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Cross-Modal Integration of Identity and Gender Information Through Faces and Voices Involves a Similar Cortical Network

  • Salvatore Campanella
  • Frédéric Joassin
Chapter

Abstract

We investigate the cerebral cross-modal interactions between human faces and voices involved during gender and identity categorization in two separate functional magnetic resonance imaging (fMRI) studies. In each of these experiments, participants were scanned in four runs that contained three conditions consisting in the presentation of faces, voices, or congruent face–voice pairs. The task consisted in categorizing each trial (visual, auditory, or associations) according to its gender or identity. The subtraction between the bimodal condition and the sum of the unimodal ones, as well as psychophysiological interaction analyses (PPI), were performed. Main results suggest that the cross-modal auditory–visual categorization of human gender and identity is sustained by a network of highly similar cerebral regions. This network included several regions such as the unimodal visual and auditory regions processing the perceived faces and voices and inter-connected via a subcortical relay located in the striatum, the left superior parietal gyrus, part of a larger parieto-motor network dispatching the attentional resources to the visual and auditory modalities, and the right inferior frontal gyrus sustaining the integration of the semantically congruent information into a coherent multimodal representation. Therefore, we suggest that cross-modal processing of human stimuli requires the activation of a network of cortical regions, including both unimodal visual and auditory regions and supramodal parietal and frontal regions involved in the integration of both faces and voices and in the cross-modal attentional processes.

Keywords

Inferior Frontal Gyrus Fusiform Face Area Bimodal Condition Calcarine Sulcus Auditory Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Laboratory of Psychological MedicineFree University of BrusselsBrusselsBelgium
  2. 2.CHU Brugmann, Psychiatry Department (EEG)The Belgian Fund for Scientific Research (FNRS)BrusselsBelgium
  3. 3.Clinique de la mémoireCHU Ambroise ParéMonsBelgium

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