What does the human face tell the human brain?

1) Brief description of the context of the research including potential impact

Experiments to understand how the brain functions have largely been limited to single person studies, confined to prohibitive scanners due to limitations with equipment. The rise of functional near-infrared spectroscopy (fNIRS) has allowed us the opportunity to delve deeper into our understanding of the brain in more ecologically valid scenarios.
This is especially important in social scenarios. The foundation of all social interactions is formed from the facial expressions of those involved. Therefore, observing how neural pathways function when presented with different facial stimuli grants us the opportunity to gain a deeper understanding of how the typical brain works. With this understanding fNIRS can be used to provide insight into how neurological disorders progress, in real time, in the case of stroke patients, dementia or a multitude of neurological disorders.

2) Aims and objectives


Thus, the aims of the project are to develop multi-modal integrative approaches, combining the use of EEG, fNIRS, eye-tracking, eye-contact, subject reports, and facial classifications into models of high-level facial dynamics, human communication and behaviour. Studies will be performed to examine and map facial responses to brain functional responses and cortical locations, in experiments were participants both emote expressions and observe emoted expressions from others. Machine Learning methodologies will be explored to apply a computational framework for the classification of neural signatures in relation to facial expressions. Signal processing and statistical techniques will also be developed to effectively relate the multi-modal equipment data with each other and for analysis.

3) Novelty of the research methodology

The novelty of the project lies with the experimental methodology and the computational methods to analyse data. A significant benefit of fNIRS over other neuroimaging modalities is the opportunity to examine the neural correlates underlying social interactions with two people simultaneously; it is known that the cortical processes of two-person interactions are significantly different to one person observing a video or picture. Considering this, the methodologies of investigating two-person neurological responses are underdeveloped. As such novel machine learning approaches will be investigated, developed, and applied with the aim of isolating neural responses to facial expressions. Additionally, as we will be developing a multi-modal suite to investigate multiple physiological parameters, computational tools will be developed to integrate the obtained data and to perform analysis on it.

4) Alignment to EPSRC's strategies and research areas

This project plays a role in the Optimising Treatment grand challenge of the EPSRC strategies. Specifically, the long term impact of this project relates to the development and improvement of novel, low-cost diagnostic devices, with high sensitivity, specificity and reliability, for timely and accurate diagnosis, improving the choice and reducing the cost of intervention, and increasing the likelihood of successful health outcomes. Additionally, data analytic methods to identify disease phenotypes and associated responses to treatment from population data, allowing evidence-based selection of treatment options, with lower costs and morbidity, and improved health outcomes. Short-term the project focuses on new methodologies for making sense of complex healthcare data, aswell as the development of next generation imaging technologies for diagnostic, monitoring and therapeutic applications; with improved accuracy, affordability and incorporating new modalities.

5) Any companies or collaborators involved

This project is in collaboration with Shimadzu Corporation and the Brain Function Laboratory, Yale School of Medicine, New Haven, CT.

The critical mass of scientists and engineers that i4health will produce will ensure the UK's continued standing as a world-leader in medical imaging and healthcare technology research. In addition to continued academic excellence, they will further support a future culture of industry and entrepreneurship in healthcare technologies driven by highly trained engineers with deep understanding of the key factors involved in delivering effective translatable and marketable technology. They will achieve this through high quality engineering and imaging science, a broad view of other relevant technological areas, the ability to pinpoint clinical gaps and needs, consideration of clinical user requirements, and patient considerations. Our graduates will provide the drive, determination and enthusiasm to build future UK industry in this vital area via start-ups and spin-outs adding to the burgeoning community of healthcare-related SMEs in London and the rest of the UK. The training in entrepreneurship, coupled with the vibrant environment we are developing for this topic via unique linkage of Engineering and Medicine at UCL, is specifically designed to foster such outcomes. These same innovative leaders will bolster the UK's presence in medical multinationals - pharmaceutical companies, scanner manufacturers, etc. - and ensure the UK's competitiveness as a location for future R&D and medical engineering. They will also provide an invaluable source of expertise for the future NHS and other healthcare-delivery services enabling rapid translation and uptake of the latest imaging and healthcare technologies at the clinical front line. The ultimate impact will be on people and patients, both in the UK and internationally, who will benefit from the increased knowledge of health and disease, as well as better treatment and healthcare management provided by the future technologies our trainees will produce.

In addition to impact in healthcare research, development, and capability, the CDT will have major impact on the students we will attract and train. We will provide our talented cohorts of students with the skills required to lead academic research in this area, to lead industrial development and to make a significant impact as advocates of the science and engineering of their discipline. The i4health CDT's combination of the highest academic standards of research with excellent in-depth training in core skills will mean that our cohorts of students will be in great demand placing them in a powerful position to sculpt their own careers, have major impact within our discipline, while influencing the international mindset and direction. Strong evidence demonstrates this in our existing cohorts of students through high levels of conference podium talks in the most prestigious venues in our field, conference prizes, high impact publications in both engineering, clinical, and general science journals, as well as post-PhD fellowships and career progression. The content and training innovations we propose in i4health will ensure this continues and expands over the next decade.