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Title: What's in a face? : psychophysiological applications of neuroscience for diagnostics and therapies
Author: Elkin, Javier A.
ISNI:       0000 0004 7230 2438
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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The idea that the utility of research should be secondary to understanding its subject delays the extraction of potential value. A parallel translational approach to research was applied whereby discovering new findings and testing their validity was performed in parallel. Research about the face was selected for translation as it provided the complexity, diversity, and fidelity necessary for multiple data-driven hypothesis exploration while remaining key to social interaction. For example, emotional contagion, the tendency for an individual to catch someone else’s emotion has been linked to facial contagion: an automatic reaction whereby facial muscles adopt the expression of any emotional face. Based on the reported exaggerated emotional reactions of patients with upper involvement in Motor Neuron Disease (MND) compared to lower involvement, an experiment was devised to make the difference through comparisons of facial contagion responses with recorded Electromyography (EMG) responses (chapter 3). As these patients were expected to have generally weak responses, it became necessary to increase the sensitivity of acquired signals to elucidate differences between subtypes. An adaptive filtering technique for signal processing was developed based on modelling methods and tested with support vector machines (chapter 2). The therapeutic intervention (chapter 4) consisted of a series of experiments seeking to induce emotional contagion of happiness by presenting images of smiling faces through smartphones. This was also gamified in an experiment at the Science Museum in London to test whether the effect could be found over the short term. Lastly, I parametrised faces from a large population of Tibetan residents and predicted haematological and electrocardiographic measures with machine learning methods as a way of screening for cardiovascular disease through photographs of the face (chapter 5). The results were analysed in relation to the field of cognitive neuroscience and the implications for a parallel translational and high-dimensional approach were discussed.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available