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

Subject Area General, Cognitive and Mathematical Psychology
Human Cognitive and Systems Neuroscience
Term from 2017 to 2021
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 352324151
 
Final Report Year 2022

Final Report Abstract

The human face is a stimulus that is the continuous source of information about individuals around us. Gender, age, emotional state, trustworthiness, beauty are just a few examples of the many important properties of a face which determine our social life. Thus, it is not surprising that a great amount of experiments are performed every year to describe the details of face processing in the human brain. One of the most important tasks of a face is to convey information about the identity of others or in other words to support identification and recognition. We recognize the faces of our relatives, colleagues, and our favorite celebrities. Despite its obvious importance and the large number of studies published yearly, the neural background of face recognition is still unclear as of today. The major aim of the current proposal was to test, how the human brain enables us to acquire and maintain a stable representation about known, familiar persons, thereby supporting face recognition. The central hypothesis of the proposal is: instead of having one single face recognition unit or area, a hierarchical, but at the same time distributed, recurrent network is responsible for face identification and recognition. We aimed at testing this hypothesis, by using psychophysical methods together with transcranial magnetic stimulation (TMS), electrophysiological (EEG) and functional magnetic resonance imaging (fMRI) methods, combined with the most modern multivariate pattern analytical machine learning analyses. Specifically, we were interested how the occipital and various temporal cortical areas enable us to acquire and maintain a stable representation about known, familiar persons, thereby supporting face recognition. We split this question into two major parts. First, we tested how unfamiliar faces become familiar and which areas play a causal role in this process. We divided this issue further, into two separate experimental series. In the first we tested face learning via multiple instances, while in the second via additional semantic information. Our results suggest the necessity to reconsider the hierarchical face-perception models and support the distributed and recurrent models. In such models the earlier stage of face processing (for example in the OFA) is not merely a “gatekeeper” of facial information towards the ventral visual pathway but rather it plays a crucial role, presumably via recurrent connections, in the entire process of representation creation. Second, we studied the representation, its image-dependence, location, stability over time as well as its differences from the representation of novel faces. Stability was tested in one experimental series while another series tested the image-specificity/invariance and a third one tested the encoding of familiar/unfamiliar faces. Overall, our aim was to reveal the neural mechanisms that are responsible for the recognition of those faces/persons whom we are familiar with. Taken together, the experiments confirm our initial hypothesis in the sense that a hierarchical, but at the same time distributed, recurrent network is responsible for face recognition. These results challenge the current hierarchical models of face perception and suggest instead concerted and parallel activation of multiple nodes in the brain’s identity encoding network while processing information of familiar faces.

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