Face processing is a fundamental aspect of human social interaction. It enables us to recognize individuals, interpret their emotional states, and make judgements based on facial cues - capabilities that are essential to our everyday social experiences. Our exceptional aptitude for these tasks underscores the importance of face processing in human cognition and social communication (Frith, 2009). However, face processing is not uniformly efficient across individuals, nor is it immune to disruption. Selective deficits in face processing, such as severe difficulty in recognizing individuals (prosopagnosia), can be highly debilitating, leading to social anxiety, loss of self-confidence and restricted social circles (Yardley et al., 2008). Hence, understanding the neural underpinnings of face processing holds substantial promise for improving diagnostic and therapeutic strategies for such conditions.
Neuroimaging research has significantly advanced our understanding of the brain's mechanisms for perceiving and interpreting faces. This progress has led to the identification of a 'face processing network' (Duchaine & Yovel, 2015; Kanwisher & Yovel, 2009), consisting of multiple regions that specialize in distinct aspects of face perception, such as identifying facial features, detecting emotional expressions, understanding eye gaze and discerning identity (Collins & Olson, 2014; Ishai, 2008; Rhodes et al., 2012). Two key nodes in this network are the fusiform face area (FFA) and the occipital face area (OFA) which are both critical to the formation of a complete and coherent face percept (Kanwisher & Yovel, 2009). Indeed, lesions in either or both regions may lead to prosopagnosia (Duchaine & Yovel, 2015). However, despite the recognized importance of FFA and OFA, the precise functional contribution of each region to face perception remains a topic of ongoing debate and research (Rossion, 2014).
Significant advances in computational processing power in fMRI research now facilitate real-time analysis of brain activity. This development allows for intriguing applications such as neurofeedback (NFB), a technique that provides individuals with immediate feedback on their brain activity, enabling them to consciously regulate activity in specific regions (Sitaram et al., 2017). Leveraging this tool, the first study of this thesis addressed the ongoing debate concerning the specific functional roles of FFA and OFA in face perception. By examining the effects of modulating activity within these regions on subsequent behavioral performance during a face processing task, we aimed to dissect their individual contributions to face detection and recognition.
In the second study, we capitalized on one of the insights gained from the first study; the pivotal role of FFA in face detection. Again, we employed fMRI-NFB but this time to enhance face perceptual abilities. Targeting only FFA, our goal was to improve the brain’s ability to process faces at a subliminal level. That is, before they reach conscious awareness. Crucially, we explored whether this would translate into improved face detection, as measured both behaviorally and in terms of functional processing using fMRI. The results not only confirmed FFA’s role in face detection but also served as a proof of concept for potential interventions designed to improve perceptual abilities in clinical populations, such as hemineglect patients.
