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A Brain Network Processing the Age of Faces

Please always quote using this URN: urn:nbn:de:bvb:20-opus-75513
  • Age is one of the most salient aspects in faces and of fundamental cognitive and social relevance. Although face processing has been studied extensively, brain regions responsive to age have yet to be localized. Using evocative face morphs and fMRI, we segregate two areas extending beyond the previously established face-sensitive core network, centered on the inferior temporal sulci and angular gyri bilaterally, both of which process changes of facial age. By means of probabilistic tractography, we compare their patterns of functionalAge is one of the most salient aspects in faces and of fundamental cognitive and social relevance. Although face processing has been studied extensively, brain regions responsive to age have yet to be localized. Using evocative face morphs and fMRI, we segregate two areas extending beyond the previously established face-sensitive core network, centered on the inferior temporal sulci and angular gyri bilaterally, both of which process changes of facial age. By means of probabilistic tractography, we compare their patterns of functional activation and structural connectivity. The ventral portion of Wernicke’s understudied perpendicular association fasciculus is shown to interconnect the two areas, and activation within these clusters is related to the probability of fiber connectivity between them. In addition, post-hoc age-rating competence is found to be associated with high response magnitudes in the left angular gyrus. Our results provide the first evidence that facial age has a distinct representation pattern in the posterior human brain. We propose that particular face-sensitive nodes interact with additional object-unselective quantification modules to obtain individual estimates of facial age. This brain network processing the age of faces differs from the cortical areas that have previously been linked to less developmental but instantly changeable face aspects. Our probabilistic method of associating activations with connectivity patterns reveals an exemplary link that can be used to further study, assess and quantify structure-function relationships.show moreshow less

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Metadaten
Author: György A. Homola, Saad Jbabdi, Christian F. Beckmann, Andreas J. Bartsch
URN:urn:nbn:de:bvb:20-opus-75513
Document Type:Journal article
Faculties:Medizinische Fakultät / Klinik und Poliklinik für Strahlentherapie
Language:English
Year of Completion:2012
Source:In: PLoS One (2012) 7(11): e49451, doi:10.1371/journal.pone.0049451
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
GND Keyword:Medizin
Release Date:2013/03/27
Collections:Open-Access-Publikationsfonds / Förderzeitraum 2012
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung