Identifying discrete neurophysiological and behavioral symptoms of chronic stress in preclinical studies using deep learning

During working on my PhD thesis I will be developing deep learning algorithms for identifying discrete neurophysiological and behavioral symptoms of chronic stress in mice. Convolutional neural networks will be used in analysis and identification of abnormalities in EEG signal. Developed model will be useful in recognizing EEG signal disruptions caused by chronic stress but also which of these disruptions are normalized by pharmacological treatment.