EEG recordings during resting-state and the maintenance periods of a spatial working memory task in humans

<p>Scripts used to analyze data for the manuscript submitted for publication in EJN</p> <p><strong>Script_Curve_Fitting_HBM.rtf</strong></p> <p>Dr. Hadj Boumediene Meziane: hbmeziane@gmail.com&nbsp;</p> <p><span>We therefore considered this continuous change in power as an extraneous variable </span><em><span>y_k(x)</span></em><span> impacting the measured power spectrum </span><em><span>Pow(E_k)</span></em><span>, and modeled it with a binomial equation that best fit the data, where the coefficients in <em>p_i</em> are in descending powers, and the length of <em>p</em> is <em>(n+1), k </em>is trial number (<em>k = 1 to 10</em>):</span></p> <p><strong><em><span>y_k(x) = p_{<span>1 </span>}. x^{<span>2</span>}<span><span>&nbsp;</span></span>+ p_{<span>2 </span>}. x<span> </span>+ p_{<span>3</span>}</span></em></strong></p> <p><span>In order to statistically compare the topographies between the trials with perfect recall and the trials with failed recall, we subtracted this variable from the mean spectral topographies of each subject and for each electrode by first producing the mean spectral curves of each maintenance trial in the theta and alpha frequency bands, taking into account the IAF, and then calculating the coefficients (</span><em><span>p₁</span></em><span>, </span><em><span>p₂</span></em><span> and </span><em><span>p₃</span></em><span>) of the binomial equation using the Matlab function <em>polyfit.m.</em> Once the coefficients were determined, this estimate was subtracted from each power spectrum matrix using the following formula:</span></p> <p><strong><em><span>PowFit(E_{<span>k</span>}) = Pow (E_{<span>k</span>}) &ndash; </span></em></strong><strong><em><span>y_k(x)</span></em></strong></p> <p>&nbsp;</p> <p><strong>Script_Perf_Fail_EEG_Power_Spec_HBM.rtf</strong></p> <p>Dr. Hadj Meziane: hbmeziane@gmail.com<br>This script calculates EEG power spectra then compares perf and fail conditions, then plots brain topographies with statical results</p> <p>&nbsp;</p> <p><strong>Script_Perf_Fail_EEG_Sources_Spec_HBM.rtf</strong></p> <p>Dr. Hadj Boumediene Meziane: hbmeziane@gmail.com<br>This script compares EEG source spectra then compares Perf vs. Fail conditions then plot statistical results (significant voxels) on MRI volume</p>