Empirical Evaluation of the Emotiv EPOC BCI Headset for the Detection of Mental Actions

A new paper-and-pencil test of spatial visualization was constructed from the figures used in the chronometric study of Shepard and Metzler (1971). In large samples, the new test displayed substantial internal consistency (Kuder-Richardson 20 = .88), a test-retest reliability (.83), and consistent sex differences over the entire range of ages investigated. Correlations with other measures indicated strong association with tests of spatial visualization and virtually no association with tests of verbal ability.

This study examined the role of self-reported attentional control in regulating attentional biases related to trait anxiety. Simple detection targets were preceded by cues labeling potential target locations as threatening (likely to result in negative feedback) or safe (likely to result in positive feedback). Trait anxious participants showed an early attentional bias favoring the threatening location 250 ms after the cue and a late bias favoring the safe location 500 ms after the cue. The anxiety-related threat bias was moderated by attentional control at the 500-ms delay: Anxious participants with poor attentional control still showed the threat bias, whereas those with good control were better able to shift from the threatening location. Thus, skilled control of voluntary attention may allow anxious persons to limit the impact of threatening information.

Recent advances in analysis of brain signals, training patients to control these signals, and improved computing capabilities have enabled people with severe motor disabilities to use their brain signals for communication and control of objects in their environment, thereby bypassing their impaired neuromuscular system. Non-invasive, electroencephalogram (EEG)-based brain-computer interface (BCI) technologies can be used to control a computer cursor or a limb orthosis, for word processing and accessing the internet, and for other functions such as environmental control or entertainment. By re-establishing some independence, BCI technologies can substantially improve the lives of people with devastating neurological disorders such as advanced amyotrophic lateral sclerosis. BCI technology might also restore more effective motor control to people after stroke or other traumatic brain disorders by helping to guide activity-dependent brain plasticity by use of EEG brain signals to indicate to the patient the current state of brain activity and to enable the user to subsequently lower abnormal activity. Alternatively, by use of brain signals to supplement impaired muscle control, BCIs might increase the efficacy of a rehabilitation protocol and thus improve muscle control for the patient.