This work reports on physiological electroencephalographic (EEG) correlates in cognitive and emotional processes within the discrimination between synthetic and real faces visual stimuli. Human perception of manipulated data has been addressed in the literature from several perspectives. Researchers have investigated how the use of deep fakes alters people's ability in face-processing tasks, such as face recognition. Although recent studies showed that humans, on average, are still able to correctly recognize synthetic faces, this study investigates whether those findings still hold considering the latest advancements in AI-based, synthetic image creation. Specifically, 18-channels EEG signals from 21 healthy subjects were analyzed during a visual experiment where synthetic and actual emotional stimuli were administered. According to recent literature, participants were able to discriminate the real faces from the synthetic ones, by correctly classifying about 77% of all images. Preliminary encouraging results showed statistical significant differences in brain activation in both stimuli (synthetic and real) classification and emotional response.

Electroencephalographic Correlates in Synthetic and Real Emotional Face Stimulation / Tarchi, Pietro; Calà, Federico; Frassineti, Lorenzo; Lanata Antonio. - ELETTRONICO. - 2023:(2023), pp. 1-4. (Intervento presentato al convegno 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023) [10.1109/EMBC40787.2023.10340895].

Electroencephalographic Correlates in Synthetic and Real Emotional Face Stimulation

Tarchi, Pietro;Calà, Federico;Frassineti, Lorenzo;Lanata Antonio
Supervision
2023

Abstract

This work reports on physiological electroencephalographic (EEG) correlates in cognitive and emotional processes within the discrimination between synthetic and real faces visual stimuli. Human perception of manipulated data has been addressed in the literature from several perspectives. Researchers have investigated how the use of deep fakes alters people's ability in face-processing tasks, such as face recognition. Although recent studies showed that humans, on average, are still able to correctly recognize synthetic faces, this study investigates whether those findings still hold considering the latest advancements in AI-based, synthetic image creation. Specifically, 18-channels EEG signals from 21 healthy subjects were analyzed during a visual experiment where synthetic and actual emotional stimuli were administered. According to recent literature, participants were able to discriminate the real faces from the synthetic ones, by correctly classifying about 77% of all images. Preliminary encouraging results showed statistical significant differences in brain activation in both stimuli (synthetic and real) classification and emotional response.
2023
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023
Tarchi, Pietro; Calà, Federico; Frassineti, Lorenzo; Lanata Antonio
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1349313
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