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Soltani Dehaghani N, Maess B, Khosrowabadi R, Zarei M, Braeutigam S. Comparing Face and Object Processing in Perception and Recognition. BCN 2024; 15 (6) :795-806
URL: http://bcn.iums.ac.ir/article-1-1830-fa.html

Introduction: Faces can be speedily processed, although they convey an immense amount of information. Hence, in psychophysiological experiments, human faces constitute very special stimuli. Numerous studies have investigated the electrophysiological correlates of face processing, showing the existence of multiple event-related components. Nevertheless, dissimilarities in various levels of processing are still controversial. In this study, we used magnetoencephalography (MEG) to examine how facial processing is different in perception and recognition from object processing. 
Methods: In this event‐related potential study, the differences between face and object processing stages were assessed. The participants were 22 healthy individuals. Three types of stimuli, including human face, monkey face, and motorbike, were projected for 200 ms onto a screen placed 90 cm in front of participants’ eyes while they sat under the MEG helmet. The participants viewed images of the same type in sequential order and had to decide the equality of the second image compared to the first image in a response window of 1 second. This procedure was repeated 48 times per stimulus. Additionally, we compared the perception and recognition per stimulus type. The neuromagnetic responses were recorded with the VectorViewTM MEG system. We used the FieldTrip toolbox for EEG/MEG-analysis.
Results: Our results confirmed the face-selectivity for the M170 component, but not always for the M100 component. We also observed a unique speed pattern for the M170 component in perception and recognition at the onset and the peak time.
Conclusion: Our findings showed an early face-selective component in recognition but not always in perception. Considering the onset and the peak time, there is no difference between various comparisons in this early component.