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A Brain Network Processing the Age of Faces

Zitieren Sie bitte immer diese 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.zeige mehrzeige weniger

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Metadaten
Autor(en): György A. Homola, Saad Jbabdi, Christian F. Beckmann, Andreas J. Bartsch
URN:urn:nbn:de:bvb:20-opus-75513
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Medizinische Fakultät / Klinik und Poliklinik für Strahlentherapie
Sprache der Veröffentlichung:Englisch
Erscheinungsjahr:2012
Originalveröffentlichung / Quelle:In: PLoS One (2012) 7(11): e49451, doi:10.1371/journal.pone.0049451
Allgemeine fachliche Zuordnung (DDC-Klassifikation):6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Normierte Schlagworte (GND):Medizin
Datum der Freischaltung:27.03.2013
Sammlungen:Open-Access-Publikationsfonds / Förderzeitraum 2012
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung