Abstract: Brain state classification by applying deep learning techniques on neuroimaging data ... To tackle these issues, we present a sparse feedforward deep neural architecture for encoding and ...

With the advent of brain imaging techniques and machine learning tools, much effort has been devoted to building computational models to capture the encoding ... deep learning-based natural image ...

which is particularly suitable for massively parallel architecture of GPUs on which the majority of machine learning is currently executed. In this paper, we present such method for efficient and ...

Our proposal introduces the following innovations: 1) an end-to-end deep learning architecture for open vocabulary EEG decoding, incorporating a subject-dependent representation learning module for ...

This study presents a useful method for the extraction of behaviour-related activity from neural population recordings based on a specific deep learning ... context of decoding behavioural variables, ...

This makes sense, as decoding is an undisputed ... as students are learning how to manipulate sounds and letters. But it does not specifically mention encoding—or other granular aspects of ...