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. 2019 Apr 6;29(12):4958–4967. doi: 10.1093/cercor/bhz035

Figure 1.

Figure 1.

Illustration of the analysis pipeline. (A) Locations of seed electrode locations for connectivity analyses, with the nine left prefrontal seeds shown in yellow (Fpz, Fp1, AF3, AF7, Fz, F1, F3, F5, F7) and the seven right prefrontal seeds shown in blue (Fp2, AF4, AF6, F2, F4, F6, F8). All electrode locations (N = 61) were utilized as connectivity nodes. Connectivity pairings of selected left and right seeds with all other electrodes yielded a total of 783 connectivity features per subject. (B) Examples of the three connectivity metrics of coherence, envelope correlation, and αSC for one responder (upper row) and one non-responder (bottom row). Magnitude squared coherence takes amplitude and phase information into account. Envelope correlation is an amplitude-amplitude coupling measure. αSC is the similarity of the spectral waveform between two channels, which was found to be more similar for responders than non-responders. (C) Elastic net regularization was used to build a model for each neurophysiologic measure that distinguished between responders and non-responders. Models were subjected to training and testing cross-validation repeated 100 times to minimize overfitting and spurious classification due to random sampling effects. For each repetition, the full sample (N = 109) was divided into 70% training and 30% testing sets. For each run, training cross-validation consisted of splitting the training set 10-fold, training the model on 9/10-folds and using the 10th-fold to make predictions. This procedure was repeated 10 times, so that each fold served as both a training and testing set. Testing validation consisted of applying the model obtained from training to make predictions about the test data set. (D) For each neurophysiologic measure, the connections that most reliably predicted outcome in validation were identified. These consisted of the 10 features most consistently selected in all training models across 100 repetitions compared among the predictors. These features then were plotted topographically (right panel).