Brain-computer interfaces (BCI) are communication systems that allow people to send messages or commands without movement. BCIs rely on different types of signals in the electroencephalogram (EEG), typically P300s, steady-state visually evoked potentials (SSVEP), or event-related desynchronization. Early BCI systems were often evaluated with a selected group of subjects. Also, many articles do not mention data from subjects who performed poorly. These and other factors have made it difficult to estimate how many people could use different BCIs. The present study explored how many subjects could use an SSVEP BCI. We recorded data from 53 subjects while they participated in 1–4 runs that were each 4 min long. During these runs, the subjects focused on one of four LEDs that each flickered at a different frequency. The eight channel EEG data were analyzed with a minimum energy parameter estimation algorithm and classified with linear discriminant analysis into one of the four classes. Online results showed that SSVEP BCIs could provide effective communication for all 53 subjects, resulting in a grand average accuracy of 95.5%. About 96.2% of the subjects reached an accuracy above 80%, and nobody was below 60%. This study showed that SSVEP based BCI systems can reach very high accuracies after only a very short training period. The SSVEP approach worked for all participating subjects, who attained accuracy well above chance level. This is important because it shows that SSVEP BCIs could provide communication for some users when other approaches might not work for them.

Neuroscientists have long debated whether some regions of the human brain are exclusively engaged in a single specific mental process. Consistent with this view, fMRI has revealed cortical regions that respond selectively to certain stimulus classes such as faces. However, results from multivoxel pattern analyses (MVPA) challenge this view by demonstrating that category-selective regions often contain information about "nonpreferred" stimulus dimensions. But is this nonpreferred information causally relevant to behavior? Here we report a rare opportunity to test this question in a neurosurgical patient implanted for clinical reasons with strips of electrodes along his fusiform gyri. Broadband gamma electrocorticographic responses in multiple adjacent electrodes showed strong selectivity for faces in a region corresponding to the fusiform face area (FFA), and preferential responses to color in a nearby site, replicating earlier reports. To test the causal role of these regions in the perception of nonpreferred dimensions, we then electrically stimulated individual sites while the patient viewed various objects. When stimulated in the FFA, the patient reported seeing an illusory face (or "facephene"), independent of the object viewed. Similarly, stimulation of color-preferring sites produced illusory "rainbows." Crucially, the patient reported no change in the object viewed, apart from the facephenes and rainbows apparently superimposed on them. The functional and anatomical specificity of these effects indicate that some cortical regions are exclusively causally engaged in a single specific mental process, and prompt caution about the widespread assumption that any information scientists can decode from the brain is causally relevant to behavior.

Background: Electrical stimulation of the cortex using subdurally implanted electrodes can causally reveal structural connectivity by eliciting cortico-cortical evoked potentials (CCEPs). While many studies have demonstrated the potential value of CCEPs, the methods to evaluate them were often relatively subjective, did not consider potential artifacts, and did not lend themselves to systematic scientific investigations. New method: We developed an automated and quantitative method called SIGNI (Stimulation-Induced Gamma-based Network Identification) to evaluate cortical population-level responses to electrical stimulation that minimizes the impact of electrical artifacts. We applied SIGNI to electrocorticographic (ECoG) data from eight human subjects who were implanted with a total of 978 subdural electrodes. Across the eight subjects, we delivered 92 trains of approximately 200 discrete electrical stimuli each (amplitude 4–15 mA) to a total of 64 electrode pairs. Results: We verified SIGNI's efficacy by demonstrating a relationship between the magnitude of evoked cortical activity and stimulation amplitude, as well as between the latency of evoked cortical activity and the distance from the stimulated locations. Conclusions: SIGNI reveals the timing and amplitude of cortical responses to electrical stimulation as well as the structural connectivity supporting these responses. With these properties, it enables exploration of new and important questions about the neurophysiology of cortical communication and may also be useful for pre-surgical planning.

Recent advances in humanoid robot technologies have made it possible to inhabit a humanlike form located at a remote place. This allows the participant to interact with others in that space and experience the illusion that the participant is actually present in the remote space. Moreover, with these humanlike forms, it may be possible to induce a full-body ownership illusion, where the robot body is perceived to be one's own. We show that it is possible to induce the full-body ownership illusion over a remote robotic body with a highly robotic appearance. Additionally, our results indicate that even with nonmanual control of a remote robotic body, it is possible to induce feelings of agency and illusions of body ownership. Two established control methods, an SSVEP-based BCI and eye tracking, were tested as a means of controlling the robot's gesturing. Our experience and the results indicate that both methods are tractable for immersive control of a humanoid robot in a social telepresence setting.

OBJECTIVE Electrocortical stimulation (ECS) is the gold standard for functional brain mapping; however, precise functional mapping is still difficult in patients with language deficits. High gamma activity (HGA) between 80 and 140 Hz on electrocorticography is assumed to reflect localized cortical processing, whereas the cortico-cortical evoked potential (CCEP) can reflect bidirectional responses evoked by monophasic pulse stimuli to the language cortices when there is no patient cooperation. The authors propose the use of "passive" mapping by combining HGA mapping and CCEP recording without active tasks during conscious resections of brain tumors. METHODS Five patients, each with an intraaxial tumor in their dominant hemisphere, underwent conscious resection of their lesion with passive mapping. The authors performed functional localization for the receptive language area, using real-time HGA mapping, by listening passively to linguistic sounds. Furthermore, single electrical pulses were delivered to the identified receptive temporal language area to detect CCEPs in the frontal lobe. All mapping results were validated by ECS, and the sensitivity and specificity were evaluated. RESULTS Linguistic HGA mapping quickly identified the language area in the temporal lobe. Electrical stimulation by linguistic HGA mapping to the identified temporal receptive language area evoked CCEPs on the frontal lobe. The combination of linguistic HGA and frontal CCEPs needed no patient cooperation or effort. In this small case series, the sensitivity and specificity were 93.8% and 89%, respectively. CONCLUSIONS The described technique allows for simple and quick functional brain mapping with higher sensitivity and specificity than ECS mapping. The authors believe that this could improve the reliability of functional brain mapping and facilitate rational and objective operations. Passive mapping also sheds light on the underlying physiological mechanisms of language in the human brain.