What Does the Human Face Tell the Human Brain?

The Department of Medical Physics and Biomedical Engineering is one of the largest Medical Physics and Biomedical Engineering departments in the UK and is proud to host internationally-leading research groups covering a broad range of activities and is spread over several sites. We are inviting applications for an exciting new PhD studentship in the development of multi-modal integrative approaches that incorporate eye-tracking, eye-contact, subject reports of emotional reactions, electroencephalography (EEG) signals, fNIRS signals, and facial classifications into models of high-level face dynamics and human communication. In a series of studies, you will examine and map facial responses to brain functional responses and cortical locations; these will include studies where participants both emote expressions and observe expressions emoted by other individuals. You will need to develop and use computational approaches for facial classifications that may include machine learning. In addition, you may need to develop statistical and/or signal processing techniques to relate brain electrical (EEG) and hemodynamic (fNIRS) signals in response to faces. One of the big neuroscience scopes of the project is to examine the use of facial expressions as a social language.

Studentship Description
The human face is designed for flexible and dynamic expression of social information, and the human brain is tuned to encode a matched repertoire of these expressions that serve as social cues. This tight coupling between face and brain is widely appreciated for the early levels of visual processing. For example, electrophysiological studies of non-human primate brain confirm a highly specialized hierarchical system of interacting neurons that are sensitive to face-specific parameters thought to underlie the rapid encoding and decoding of facial information (Chang and Tsao, 2017). Further, functional imaging studies of human brain confirm that face-related processes are segregated into homologous regions specialized for detecting and interpreting facial information (Kanwisher, et al, 1997). Beyond this neural machinery for extracting information, however, faces also have privileged access to high level brain centres for emotions, memories, and communicative actions that drive spontaneous and automatic social interactions. These interactive and dynamic face-to-brain systems are poorly understood and are topics of active scientific efforts.

Although conventional neuroimaging approaches such as functional magnetic resonance imaging (fMRI) provide fundamental insight into the organization of the human brain, the technique is limited to single brains in stationary conditions without the benefit of live and interactive behaviour due to the high magnetic fields of the MRI. However, recent developments of functional near-infrared spectroscopy (fNIRS), a head mounted neuroimaging technology, enables the acquisition of neural responses (as measured by hemodynamic signals) during live and dynamic interpersonal interactions between two naturally interacting individuals (dyads). The absence of the high magnetic field with fNIRS also enables multimodal acquisitions of behavioural events such as continuous facial information (Kinect cameras), eye gaze and eye tracking information, task-related responses, electromagnetic responses (EEG), and subjective reports all acquired simultaneously with the fNIRS data (Hirsch, et al., 2017, 2018). Together, the integration of these modalities contributes a novel foundational framework to understand the operational links between face, brain, and social behaviour. These objectives include the most significant goals of current social neuroscience.

The Brain Function Lab at Yale School of Medicine under the direction of Professor Joy Hirsch recently acquired a state-of-the-art high density fNIRS instrument (LabNIRS, Shimadzu Japan) that has the capacity to record the brain haemodynamic response over a large number of channels achieving spatial resolution similar to fMRI. This fNIRS configuration is referred to as Diffuse Optical Tomography or HD-DOT (Eggebrecht et al Nature Photonics 2014) and enhances the mapping resolution of functional activity in the brain cortex. The enhanced neuroimaging information with this state-of-the-art high density fNIRS instrument; in combination with the quantitative markers of behaviour allow new approaches to investigate live interpersonal interactions, facial expressions, and the interrelationships between brain function, systemic physiological changes, and behaviour.

Person Specification
Applicants should have achieved (or are predicted) a first class or upper second class honours undergraduate degree (or equivalent international qualifications or experience) in either Computer Science, Engineering, Mathematics or Physics. An MSc is also preferred, though not essential. Applicants with degrees in Psychology or Cognitive Neuroscience are welcome but applicants must be able to demonstrate strong computational\programming skills.

Essential skills: - experience with computer programming (ideally Matlab) - experience of advanced data and signal analysis - hands-on experience of running experiments with human participants - experience of communicating scientific research (in project reports and talks)
Desirable skills: -high grades on relevant courses at BSc and MSc level -experience of research with neuroimaging data –experience with fNIRS neuroimaging -experience of working in a team.


Studentship Information
The starting date is 23rd September 2019. The contract is for 48 months and includes the 12 months of the MRes

If you have any scientific queries please contact Dr Ilias Tachtsidis:[Email Address Removed]

Applications (including a covering letter, CV and names of two referees) should be sent to Miss Mohini Nair ([Email Address Removed]), Medical Physics and Biomedical Engineering, who will also be happy to handle any informal enquiries.

Our department holds an Athena SWAN Bronze award, in recognition of our commitment to advancing gender equality.
For further information, please visit:
http://www.ucl.ac.uk/medphys/women-in-medical-physics