The ventral visual pathway and the construction of identity-specific representation

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The major objective of the present proposal is to better understand how the brain encodes faces for recognition. We will use psychophysical methods together with transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) to test how the occipito-temporal and anterior-temporal cortical areas of the human brain enable us to acquire and maintain a stable representation about known, familiar persons, thereby supporting face recognition. The central hypothesis of the proposal is that instead of having a single face recognition area a hierarchical, but distributed and recurrent network is responsible for face recognition. For testing this hypothesis we study the role of the occipital face area (OFA) and the anterior temporal lobe (ATL) in recognition processes, as these two areas are located towards opposite ends of the proposed hierarchy. We split our major question into two parts. First, using TMS, we will test the role of OFA/ATL in the process as faces transition from unfamiliar to familiar. We will compare the effect of OFA and ATL stimulation as participants acquire identity-specific information in two fundamentally different ways. Participants will either be exposed to a large amount of naturally variable faces to facilitate the creation of a statistically based average faces or they will see faces along additional person-related semantic information (names, job-titles). We will evaluate the causal roles of OFA and ATL in these tasks. We expect that the manner how the stimulation of OFA/ATL interferes with learning during the two tasks will give us information regarding the structure of the face-processing network. Second, we will study the acquired familiar face representation within the ventral visual system. In psychophysical experiments we will test its stability over time. In fMRI-guided, state-dependent TMS experiments we will test its image independence within the OFA and ATL. Finally, using fMRI and a novel version of multivariate pattern analysis (representational similarity analysis) we will test the differences and similarities of the fine-grained representation of unfamiliar versus familiar faces. Overall, our aim is to reveal the neural mechanisms that are responsible for face recognition.