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Visual angles and emotional valence affect temporal dynamics of neural representations of facial expression: An MEG study

  • Sanjeev Nara
  • , Dheeraj Rathee
  • , Nicola Molinaro
  • , Naomi Du Bois
  • , Braj Bhushan
  • , Girijesh Prasad

Research output: Contribution to journalArticlepeer-review

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Abstract

Emotion processing has been a focus of research in Cognitive Neuroscience for decades. While the evoked neural markers as brain activations in response to different emotions have been reported, the temporal dynamics of emotion processing have received little attention. Furthermore, behavioral studies have found that the right side of the human face expresses emotions more accurately than the left side. Therefore, accounting for both the content of the emotion and the visual angle of the presentation from the viewer’s perspective, we have investigated temporal dynamics and variability in the processing of happy and sad emotions using magnetoencephalography (MEG), when the visual angle of presentation was either Positive (right side of the face) or Negative (left side of the face). Our results showed that decodable processing of happy emotions emerged earlier than that for sad emotions, irrespective of visual angle. However, the amplitude of the evoked response to sad emotions was higher than that to happy emotions, when faces were presented at Positive visual angles only. Source reconstructed Event Related Fields (ERFs) showed localized activities in ventral and dorsal streams including fusiform gyrus, lingual gyrus, putamen and pre and post central gyrus. Multivariate pattern analysis also demonstrated successful decoding of happy and sad emotions only when the facial expression was viewed from a positive visual angle.
Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume33
Early online date26 Nov 2024
DOIs
Publication statusPublished online - 26 Nov 2024

Bibliographical note

Publisher Copyright:
© 2024 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

Funding

This research was partly supported by the project BES-2016-077560 funded by the Spanish Ministry of Economy and Competitiveness (MINECO) awarded to SN and NM. SN also acknowledges the support from EMBO short term fellowship. BB was supported through Science & Engineering Research Board (SERB), Govt. of India, grant no. MTR/2019/000224. This work was supported in part by Northern Ireland Functional Brain Mapping (NIFBM) Facility Project funded through InvestNI and the Ulster University under the Grant 1303/101154803, the MRC UK MEG Partnership Grant MR/K005464/1 and the DfE ISPF Project 610124: A UK-LMIC Research Network For Autism Spectrum Disorder (ULMiRN-ASD).

FundersFunder number
MTR/2019/000224
Medical Research CouncilMR/K005464/1
1303/101154803
610124

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being
    2. SDG 10 - Reduced Inequalities
      SDG 10 Reduced Inequalities

    Keywords

    • Magnetoencephalography (MEG)
    • Temporal dynamics
    • Emotion processing
    • Multivariate pattern analysis (MVPA)

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