Error-related brain activity in relation to psychopathic traits in multiproblem young adults: An ERP study
فعالیت مغزی مرتبط با خطا در رابطه با صفات روانی در بزرگسالان جوان چندبعدی: یک مطالعه ERP-2019
One of the most prominent issues in psychopathy is the inability to adequately monitor one’s performance and learn from one’s mistakes. We investigated the relationship between psychopathic traits, as measured with the Youth Psychopathy Inventory – Short Version, and both early and late error-related brain activity in an at-risk sample of male young adults. These multi-problem young adults (age 18–27) are severely dysfunctional in society and suffer from multiple problems including financial problems, delinquency, psychological problems, and drug use. Our final sample consisted of 115 multi-problem young adults and 26 controls. Participants performed an Eriksen-Flanker task during EEG measurements. We used the difference wave of the error-related negativity (ΔERN) as a measure of early error processing and the error positivity (Pe) as a measure of late error processing. Multi-problem young adults showed reduced ERN amplitudes compared to controls, but did not differ in Pe amplitude. We found no statistically significant relation between psychopathic traits and ERN and Pe amplitudes within the multi-problem group. Thus, we found evidence for dysfunctional error-processing in multi-problem young adults compared to controls. However, within the multi-problem sample we did not find evidence for a relationship between psychopathic traits and dysfunctional error-processing. One explanation may be that this is due to the specific developmental stage of our young adult participants in which a transition between error-processing deficits, as present in adolescents high in psychopathic traits, and error-processing overcompensation, as present in adults high in psychopathic traits, may occur.
Keywords: Psychopathy | Electroencephalography | Event-related potential | Young adulthood |Error-processing | Error-related negativity
Towards an accessible use of smartphone-based social networks through brain-computer interfaces
به سمت استفاده در دسترس از شبکه های اجتماعی مبتنی بر تلفن های هوشمند از طریق رابط های مغز و کامپیوتر-2019
This study presents an asynchronous P300-based Brain–Computer Interface (BCI) system for controlling social networking features of a smartphone. There are very few BCI studies based on these mobile devices and, to the best of our knowledge, none of them supports networking applications or are focused on an assistive context, failing to test their systems with motor-disabled users. Therefore, the aim of the present study is twofold: (i) to design and develop an asynchronous P300-based BCI system that allows users to control Twitter and Telegram in an Android device; and (ii) to test the usefulness of the developed system with a motor-disabled population in order to meet their daily communication needs. Row-col paradigm (RCP) is used in order to elicitate the P300 potentials in the scalp of the user, which are immediately processed for decoding the user’s intentions. The expert system integrates a decision-making stage that analyzes the attention of the user in real-time, providing a comprehensive and asynchronous control. These intentions are then translated into application commands and sent via Bluetooth to the mobile de- vice, which interprets them and provides visual feedback to the user. During the assessment, both quali- tative and quantitative metrics were obtained, and a comparison among other state-ofthe-art studies was performed as well. The system was tested with 10 healthy control subjects and 18 motor-disabled sub- jects, reaching average online accuracies of 92.3% and 80.6%, respectively. Results suggest that the system allows users to successfully control two socializing features of a smartphone, bridging the accessibility gap in these trending devices. Our proposal could become a useful tool within households, rehabilitation centers or even companies, opening up new ways to support the integration of motor-disabled people, and making an impact in their quality of life by improving personal autonomy and self-dependence.
Keywords: Brain-computer interface (BCI) | Smartphones | Asynchronous control | Social networks | P300 Event-related potentials | Electroencephalography (EEG)