Nikolas Williams

Bio: Nikolas Williams is an academic researcher from Macquarie University. The author has contributed to research in topics: Computer science & Electroencephalography. The author has an hindex of 6, co-authored 9 publications receiving 74 citations.

A validation of Emotiv EPOC Flex saline for EEG and ERP research.

Abstract: Background Previous work has validated consumer-grade electroencephalography (EEG) systems for use in research. Systems in this class are cost-effective and easy to set up and can facilitate neuroscience outside of the laboratory. The aim of the current study was to determine if a new consumer-grade system, the Emotiv EPOC Saline Flex, was capable of capturing research-quality data. Method The Emotiv system was used simultaneously with a research-grade EEG system, Neuroscan Synamps2, to collect EEG data across 16 channels during five well-established paradigms: (1) a mismatch negativity (MMN) paradigm that involved a passive listening task in which rare deviant (1,500 Hz) tones were interspersed amongst frequent standard tones (1,000 Hz), with instructions to ignore the tones while watching a silent movie; (2) a P300 paradigm that involved an active listening task in which participants were asked to count rare deviant tones presented amongst frequent standard tones; (3) an N170 paradigm in which participants were shown images of faces and watches and asked to indicate whether the images were upright or inverted; (4) a steady-state visual evoked potential (SSVEP) paradigm in which participants passively viewed a flickering screen (15 Hz) for 2 min; and (5) a resting state paradigm in which participants sat quietly with their eyes open and then closed for 3 min each. Results The MMN components and P300 peaks were equivalent between the two systems (BF10 = 0.25 and BF10 = 0.26, respectively), with high intraclass correlations (ICCs) between the ERP waveforms (>0.81). Although the N170 peak values recorded by the two systems were different (BF10 = 35.88), ICCs demonstrated that the N170 ERP waveforms were strongly correlated over the right hemisphere (P8; 0.87-0.97), and moderately-to-strongly correlated over the left hemisphere (P7; 0.52-0.84). For the SSVEP, the signal-to-noise ratio (SNR) was larger for Neuroscan than Emotiv EPOC Flex (19.94 vs. 8.98, BF10 = 51,764), but SNR z-scores indicated a significant brain response at the stimulus frequency for both Neuroscan (z = 12.47) and Flex (z = 11.22). In the resting state task, both systems measured similar alpha power (BF10 = 0.28) and higher alpha power when the eyes were closed than open (BF10 = 32.27). Conclusions The saline version of the Emotiv EPOC Flex captures data similar to that of a research-grade EEG system. It can be used to measure reliable auditory and visual research-quality ERPs. In addition, it can index SSVEP signatures and is sensitive to changes in alpha oscillations.

10 years of EPOC: A scoping review of Emotiv’s portable EEG device

Abstract: BACKGROUND Commercially-made low-cost electroencephalography (EEG) devices have become increasingly available over the last decade. One of these devices, Emotiv EPOC, is currently used in a wide variety of settings, including brain-computer interface (BCI) and cognitive neuroscience research. PURPOSE The aim of this study was to chart peer-reviewed reports of Emotiv EPOC projects to provide an informed summary on the use of this device for scientific purposes. METHODS We followed a five-stage methodological framework for a scoping review that included a systematic search using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. We searched the following electronic databases: PsychINFO, MEDLINE, Embase, Web of Science, and IEEE Xplore. We charted study data according to application (BCI, clinical, signal processing, experimental research, and validation) and location of use (as indexed by the first author’s address). RESULTS We identified 382 relevant studies. The top five publishing countries were the United States (n = 35), India (n = 25), China (n = 20), Poland (n = 17), and Pakistan (n = 17). The top five publishing cities were Islamabad (n = 11), Singapore (n = 10), Cairo, Sydney, and Bandung (n = 7 each). Most of these studies used Emotiv EPOC for BCI purposes (n = 277), followed by experimental research (n = 51). Thirty-one studies were aimed at validating EPOC as an EEG device and a handful of studies used EPOC for improving EEG signal processing (n = 12) or for clinical purposes (n = 11). CONCLUSIONS In its first 10 years, Emotiv EPOC has been used around the world in diverse applications, from control of robotic limbs and wheelchairs to user authentication in security systems to identification of emotional states. Given the widespread use and breadth of applications, it is clear that researchers are embracing this technology.

Assessing early processing of eye gaze in schizophrenia: measuring the cone of direct gaze and reflexive orienting of attention

Abstract: Introduction: The accurate discrimination of another person’s eye-gaze direction is vital as it provides a cue to the gazer’s focus of attention, which in turn supports joint attention. Patients with schizophrenia have shown a “direct gaze bias” when judging gaze direction. However, current tasks do not dissociate an early perceptual bias from high-level top-down effects. We investigated early stages of gaze processing in schizophrenia by measuring perceptual sensitivity to fine deviations in gaze direction (i.e., the cone of direct gaze: CoDG) and ability to reflexively orient to locations cued by the same deviations.Methods: Twenty-four patients and 26 controls completed a CoDG discrimination task that used realistic direct-face images with six fine degrees of deviation (i.e., 3, 6 or 9 pixels to the left and right) and direct gaze, and a gaze cueing task that assessed reflexive orienting to the same fine-grained deviations.Results: Our data showed patients exhibited no impairment in gaze discri...

Should I Trust You? Autistic Traits Predict Reduced Appearance-Based Trust Decisions

Abstract: Facial impressions of trustworthiness guide social decisions in the general population, as shown by financial lending in economic Trust Games. As an exception, autistic boys fail to use facial impressions to guide trust decisions, despite forming typical facial trustworthiness impressions (Ewing et al., 2015). Here, we tested whether this dissociation between forming and using facial impressions of trustworthiness extends to neurotypical men with high levels of autistic traits. Forty-six Caucasian men completed a multi-turn Trust Game, a facial trustworthiness impressions task, the Autism-Spectrum Quotient, and two Theory of Mind tasks. As hypothesized, participants’ levels of autistic traits had no observed effect on the impressions formed, but negatively predicted the use of those impressions in trust decisions. Thus, the dissociation between forming and using facial impressions of trustworthiness extends to the broader autism phenotype. More broadly, our results identify autistic traits as an important source of individual variation in the use of facial impressions to guide behaviour. Interestingly, failure to use these impressions could potentially represent rational behaviour, given their limited validity.

An Introduction To The Event Related Potential Technique

Abstract: Thank you for downloading an introduction to the event related potential technique. Maybe you have knowledge that, people have look hundreds times for their favorite readings like this an introduction to the event related potential technique, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some malicious bugs inside their laptop.

A Database of Comprehensive Clinical, Endophenotypic and Genetic Data for Aetiological Studies of Schizophrenia

Abstract: Objective: This article describes the establishment of the Australian Schizophrenia Research Bank (ASRB), which operates to collect, store and distribute linked clinical, cognitive, neuroimaging and genetic data from a large sample of people with schizophrenia and healthy controls. Method: Recruitment sources for the schizophrenia sample include a multi-media national advertising campaign, inpatient and community treatment services and non-government support agencies. Healthy controls have been recruited primarily through multi-media advertisements. All participants undergo an extensive diagnostic and family history assessment, neuropsychological evaluation, and blood sample donation for genetic studies. Selected individuals also complete structural MRI scans. Results: Preliminary analyses of 493 schizophrenia cases and 293 healthy controls are reported. Mean age was 39.54 years (SD = 11.1) for the schizophrenia participants and 37.38 years (SD = 13.12) for healthy controls. Compared to the controls, features of the schizophrenia sample included a higher proportion of males (cases 65.9%; controls 46.8%), fewer living in married or de facto relationships (cases 16.1%; controls 53.6%) and fewer years of education (cases 13.05, SD = 2.84; controls 15.14, SD = 3.13), as well as lower current IQ (cases 102.68, SD = 15.51; controls 118.28, SD = 10.18). These and other sample characteristics are compared to those reported in another large Australian sample (i.e. the Low Prevalence Disorders Study), revealing some differences that reflect the different sampling methods of these two studies. Conclusion: The ASRB is a valuable and accessible schizophrenia research facility for use by approved scientific investigators. As recruitment continues, the approach to sampling for both cases and controls will need to be modified to ensure that the ASRB samples are as broadly representative as possible of all cases of schizophrenia and healthy controls.

EEG based stress level identification

Abstract: This paper investigates detection of patterns in brain waves while induced with mental stress. Electroencephalogram (EEG) is the most commonly used brain signal acquisition method as it is simple, economical and portable. An automatic EEG based stress recognition system is designed and implemented in this study with two effective stressors to induce different levels of mental stress. The Stroop colour-word test and mental arithmetic test are used as stressors to induce low level and high level of stress respectively, and their relevant C# applications are developed in Microsoft Visual Studio to interface with Emotiv Epoc device. Power band features from EEG signals are analyzed and using the relative difference of beta and alpha power as feature along with Support Vector Machine as classifier, three-levels of stress can be recognized with an accuracy of 75%. For two-level stress analysis, accuracy of 88% and 96% are achieved for Stroop colour-word test and mental arithmetic test respectively.