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Steady-state visual evoked potentials (SSVEPs), the brain response to visual flicker stimulation, have proven beneficial in both research and clinical applications. Despite the practical advantages of stimulation at high frequencies in terms of visual comfort and safety, high frequency-SSVEPs have not received enough attention and little is known about the mechanisms behind their generation and propagation in time and space. In this study, we investigated the origin and propagation of SSVEPs in the gamma frequency band (40-60 Hz) by studying the dynamic properties of EEG in 32 subjects. Using low-resolution brain electromagnetic tomography (sLORETA) we identified the cortical sources involved in SSVEP generation in that frequency range to be in the primary visual cortex, Brodmann areas 17, 18 and 19 with minor contribution from sources in central and frontal sites. We investigated the SSVEP propagation as measured on the scalp in the framework of the existing theories regarding the neurophysiological mechanism through which the SSVEP spreads through the cortex. We found a progressive phase shift from posterior parieto-occipital sites over the cortex with a phase velocity of approx. 8-14 m/s and wavelength of about 21 and 24 cm. The SSVEP spatial properties appear sensitive to input frequency with higher stimulation frequencies showing a faster propagation speed.

Objective: Brain computer interfaces (BCIs) are slowly making their appearance on the consumer market, accompanied by a higher popularity among the general public. This new group of users requires easy-to-use headsets with robustness to non-precise placement. In this paper, an optimized fixed montage EEG headset for VEP BCIs is proposed., Approach: The proposed layout covers only the most relevant area with large sensors to account for slight misplacement. To obtain large sensors, without having them physically available, we tie multiple sensors together and simulate the effect by averaging the signal of multiple sensors., Main Results: In simulations based on recorded 256-channel EEG data, it is shown that a circular center-surround configuration with sensor tying, leading to only eight channels covering a large part of the occipital lobe, can provide high performance and good robustness to misplacement. Automatically optimized layouts were unable to achieve better performance, demonstrating the utility of this manual design. Finally, the performance and benefits of sensor tying in the manual design are then validated in a physical experiment., Significance: The resulting proposed layout fulfills most requirements of an easy to use consumer EEG headset.

The current work investigates the brain activation shared between perception and imagery of music as measured with electroencephalography (EEG). Meta-analyses of four separate EEG experiments are presented, each focusing on perception and imagination of musical sound, with differing levels of stimulus complexity. Imagination and perception of simple accented metronome trains, as manifested in the clock illusion, as well as monophonic melodies are discussed, as well as more complex rhythmic patterns and ecologically natural music stimuli. By decomposing the data with principal component analysis (PCA), similar component distributions are found to explain most of the variance in each experiment. All data sets show a fronto-central and a more central component as the largest sources of variance, fitting with projections seen for the network of areas contributing to the N1/P2 complex. We expanded on these results using tensor decomposition. This allows us to add in the tasks to find shared activation, but does not make assumptions of independence or orthogonality and calculates the relative strengths of these components for each task. The components found in the PCA were shown to be further decomposable into parts that load primarily on to the perception or imagery task, or both, thereby adding more detail. It is shown that the frontal and central components have multiple parts that are differentially active during perception and imagination. A number of possible interpretations of these results are discussed, taking into account the different stimulus materials and measurement conditions., (Copyright © 2012 Elsevier Inc. All rights reserved.)

This paper investigates the effect of varying different stimulus properties on performance of the visual speller. Each of the different stimulus properties has been tested in previous literature and has a known effect on visual speller performance. This paper investigates whether a combination of these types of stimuli can lead to a greater improvement. It describes an experiment aimed at answering the following questions. (i) Does visual speller performance suffer from high stimulus rates? (ii) Does an increase in stimulus rate lead to a lower training time for an online visual speller? (iii) What aspect of the difference in the event related potential to a flash or a flip stimulus causes the increase in accuracy. (iv) Can an error-correcting (dense) stimulus code overcome the reduction in performance associated with decreasing target-to-target intervals? We found that higher stimulus rates can improve the visual speller performance and can lead to less time required to train the system. We also found that a proper stimulus code can overcome the stronger response to rows and columns, but cannot greatly improve speller performance.

Brain Computer Interfaces could be useful in rehabilitation of movement, perhaps also for gait. Until recently, research on movement related brain signals has not included measuring electroencephalography (EEG) during walking, because of the potential artifacts. We investigated if it is possible to measure the event Related Desynchronization (ERD) and event related spectral perturbations (ERSP) during walking. Six subjects walked on a treadmill with a slow speed, while EEG, electromyography (EMG) of the neck muscles and step cycle were measured. A Canonical Correlation Analysis (CCA) was used to remove EMG artifacts from the EEG signals. It was shown that this method correctly deleted EMG components. A strong ERD in the mu band and a somewhat less strong ERD in the beta band were found during walking compared to a baseline period. Furthermore, lateralized ERSPs were found, depending on the phase in the step cycle. It is concluded that this is a promising method to use in BCI research on walking. These results therefore pave the way for using brain signals related to walking in a BCI context.

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., (Copyright © 2011 Elsevier B.V. All rights reserved.)

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.

The Farwell and Donchin matrix speller is well known as one of the highest performing brain-computer interfaces (BCIs) currently available. However, its use of visual stimulation limits its applicability to users with normal eyesight. Alternative BCI spelling systems which rely on non-visual stimulation, e.g. auditory or tactile, tend to perform much more poorly and/or can be very difficult to use. In this paper we present a novel extension of the matrix speller, based on flipping the letter matrix, which allows us to use the same interface for visual, auditory or simultaneous visual and auditory stimuli. In this way we aim to allow users to utilize the best available input modality for their situation, that is use visual + auditory for best performance and move smoothly to purely auditory when necessary, e.g. when disease causes the user's eyesight to deteriorate. Our results on seven healthy subjects demonstrate the effectiveness of this approach, with our modified visual + auditory stimulation slightly out-performing the classic matrix speller. The purely auditory system performance was lower than for visual stimulation, but comparable to other auditory BCI systems.

In brain-imaging research, we are often interested in making quantitative claims about effects across subjects. Given that most imaging data consist of tens to thousands of spatially correlated time series, inter-subject comparisons are typically accomplished with simple combinations of inter-subject data, for example methods relying on group means. Further, these data are frequently taken from reduced channel subsets defined either a priori using anatomical considerations, or functionally using p-value thresholding to choose cluster boundaries. While such methods are effective for data reduction, means are sensitive to outliers, and current methods for subset selection can be somewhat arbitrary. Here, we introduce a novel "partial-ranking" approach to test for inter-subject agreement at the channel level. This non-parametric method effectively tests whether channel concordance is present across subjects, how many channels are necessary for maximum concordance, and which channels are responsible for this agreement. We validate the method on two previously published and two simulated EEG data sets.

Abstract: Objective: Simultaneous tactile finger stimulation evokes transient ERP responses that are smaller than the linear summation of ERP responses to individual stimulation. Occlusion and lateral inhibition are two possible mechanisms responsible for this effect. The present study disentangles these two effects using steady-state somatosensory evoked potentials (SSSEP). Simultaneous stimulation on adjacent and distant finger pairs with the same and different stimulation frequencies are compared. Methods: The index finger (IF), middle finger (MF) and little finger (LF) were mechanically stimulated with a frequency of 18, 22 or 26Hz, respectively. Stimulation was applied for each finger separately, and for the IF (18Hz) in combination with either the MF or LF for 22 and 26Hz, respectively. A measure for interaction (IR) was calculated for the P60 component and the SSSEP amplitude. Results: Significant interactions were found in both the P60 response and in the SSSEP response. Stimulation of adjacent finger combinations caused more interaction than distant finger combinations. No difference was found between stimulation of two fingers with the same or a different frequency. Conclusions: Our results indicate that lateral inhibition is mainly responsible for the interaction effect. Significance: These observations provide further insight in the mechanisms behind interaction between somatosensory inputs. [ABSTRACT FROM AUTHOR]

Abstract: 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 Parkinson’s 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. [Copyright &y& Elsevier]