A survey of the dummy face and human face stimuli used in BCI paradigm

Chen, Long; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

doi:10.1016/j.jneumeth.2014.10.002

Cited by 31 publications

(24 citation statements)

References 47 publications

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“…Furthermore, no significant difference was found between the two paradigms across VPP and P300 ( t = 0.35, p > 0.05, df = 9 for VPP, and t = 1.45, p > 0.05, df = 9 for P300, Figures 4(a) and 4(c)). Meanwhile, the value of P300 was smaller than that of the P300 reported in other studies [19, 24]. Although the N400 at Cz from STF-P showed no significant difference compared with that from F-P ( t = −0.65, p > 0.05, df = 9; Figure 4(d)), the stability of N400 from STF-P ( t = −1.70, p > 0.05, df = 9; Figure 4(f)) was better than that from F-P ( t = −2.69, p < 0.05, df = 9; Figure 4(e)).…”

Section: Resultscontrasting

confidence: 69%

Comparison of the BCI Performance between the Semitransparent Face Pattern and the Traditional Face Pattern

Cheng

Jin

Wang

2017

Computational Intelligence and Neuroscience

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Brain-computer interface (BCI) systems allow users to communicate with the external world by recognizing the brain activity without the assistance of the peripheral motor nervous system. P300-based BCI is one of the most common used BCI systems that can obtain high classification accuracy and information transfer rate (ITR). Face stimuli can result in large event-related potentials and improve the performance of P300-based BCI. However, previous studies on face stimuli focused mainly on the effect of various face types (i.e., face expression, face familiarity, and multifaces) on the BCI performance. Studies on the influence of face transparency differences are scarce. Therefore, we investigated the effect of semitransparent face pattern (STF-P) (the subject could see the target character when the stimuli were flashed) and traditional face pattern (F-P) (the subject could not see the target character when the stimuli were flashed) on the BCI performance from the transparency perspective. Results showed that STF-P obtained significantly higher classification accuracy and ITR than those of F-P (p < 0.05).

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Section: Resultscontrasting

confidence: 69%

Comparison of the BCI Performance between the Semitransparent Face Pattern and the Traditional Face Pattern

Cheng

Jin

Wang

2017

Computational Intelligence and Neuroscience

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“…Various neural activities can be used as features in electroencephalogram (EEG)-based BCI systems. P300 evoked potentials [5][6][7][8][9][10], slow cortical potentials, steady state visually evoked potentials [11,12], and event-related desynchronization (ERD) [ [14] are extensively used in BCI systems.…”

Section: Introductionmentioning

confidence: 99%

Improved SFFS method for channel selection in motor imagery based BCI

et al. 2016

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“…The latter could be extended to BCI-based technical solutions by using face familiarity within stimulus presentation patterns to elicit face-specific ERP components (i.e., N170) and by utilizing unique brain activity elicited by well-known (familiar) faces. This could increase the speed and fluency of communication for people using a visual stimuli-driven BCI (Zhang et al, 2012; Kashihara, 2014; Yeom et al, 2014; Chen et al, 2015). Combining BCIs with near-infrared spectroscopy systems that have been shown to be sensitive to localized brain dysfunction in individuals with ASD (Iwanaga et al, 2013) could improve signal processing and analysis (Coyle et al, 2007).…”

Section: Face Recognition Phenomenon In the Era Of Advanced Neurotechmentioning

confidence: 99%

Neurobiological Aspects of Face Recognition: The Role of Oxytocin

Lopatina

Komleva

Gorina

et al. 2018

Front. Behav. Neurosci.

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Face recognition is an important index in the formation of social cognition and neurodevelopment in humans. Changes in face perception and memory are connected with altered sociability, which is a symptom of numerous brain conditions including autism spectrum disorder (ASD). Various brain regions and neuropeptides are implicated in face processing. The neuropeptide oxytocin (OT) plays an important role in various social behaviors, including face and emotion recognition. Nasal OT administration is a promising new therapy that can address social cognition deficits in individuals with ASD. New instrumental neurotechnologies enable the assessment of brain region activation during specific social tasks and therapies, and can characterize the involvement of genes and peptides in impaired neurodevelopment. The present review sought to discuss some of the mechanisms of the face distinguishing process, the ability of OT to modulate social cognition, as well as new perspectives and technologies for research and rehabilitation of face recognition.

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A survey of the dummy face and human face stimuli used in BCI paradigm

Cited by 31 publications

References 47 publications

Comparison of the BCI Performance between the Semitransparent Face Pattern and the Traditional Face Pattern

Comparison of the BCI Performance between the Semitransparent Face Pattern and the Traditional Face Pattern

Improved SFFS method for channel selection in motor imagery based BCI

Neurobiological Aspects of Face Recognition: The Role of Oxytocin

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