VAE-clustering of neural signals and their association to cytokines

Sammanfattning: In this thesis we start by reproducing previous experiments by Zanos et al., where they have shown that it is possible to associate neural signals with specific cytokines. One future aim of this project is to send synthetic neural signals through the efferent arc of the vagus nerve and observe reactions without the corresponding catalyst of the symptoms. We use a variational autoencoder (VAE) in our experiment to create a model able to generate new neural signals, and we introduce a novel clustering technique called VAE-clustering, which will be used to cluster neural signals with their associated cytokines. The focus of this paper is the implementation of this method and applying it on the neural signals. Running VAE-clustering on the MNIST dataset shows it to be viable for finding detailed properties of a dataset. We also find that using a VAE as a generative model for neural signals is a good way for recreating detailed waveforms.