… to understand and explore the complex dynamics and behavior of the brain. While … and
deep learning in EEG analysis. And a framework combining complex network and deep learning …

… trends in EEG have not yet been explored. In this study, we develop a deep learning model
for neurologic outcome prediction which leverages trend information in continuous EEG data …

… In particular, using data from the best single EEG channel, we obtain an area under the …
conclude that deep networks may provide a useful tool for the analysis of EEG dynamics even …

… of deep learning applications to EEG signal classification, as shown in figure 1. This search
was conducted on 22 December 2018 within both Web of Science and PubMed databases …

… of EEG demonstrated different trends of dynamic clusters … of marker EEG features and resulted
in an improved accuracy of EEG … During learning of EEG data, the areas of neurons in the …

… review about deep learning (DNN, RNN, CNN, and so on) for analyzing EEG data for …
the hyper parameters of deep learning architecture. Later, it is studied how semi‐supervised …

… the dynamics of microstates that are based on EEG recorded inside (… with the transition
dynamics of EEG microstate. However, … advancements in the domain of deep learning, it would be …

… In this paper, we have described two deep learning-based models EEG-Conv and EEG-Conv-R
to predict the mental state of driver, respectively. A 5-layer convolution neural network is …

… Our analysis reveals that the amount of EEG data used … their models on raw or preprocessed
EEG time series. Finally, the … We also make our summary table of DL and EEG papers …

… to classify whether the EEG trial belongs to 100 … deep learning can help us predict the stages
of visual processing and, hence, unlock important insights regarding the temporal dynamics …