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Simon Faghel-Soubeyrand, Frédéric Gosselin; Task-modulated integration of facial features in the brain. Journal of Vision 2017;17(10):268. doi: 10.1167/17.10.268.
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The presence of intermodulation frequencies (IM) in an EEG frequency-tagging paradigm indicates non-linear integration of multiple tagged visual features by the brain (Norcia et al., 2015). Despite its growing use in high-level vision, the efficiency of IM as an index of non-linear processing remains unclear, mostly because the importance of the non-linear integration for the task is typically unknown. We assessed the efficiency of IM using a realistic face processing task which we know implements a simple XOR non-linear function—wink detection. On each trial, EEG activity was recorded while each feature of a face flickered at a specific frequency (e.g. left eye: 6 Hz, right eye: 3Hz and mouth: 8 Hz). Subjects had to fixate a central cross and detect winks (one eye closed rather than no eyes/both eyes closed) in the non-linear condition, and the closing of one of the two eyes in the linear condition. Comparisons of brain responses between tasks during identical visual stimulations revealed that left/right-eye tagged IM—the neural response imputable to the non-linear integration of both features—were stronger in occipito-temporal electrodes when this particular feature integration was useful for the task at hand (i.e. wink condition, F(1,362)=13.98,p< .001). The magnitude of the eye-pair IM was also associated with faster response time (RT) in the non-linear wink detection condition (r= -.73,p< .05), but not in the linear control task (r=-.10,p>.70). Oppositely, the magnitude of the mouth tagged neural responses (unrelated to both tasks) was associated with longer RT in both conditions (r1=.67,p1< .05;r2 =.85,p2< .05), most likely reflecting a distractor effect. While the magnitude of feature frequency-tags clearly outweighed that of IM (average SNR were ~15 and ~1.75, respectively), the present results clearly demonstrates that IM can be an effective neural correlate of non-linear visual integration processing.
Meeting abstract presented at VSS 2017
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