Neural response to the visual familiarity of faces
Introduction
In two previous fMRI studies on familiar face recognition [12], [23] we have suggested that recognizing someone we know is the result of a spatially distributed process that involves not only visual cortical areas but also areas that are involved in other social and cognitive functions such as the theory of mind areas (anterior paracingulate and posterior superior temporal sulcus) [10], [11], the precuneus, the amygdala and the insula. We have hypothesized that different areas encode different types of information that support the successful recognition of a familiar individual [13]. While the precuneus and anterior temporal cortex [14], [24], [26], [32] might be involved in retrieval of information from long-term memory, the theory of mind areas might encode information about personality traits and mental states of a familiar individual [12], [23]. The emotional response that we experience when seeing a familiar face plays an important role in successful recognition of that individual [1], [12], [23] and is reflected by changes in activity in the amygdala and the insula.
In our functional model on face perception [17], we grouped face responsive regions in two systems: the core system that includes areas involved with the visual analysis of a face and the extended system that includes areas that are involved in the extraction of other non-visual information.
We were interested in isolating the effect of simple visual familiarity in face recognition. With this purpose, neural activity was recorded with fMRI while participants viewed faces that were visually familiar, due to experimentally induced learning, with no associated semantic information.
Based on our previous findings, we hypothesized that visual familiarity would modulate activity in the “core system”, namely the fusiform gyrus. We also predicted modulation of activity in parts of the extended system, such as in the precuneus, an area involved with the retrieval of episodic memories [3] and in the amygdala, a structure involved in detecting and processing unexpected or unfamiliar events with potential biological importance [5], [7], [12], [22], [23], [31].
We did not expect any modulation of activity in areas involved with the retrieval of personal traits such as the anterior paracingulate cortex [12], [23], [25] or in areas associated with retrieval of biographical information such as the anterior temporal regions [14], [24], [26], [30].
Section snippets
Subjects
Seven healthy right-handed volunteers with no history of neurological or psychiatric disease (four males and three females) participated in the experiment (mean age 30.7, range: 26–34). Subjects had normal or corrected-to-normal vision. All participants gave written informed consent.
Stimuli
Stimuli were faces and nonsense pictures (Fig. 1). Nonsense pictures were phase-scrambled images of the faces used in the study and matched the faces in terms of spatial frequencies and luminance.
Faces of 81
Behavioral results
Behavioral data from day 1 of the experiment did not show any difference in reaction time for the learned faces and the highly repeated novel faces (respectively, 457.5 ms, S.D. 195.4 versus 454.7 ms S.D. 189.7, p = 0.8).
The behavioral data from the training session on day 2 of the experiment demonstrated an improvement in performance through a faster reaction time (RT at the beginning of the training session = 1438.0 ms, S.D. 205.3 versus RT at the end of the training session = 285.4 ms, S.D. 60.5, p <
Discussion
Facial appearance is only one aspect of how we recognize known individuals. In two previous studies, we have demonstrated that recognizing familiar faces activates a distributed network of areas that involves not only the visual perceptual areas but also areas engaged in emotional response, such as the amygdala and the insula, and areas that are involved with social behavior and “theory of mind” [12], [13], [23]. According to our model of face perception [17], recognizing a face is the result
Acknowledgement
We would like to thank Alex Martin for helpful discussion at the inception of this project. We also would like to thank Carlo Cipolli for helpful comments.
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