Using perceptual learning to understand and influence face recognition

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Perceptual learning is a fundamental cognitive skill. It can be defined as an enhancement in the ability to distinguish between similar stimuli (that otherwise would be very hard to tell apart) as a consequence of experience with them, or with stimuli similar to the target stimuli. The proposed project focuses on the development of this phenomenon as a key factor to our ability to recognise faces. Further, by using a range of neuroscience techniques (EEG/ERP, tDCS, fMRI, TMS) in conjunction with the behavioural designs I have developed, I will investigate methods to improve this perceptual skill and define specific brain structures responsible for the control and development of this phenomenon. So, basically, I aim to find out how we improve at telling things apart (discrimination) and to discover ways of enhancing this ability.I will start by developing the case for perceptual learning as a key contributor to one of the most robust cognitive phenomenon in face recognition i.e. the composite face effect. This refers to individuals' decreased ability to recognise the top half of one face presented in composite with the bottom half of another face when the composite is upright and aligned than when the two halves are offset laterally (misalignment). By using novel categories of prototype-defined chequerboards which participants will be pre-exposed to during the study procedure, I would expect to show a similar composite effect for familiar chequerboards to that usually found with faces. This will be our index of perceptual learning.The project will then continue by using different neurostimulation techniques (tDCS and TMS) to selectively increase and decrease the composite effect for chequerboards and that for faces. Through a combination of tDCS and EEG techniques, this project will also reveal how specific brain responses usually found for faces, can also be found for familiar chequerboards and be altered by neurostimulation. Finally, a combination of tDCS and fMRI will help to localise more precisely the brain structures involved in perceptual learning.This project will provide us with insights into the mechanisms that characterise the development and control of perceptual learning and will extend perceptual learning to face recognition by showing how similar effects to those usually found for faces can be found for categories of stimuli that participants had never seen before entering the lab. It will also provide evidence for the neurocognitive basis of perceptual learning. We will use these results to devise methods of training that can enhance our discrimination abilities in various domains. It would allow us to tailor training programmes (e.g. involving stimuli such as faces, fingerprints, cervical smears, mammograms) to provide maximum benefit in terms of performance by the trainee. As an example, this research would be suitable for enhancing the face recognition skills of frontline and intelligence staff, and one might be able to selectively increase the effectiveness of this training through the use of mobile neuroscience techniques based on the Starstim EEG/tDCS system. It would also give us insights into how to design artificial systems for the detection and recognition of such stimuli, which would be of interest to companies specialised in computer software or apps for face recognition.