Literature DB >> 31730780

Neuromagnetic correlates of hemispheric specialization for face and word recognition.

Saeko Inamizu1, Emi Yamada2, Katsuya Ogata2, Taira Uehara2, Jun-Ichi Kira3, Shozo Tobimatsu2.   

Abstract

The adult human brain appears to have specialized and independent neural systems for the visual processing of faces and words: greater selectivity for faces in the right hemisphere (RH) while greater selectivity for words in the left hemisphere (LH). Nevertheless, the nature of functional differences between the hemispheres is still largely unknown. To elucidate the hemispheric specialization for face and word recognition, event-related magnetic fields (ERFs) were recorded in young adults while they passively viewed faces and words presented either in the right visual field or in the left visual field. If the neural correlates of face recognition and word recognition reflect the same lateralization profile, then the lateralization of the magnetic source of the M170 component should follow a similar profile, with a greater M170 response for faces in the RH and a greater M170 response for words in the LH. We observed the expected finding of a larger M170 in the LH for words. Unexpectedly, a larger M170 response in the RH for faces was not found. Thus, the hemispheric organization of face recognition is different from that of word recognition in terms of specificity.
Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Face recognition; Fusiform face area; Magnetoencephalography; Visual word fusiform area; Word recognition

Mesh:

Year:  2019        PMID: 31730780     DOI: 10.1016/j.neures.2019.11.006

Source DB:  PubMed          Journal:  Neurosci Res        ISSN: 0168-0102            Impact factor:   3.304


  1 in total

1.  Optimum Feature Selection with Particle Swarm Optimization to Face Recognition System Using Gabor Wavelet Transform and Deep Learning.

Authors:  Sulayman Ahmed; Mondher Frikha; Taha Darwassh Hanawy Hussein; Javad Rahebi
Journal:  Biomed Res Int       Date:  2021-03-10       Impact factor: 3.411

  1 in total

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