AUTHOR=Shalbaf Reza , Brenner Colleen , Pang Christopher , Blumberger Daniel M. , Downar Jonathan , Daskalakis Zafiris J. , Tham Joseph , Lam Raymond W. , Farzan Faranak , Vila-Rodriguez Fidel 

TITLE=Non-linear Entropy Analysis in EEG to Predict Treatment Response to Repetitive Transcranial Magnetic Stimulation in Depression

JOURNAL=Frontiers in Pharmacology

VOLUME=9

YEAR=2018

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2018.01188

DOI=10.3389/fphar.2018.01188

ISSN=1663-9812

ABSTRACT=<p><bold>Background:</bold> Biomarkers that predict clinical outcomes in depression are essential for increasing the precision of treatments and clinical outcomes. The electroencephalogram (EEG) is a non-invasive neurophysiological test that has promise as a biomarker sensitive to treatment effects. The aim of our study was to investigate a novel non-linear index of resting state EEG activity as a predictor of clinical outcome, and compare its predictive capacity to traditional frequency-based indices.</p><p><bold>Methods:</bold> EEG was recorded from 62 patients with treatment resistant depression (TRD) and 25 healthy comparison (HC) subjects. TRD patients were treated with excitatory repetitive transcranial magnetic stimulation (rTMS) to the dorsolateral prefrontal cortex (DLPFC) for 4 to 6 weeks. EEG signals were first decomposed using the empirical mode decomposition (EMD) method into band-limited intrinsic mode functions (IMFs). Subsequently, Permutation Entropy (PE) was computed from the obtained second IMF to yield an index named PEIMF2. Receiver Operator Characteristic (ROC) curve analysis and ANOVA test were used to evaluate the efficiency of this index (PEIMF2) and were compared to frequency-band based methods.</p><p><bold>Results:</bold> Responders (RP) to rTMS exhibited an increase in the PEIMF2 index compared to non-responders (NR) at F3, FCz and FC3 sites (<italic>p</italic> &lt; 0.01). The area under the curve (AUC) for ROC analysis was 0.8 for PEIMF2 index for the FC3 electrode. The PEIMF2 index was superior to ordinary frequency band measures.</p><p><bold>Conclusion:</bold> Our data show that the PEIMF2 index, yields superior outcome prediction performance compared to traditional frequency band indices. Our findings warrant further investigation of EEG-based biomarkers in depression; specifically entropy indices applied in band-limited EEG components. Registration in <ext-link ext-link-type="uri" xlink:href="https://clinicaltrials.gov/" xmlns:xlink="http://www.w3.org/1999/xlink">ClinicalTrials.Gov</ext-link>; identifiers NCT02800226 and NCT01887782.</p>