Classification of Different Episodic Memory Tasks by Time Points using a Deep Neural Network

Classification of different episodic memory tasks by time points is challenging because the signal-to-noise ratio in affected brain regions of the medial temporal lobes is low and similar brain regions (such as the hippocampus) contribute to memory activation. No studies have implemented a deep neural network (DNN) to classify memory tasks at each fMRI time point using whole-brain data. We have implemented a region-of-interest based DNN framework and applied it to classify three different episodic memory tasks. Results indicate that this DNN classifier can accurately discriminate between all these tasks.