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EDHMM classification produces improved agreement between simultaneously recorded LFP and MP signals.

By James M. McFarland (216130), Thomas T. G. Hahn (349104) and Mayank R. Mehta (216136)


<p><b>A</b>) Example of an LFP (blue trace) recorded simultaneously with the MP (black trace) of a nearby cortical neuron. The corresponding LFP (gray) and MP (red) state sequences inferred from the EDHMM are overlaid. <b>B</b>) The instantaneous probability of detecting false DOWN states is plotted against that for false UP states for the EDHMM method as well as the SMM- and Np-TC methods. The mean and SEM are indicated by the colored crosses. <b>C</b>) The probability of a missed LFP state, relative to the MP state sequence, is plotted against the probability of detecting an extra LFP state. <b>D</b>) Box plots illustrating the changes in <i>e<sub>i</sub></i> relative to the EDHMM algorithm for the following decoding algorithms: HMM; fixed-mean EDHMM (fm-EDHMM); static mixture model threshold-crossing (SMM-TC); and nonparametric threshold-crossing (Np-TC). <b>E</b>) Same as D for <i>e<sub>s</sub></i>.</p

Topics: Neuroscience, Mathematics, classification, produces, recorded, lfp, mp
Year: 2013
DOI identifier: 10.1371/journal.pone.0021606.g008
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Provided by: FigShare
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