Kevin Hilbert, Joscha Böhnlein, Charlotte Meinke, Alice V Chavanne, Till Langhammer, Lara Stumpe, Nils Winter, Ramona Leenings, Dirk Adolph, Volker Arolt, Sophie Bischoff, Jan C Cwik, Jürgen Deckert, Katharina Domschke, Thomas Fydrich, Bettina Gathmann, Alfons O Hamm, Ingmar Heinig, Martin J Herrmann, Maike Hollandt, Jürgen Hoyer, Markus Junghöfer, Tilo Kircher, Katja Koelkebeck, Martin Lotze, Jürgen Margraf, Jennifer L M Mumm, Peter Neudeck, Paul Pauli, Andre Pittig, Jens Plag, Jan Richter, Isabelle C Ridderbusch, Winfried Rief, Silvia Schneider, Hanna Schwarzmeier, Fabian R Seeger, Niklas Siminski, Benjamin Straube, Thomas Straube, Andreas Ströhle, Hans-Ulrich Wittchen, Adrian Wroblewski, Yunbo Yang, Kati Roesmann, Elisabeth J Leehr, Udo Dannlowski, Ulrike Lueken
Lack of evidence for predictive utility from resting state fMRI data for individual exposure-based cognitive behavioral therapy outcomes: A machine learning study in two large multi-site samples in anxiety disorders
NeuroImage
eventrelated potentials erps superposition electric potential differences generated neurophysiological activity associated psychophysical events spatiotemporal dissociation signal sources supplement conventional erp analysis improve source localization however results established source separation methods applied erps challenging interpret hence developed recurrent neural network rnn method blind source separation rnn transforms input step pulse signals representing events corresponding erp difference waveforms source waveforms obtained penultimate layer units scalp maps obtained feedforward output layer weights project source waveforms onto eeg electrode amplitudes interpretable sparse source representation achieved incorporating l1 regularization signals obtained penultimate layer network training rnn method applied four erp difference waveforms mmn n170 n400 p3 openaccess erp core database independent component analysis ica applied data comparison rnn decomposed erps eleven spatially temporally separate sources less noisy tended erpspecific less similar icaderived sources rnn sources also less ambiguity source waveform amplitude scalp potential polarity equivalent current dipole orientation ica sources conclusion proposed rnn blind source separation method effectively applied grandaverage erp difference waves holds promise development computational model eventrelated neural signals