Rutger Vlek

The brain–computer interface cycle

Brain-computer interfaces (BCIs) have attracted much attention recently, triggered by new scientific progress in understanding brain function and by impressive applications. The aim of this review is to give an overview of the various steps in the BCI cycle, i.e., the loop from the measurement of brain activity, classification of data, feedback to the subject and the effect of feedback on brain activity. In this article we will review the critical steps of the BCI cycle, the present issues and state-of-the-art results. Moreover, we will develop a vision on how recently obtained results may contribute to new insights in neurocognition and, in particular, in the neural representation of perceived stimuli, intended actions and emotions. Now is the right time to explore what can be gained by embracing real-time, online BCI and by adding it to the set of experimental tools already available to the cognitive neuroscientist. We close by pointing out some unresolved issues and present our view on how BCI could become an important new tool for probing human cognition.

Music perception and imagery in EEG: Alpha band effects of task and stimulus

Previous work has shown that mental imagination of sound generally elicits an increase of alpha band activity (8-12 Hz) in the electroencephalogram (EEG). In addition, alpha activity has been shown to be related to aspects of music processing. In the current study, EEG signatures were investigated for perception and imagery of two different natural musical phrases. The responses are compared between tasks and between stimuli. For all tasks and stimuli, posterior alpha band activity was seen, but differences are shown in the power of this response. As expected, imagery resulted in a significantly stronger alpha activation than perception. The comparison of the averaged responses to the stimuli also showed a difference in alpha power, although this effect is seen in different directions. These results are interpreted to indicate that both the tasks and the stimuli modulate an attentional network, which may relate to the inhibition of non-task relevant cortical areas, as well as engagement with the music.

2009 Special Issue: A note on ethical aspects of BCI

This paper focuses on ethical aspects of BCI, as a research and a clinical tool, that are challenging for practitioners currently working in the field. Specifically, the difficulties involved in acquiring informed consent from locked-in patients are investigated, in combination with an analysis of the shared moral responsibility in BCI teams, and the complications encountered in establishing effective communication with media.

Decomposing rhythm processing: electroencephalography of perceived and self-imposed rhythmic patterns

Perceiving musical rhythms can be considered a process of attentional chunking over time, driven by accent patterns. A rhythmic structure can also be generated internally, by placing a subjective accent pattern on an isochronous stimulus train. Here, we investigate the event-related potential (ERP) signature of actual and subjective accents, thus disentangling low-level perceptual processes from the cognitive aspects of rhythm processing. The results show differences between accented and unaccented events, but also show that different types of unaccented events can be distinguished, revealing additional structure within the rhythmic pattern. This structure is further investigated by decomposing the ERP into subcomponents, using principal component analysis. In this way, the processes that are common for perceiving a pattern and self-generating it are isolated, and can be visualized for the tasks separately. The results suggest that top-down processes have a substantial role in the cerebral mechanisms of rhythm processing, independent of an externally presented stimulus.

Combined EEG-fNIRS Decoding of Motor Attempt and Imagery for Brain Switch Control: An Offline Study in Patients With Tetraplegia

Combining electrophysiological and hemodynamic features is a novel approach for improving current performance of brain switches based on sensorimotor rhythms (SMR). This study was conducted with a dual purpose: to test the feasibility of using a combined electroencephalogram/functional near-infrared spectroscopy (EEG-fNIRS) SMR-based brain switch in patients with tetraplegia, and to examine the performance difference between motor imagery and motor attempt for this user group. A general improvement was found when using both EEG and fNIRS features for classification as compared to using the single-modality EEG classifier, with average classification rates of 79% for attempted movement and 70% for imagined movement. For the control group, rates of 87% and 79% were obtained, respectively, where the “attempted movement” condition was replaced with “actual movement.” A combined EEG-fNIRS system might be especially beneficial for users who lack sufficient control of current EEG-based brain switches. The average classification performance in the patient group for attempted movement was significantly higher than for imagined movement using the EEG-only as well as the combined classifier, arguing for the case of a paradigm shift in current brain switch research.

Shared mechanisms in perception and imagery of auditory accents.

OBJECTIVE An auditory rhythm can be perceived as a sequence of accented (loud) and non-accented (soft) beats or it can be imagined. Subjective rhythmization refers to the induction of accenting patterns during the presentation of identical auditory pulses at an isochronous rate. It can be an automatic process, but it can also be voluntarily controlled. We investigated whether imagined accents can be decoded from brain signals on a single-trial basis, and if there is information shared between perception and imagery in the contrast of accents and non-accents. METHODS Ten subjects perceived and imagined three different metric patterns (two-, three-, and four-beat) superimposed on a steady metronome while electroencephalography (EEG) measurements were made. Shared information between perception and imagery EEG is investigated by means of principal component analysis and by means of single-trial classification. RESULTS Classification of accented from non-accented beats was possible with an average accuracy of 70% for perception and 61% for imagery data. Cross-condition classification yielded significant performance above chance level for a classifier trained on perception and tested on imagery data (up to 66%), and vice versa (up to 60%). CONCLUSIONS Results show that detection of imagined accents is possible and reveal similarity in brain signatures relevant to distinction of accents from non-accents in perception and imagery. SIGNIFICANCE Our results support the idea of shared mechanisms in perception and imagery for auditory processing. This is relevant for a number of clinical settings, most notably by elucidating the basic mechanisms of rhythmic auditory cuing paradigms, e.g. as used in motor rehabilitation or therapy for Parkinsons disease. As a novel Brain-Computer Interface (BCI) paradigm, our results imply a reduction of the necessary BCI training in healthy subjects and in patients.

Sequenced subjective accents for brain-computer interfaces.

Subjective accenting is a cognitive process in which identical auditory pulses at an isochronous rate turn into the percept of an accenting pattern. This process can be voluntarily controlled, making it a candidate for communication from human user to machine in a brain-computer interface (BCI) system. In this study we investigated whether subjective accenting is a feasible paradigm for BCI and how its time-structured nature can be exploited for optimal decoding from non-invasive EEG data. Ten subjects perceived and imagined different metric patterns (two-, three- and four-beat) superimposed on a steady metronome. With an offline classification paradigm, we classified imagined accented from non-accented beats on a single trial (0.5 s) level with an average accuracy of 60.4% over all subjects. We show that decoding of imagined accents is also possible with a classifier trained on perception data. Cyclic patterns of accents and non-accents were successfully decoded with a sequence classification algorithm. Classification performances were compared by means of bit rate. Performance in the best scenario translates into an average bit rate of 4.4 bits min(-1) over subjects, which makes subjective accenting a promising paradigm for an online auditory BCI.

Detection of event-related desynchronization during attempted and imagined movements in tetraplegics for brain switch control

Motor-impaired individuals such as tetraplegics could benefit from Brain-Computer Interfaces with an intuitive control mechanism, for instance for the control of a neuroprosthesis. Whereas BCI studies in healthy users commonly focus on motor imagery, for the eventual target users, namely patients, attempted movements could potentially be a more promising alternative. In the current study, EEG frequency information was used for classification of both imagined and attempted movements in tetraplegics. Although overall classification rates were considerably lower for tetraplegics than for the control group, both imagined and attempted movement were detectable. Classification rates were significantly higher for the attempted movement condition, with a mean rate of 77%. These results suggest that attempted movement is an appropriate task for BCI control in long-term paralysis patients.