetics, Norwegian University of Life Sciences, Ås, Norway</li><li>Beth Tunstall, Faculty of Life Sciences, University of Manchester, Manchester, UK</li><li>Gaute T. Einevoll, Department of Mathematical Sciences and Technology and Center for Integrative Genetics, Norwegian University of Life Sciences, Ås, Norway</li><li>John Gigg, Faculty of Life Sciences, University of Manchester, Manchester, UK</li><li>Daniel K. Wójcik, Department of Neurophysiology, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, ul. Pasteura 3, 02–093 Warsaw, Poland</li> </ul></li> </ul><ul class="parents"> <ul class="details"> <li><span class="header labelName">Journal </span><span class="labelValue"><a href="http://www.springerlink.com/content/120559/">Neuroinformatics</a></span></li><li><span class="labelName">Online ISSN </span><span class="labelValue">1559-0089</span></li><li><span class="labelName">Print ISSN </span><span class="labelValue">1539-2791</span></li> </ul><ul class="details"> <li><span class="header labelName">Journal Volume </span><span class="labelValue">Volume 9</span></li> </ul><ul class="details"> <li><span class="header labelName">Journal Issue </span><span class="labelValue"><a href="http://www.springerlink.com/content/v50w168v4hq8/">Volume 9, Number 4</a></span></li> </ul> </ul> en-us Copyright 2000-2026 NITRC OSI Mon, 20 Apr 2026 2:02:39 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator