AUTHOR=Trongnetrpunya Amy , Nandi Bijurika , Kang Daesung , Kocsis Bernat , Schroeder Charles E. , Ding Mingzhou TITLE=Assessing Granger Causality in Electrophysiological Data: Removing the Adverse Effects of Common Signals via Bipolar Derivations JOURNAL=Frontiers in Systems Neuroscience VOLUME=9 YEAR=2016 URL=https://www.frontiersin.org/journals/systems-neuroscience/articles/10.3389/fnsys.2015.00189 DOI=10.3389/fnsys.2015.00189 ISSN=1662-5137 ABSTRACT=
Multielectrode voltage data are usually recorded against a common reference. Such data are frequently used without further treatment to assess patterns of functional connectivity between neuronal populations and between brain areas. It is important to note from the outset that such an approach is valid only when the reference electrode is nearly electrically silent. In practice, however, the reference electrode is generally not electrically silent, thereby adding a common signal to the recorded data. Volume conduction further complicates the problem. In this study we demonstrate the adverse effects of common signals on the estimation of Granger causality, which is a statistical measure used to infer synaptic transmission and information flow in neural circuits from multielectrode data. We further test the hypothesis that the problem can be overcome by utilizing bipolar derivations where the difference between two nearby electrodes is taken and treated as a representation of local neural activity. Simulated data generated by a neuronal network model where the connectivity pattern is known were considered first. This was followed by analyzing data from three experimental preparations where