Face-selective responses in combined EEG/MEG recordings with fast periodic visual stimulation (FPVS)

Autor: F. Magnabosco, Olaf Hauk, Grace E. Rice, Bruno Rossion, M. A. Lambon Ralph, A. Volfart
Přispěvatelé: Cognition and Brain Sciences Unit (MRC CBU), University of Cambridge [UK] (CAM), Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université Catholique de Louvain = Catholic University of Louvain (UCL), Service de neurologie [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Medical Research Council UK ( MC_UU_00005/18 to OH, GER, MLR), AV was supported by a doctoral grant from the Universitéde Lorraine and a Lorraine Universitéd’Excellence / DrEAM grant., Hauk, Olaf [0000-0003-0817-6054], Apollo - University of Cambridge Repository
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Adult
Male
genetic structures
Computer science
Cognitive Neuroscience
[SDV]Life Sciences [q-bio]
Source estimation
Neurosciences. Biological psychiatry. Neuropsychiatry
Electroencephalography
Signal-To-Noise Ratio
Frequency tagging
behavioral disciplines and activities
Facial recognition system
Article
Correlation
03 medical and health sciences
Young Adult
0302 clinical medicine
medicine
Humans
Time domain
Face recognition
030304 developmental biology
0303 health sciences
Brain Mapping
medicine.diagnostic_test
business.industry
Brain
Magnetoencephalography
Pattern recognition
medicine.anatomical_structure
nervous system
Neurology
Categorization
Pattern Recognition
Visual
Scalp
Face (geometry)
Face categorization
Female
Artificial intelligence
business
Facial Recognition
psychological phenomena and processes
030217 neurology & neurosurgery
Photic Stimulation
RC321-571
Zdroj: NeuroImage
NeuroImage, Elsevier, 2021, 242, pp.118460. ⟨10.1016/j.neuroimage.2021.118460⟩
NeuroImage, Vol 242, Iss, Pp 118460-(2021)
Neuroimage
ISSN: 1053-8119
1095-9572
Popis: Highlights • FPVS allows high-SNR EEG/MEG recordings of face-selective brain responses. • High comparable z-scores obtained for EEG and MEG in all but one participants. • Face-selective responses right-lateralized in EEG. • Face-selective responses bilateral but numerically right-lateralized in MEG. • Strongest face-selective sources anterior to base frequency response.
Fast periodic visual stimulation (FPVS) allows the recording of objective brain responses of human face categorization (i.e., generalizable face-selective responses) with high signal-to-noise ratio. This approach has been successfully employed in a number of scalp electroencephalography (EEG) studies but has not been used with magnetoencephalography (MEG) yet, let alone with combined MEG/EEG recordings and distributed source estimation. Here, we presented various natural images of faces periodically (1.2 Hz) among natural images of objects (base frequency 6 Hz) whilst recording simultaneous EEG and MEG in 15 participants. Both measurement modalities showed face-selective responses at 1.2 Hz and harmonics across participants, with high and comparable signal-to-noise ratio (SNR) in about 3 min of stimulation. The correlation of face categorization responses between EEG and two MEG sensor types was lower than between the two MEG sensor types, indicating that the two sensor modalities provide independent information about the sources of face-selective responses. Face-selective EEG responses were right-lateralized as reported previously, and were numerically but non-significantly right-lateralized in MEG data. Distributed source estimation based on combined EEG/MEG signals confirmed a more bilateral face-selective response in visual brain regions located anteriorly to the common response to all stimuli at 6 Hz and harmonics. Conventional sensor and source space analyses of evoked responses in the time domain further corroborated this result. Our results demonstrate that FPVS in combination with simultaneously recorded EEG and MEG may serve as an efficient localizer paradigm for human face categorization.
Databáze: OpenAIRE
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