Steady‐state visual evoked potentials as a research tool in social affective neuroscience

Abstract

Like many other primates, humans place a high premium on social information transmission and processing. One important aspect of this information concerns the emotional state of other individuals, conveyed by distinct visual cues such as facial expressions, overt actions, or by cues extracted from the situational context. A rich body of theoretical and empirical work has demonstrated that these socio-emotional cues are processed by the human visual system in a prioritized fashion, in the service of optimizing social behavior. Furthermore, socio-emotional perception is highly dependent on situational contexts and previous experience. Here, we review current issues in this area of research and discuss the utility of the steady-state visual evoked potential (ssVEP) technique for addressing key empirical questions. Methodological advantages and caveats are discussed with particular regard to quantifying time-varying competition among multiple perceptual objects, trial-by-trial analysis of visual cortical activation, functional connectivity, and the control of low-level stimulus features. Studies on facial expression and emotional scene processing are summarized, with an emphasis on viewing faces and other social cues in emotional contexts, or when competing with each other. Further, because the ssVEP technique can be readily accommodated to studying the viewing of complex scenes with multiple elements, it enables researchers to advance theoretical models of socio-emotional perception, based on complex, quasi-naturalistic viewing situations.

Sleepless and Desynchronized: Impaired Inter Trial Phase Coherence of Steady-State Potentials Following Sleep Deprivation

“…Despite identical sensory demands put forward by the ssVEP task, the ability to synchronize to the task in a consistent manner was dependent upon a rested night of sleep. Our findings further demonstrate that sleep deprivation can be reliably assessed by means of ssVEPs paradigms, shown to be sensitive to a wide range of tasks used in cognitive and clinical neuroscience (Norcia et al, 2015;Vialatte et al, 2010;Wieser et al, 2016). These results are in line with prior findings that demonstrate decreased phase consistency in sleep deprivation (Hoedlmoser et al, 2011), as well as studies that demonstrate the impact of fatigue on the amplitude of ssVEPs (Cao et al, 2014;Hoedlmoser et al, 2011).…”

An emergency call system for patients in locked‐in state using an SSVEP‐based brain switch

“…We used such a long epoch length to increase the accuracy of the SSVEP detection because reliability of the emergency call system was thought to be more important than the response time. Nevertheless, adopting a better feature extraction method such as canonical correlation analysis (CCA) would be considered in future studies to enhance the overall performance of our emergency call system because the use of CCA features enhanced the overall BCI performance in many recent SSVEP-based BCI studies (Wang et al, 2016;Wieser, Miskovic, & Keil, 2016;Zhang et al, 2013Zhang et al, , 2014Zhang et al, , 2015Zhang et al, , 2017. In addition, we asked the participants to gaze at the fixation cross during the idle state; however, this condition might not be realistic because many patients with ALS generally spend time watching TV.…”

What does the dot‐probe task measure? A reverse correlation analysis of electrocortical activity

“…For example, two fully overlapping stimuli flickering at different temporal rates evoke different electrophysiological response trains that can be separated as two distinct, narrow, peaks in the frequency spectrum of the electroencephalogram (EEG) recordings (Appelbaum, Wade, Vildavski, Pettet, & Norcia, 2006). The SSVEP frequency-tagging technique can also be applied to naturalistic nonoverlapping stimuli in complex arrays (Wieser, Miskovic, & Keil, 2016), as used in the present study.…”