A robust neural familiar face recognition response in a dynamic (periodic) stream of unfamiliar faces

Detecting a viewer’s familiarity with a face: Evidence from event‐related brain potentials and classifier analyses

“…Moreover, Yan and colleagues (Yan et al., 2020) reported false positive familiarity responses in five out of 14 participants ( p = .36) when faces were presented in upright orientation, and even in eight out of 14 participants ( p = .57) with inverted stimulus presentation (i.e., in the condition in which face recognition should be less likely). A further recent study (Yan & Rossion, 2020) reports reliable familiarity effects in all tested participants, which is similar to the present Experiment 1, but does not report a false alarm rate. Given the relatively small sample size in all experiments, including those we present here, there remains substantial uncertainty about the precision of these estimates (Cumming, 2012).…”

Differences in own-face but not own-name discrimination between autistic and neurotypical adults: A fast periodic visual stimulation-EEG study

“…Both faces and names elicited signals with high SNRs in bilateral parieto-occipital clusters, similar to the regions typically associated with face recognition ( Liu-Shuang et al., 2014 ; Retter & Rossion, 2016 ; Yan & Rossion, 2020 ), as well as in an additional frontocentral cluster ( Campbell et al., 2020 ).…”

“…This allows one to test whether the steady-state visual evoked potentials discriminate the property in which the oddball and standard stimuli differ, isolating this property from the lower-level processing of properties shared by both oddball and standard stimuli. It thus provides an ideal measure to identify specific aspects of face discrimination, such as discriminating between specific emotional expressions ( Coll et al., 2019 ) or different facial identities ( Liu-Shuang et al., 2014 ; Retter & Rossion, 2016 ; Yan & Rossion, 2020 ), respectively controlling for non-emotion- or non-identity-specific face-selective processes.…”

Implicit, automatic semantic word categorisation in the left occipito-temporal cortex as revealed by fast periodic visual stimulation

“…Considering its numerous advantages, using FPVS to study semantic/conceptual categorisation processes is extremely appealing. Up to now, the FPVS approach had been tested to probe automatic semantic categorisation using pictures of object categories ( Stothart et al, 2017 ; Milton et al, 2020 ) or faces (i.e., comparison of natural images of unfamiliar faces with famous faces associated with rich semantic information; Zimmermann et al, 2019 Yan and Rossion, 2020 ). However, selective neural responses to pictures or photographs of familiar items can be partly due to differential physical features rather than semantic knowledge.…”