From full calibration to zero training for a code-modulated visual evoked potentials for brain-computer interface.

Objective.Typically, a brain-computer interface (BCI) is calibrated using user- and session-specific data because of the individual idiosyncrasies and the non-stationary signal properties of the electroencephalogram (EEG). Therefore, it is normal for BCIs to undergo a time-consuming passive training stage that prevents users from directly operating them. In this study, we systematically reduce the training data set in a stepwise fashion, to ultimately arrive at a calibration-free method for a code-modulated visually evoked potential (cVEP)-based BCI to fully eliminate the tedious training stage.Approach.In an extensive offline analysis, we compare our sophisticated encoding model with a traditional event-related potential (ERP) technique. We calibrate the encoding model in a standard way, with data limited to a single class while generalizing to all others and without any data. In addition, we investigate the feasibility of the zero-training cVEP BCI in an online setting.Main results.By adopting the encoding model, the training data can be reduced substantially, while maintaining both the classification performance as well as the explained variance of the ERP method. Moreover, with data from only one class or even no data at all, it still shows excellent performance. In addition, the zero-training cVEP BCI achieved high communication rates in an online spelling task, proving its feasibility for practical use.Significance.To date, this is the fastest zero-training cVEP BCI in the field, allowing high communication speeds without calibration while using only a few non-invasive water-based EEG electrodes. This allows us to skip the training stage altogether and spend all the valuable time on direct operation. This minimizes the session time and opens up new exciting directions for practical plug-and-play BCI. Fundamentally, these results validate that the adopted neural encoding model compresses data into event responses without the loss of explanatory power compared to using full ERPs as a template.

The N400 for brain computer interfacing: complexities and opportunities.

The N400 is an event related potential that is evoked in response to conceptually meaningful stimuli. It is for instance more negative in response to incongruent than congruent words in a sentence, and more negative for unrelated than related words following a prime word. This sensitivity to semantic content of a stimulus in relation to the mental context of an individual makes it a signal of interest for Brain Computer Interfaces. A complicating aspect is the number of factors that can affect the N400 amplitude. In this paper, we provide an accessible overview of this range of N400 effects, and survey the three main BCI application areas that currently exploit the N400: (1) exploiting the semantic processing of faces to enhance matrix speller performance, (2) detecting language processing in patients with Disorders of Consciousness, and (3) using semantic stimuli to probe what is on a user's mind. Drawing on studies from these application areas, we illustrate that the N400 can successfully be exploited for BCI purposes, but that the signal-to-noise ratio is a limiting factor, with signal strength also varying strongly across subjects. Furthermore, we put findings in context of the general N400 literature, noting open questions and identifying opportunities for further research.

Low channel count montages using sensor tying for VEP-based BCI.

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.

Author Correction: 2600-years of stratospheric volcanism through sulfate isotopes.

The authors became aware of a mistake in the data and axis labeling in Fig. 2 in the original version of the Article. Specifically, the authors mistakenly copied and pasted a formula for background correction instead of the actual values. As a result of this, Fig. 3 was updated to replace the incorrect label 'sulfate flux (kg km-2)' with the correct 'sulfate concentrations (ng g-1)' on the far-left y-axes in both panels, and to add the correct data for Δ33S, as given by the red dotted lines. The correct version of Fig. 3 is shown below as Fig. 1, which replaced the previous incorrect version, shown below as Fig. 2. This has been corrected in both the PDF and the HTML versions of the Article. The findings and interpretations in the original Article are based on the correct dataset, and this error does not affect the original discussion or conclusions of the Article. The authors apologize for the confusion caused by this mistake.

2600-years of stratospheric volcanism through sulfate isotopes.

High quality records of stratospheric volcanic eruptions, required to model past climate variability, have been constructed by identifying synchronous (bipolar) volcanic sulfate horizons in Greenland and Antarctic ice cores. Here we present a new 2600-year chronology of stratospheric volcanic events using an independent approach that relies on isotopic signatures (Δ33S and in some cases Δ17O) of ice core sulfate from five closely-located ice cores from Dome C, Antarctica. The Dome C stratospheric reconstruction provides independent validation of prior reconstructions. The isotopic approach documents several high-latitude stratospheric events that are not bipolar, but climatically-relevant, and diverges deeper in the record revealing tropospheric signals for some previously assigned bipolar events. Our record also displays a collapse of the Δ17O anomaly of sulfate for the largest volcanic eruptions, showing a further change in atmospheric chemistry induced by large emissions. Thus, the refinement added by considering both isotopic and bipolar correlation methods provides additional levels of insight for climate-volcano connections and improves ice core volcanic reconstructions.

Identifying the Attended Speaker Using Electrocorticographic (ECoG) Signals.

People affected by severe neuro-degenerative diseases (e.g., late-stage amyotrophic lateral sclerosis (ALS) or locked-in syndrome) eventually lose all muscular control. Thus, they cannot use traditional assistive communication devices that depend on muscle control, or brain-computer interfaces (BCIs) that depend on the ability to control gaze. While auditory and tactile BCIs can provide communication to such individuals, their use typically entails an artificial mapping between the stimulus and the communication intent. This makes these BCIs difficult to learn and use. In this study, we investigated the use of selective auditory attention to natural speech as an avenue for BCI communication. In this approach, the user communicates by directing his/her attention to one of two simultaneously presented speakers. We used electrocorticographic (ECoG) signals in the gamma band (70-170 Hz) to infer the identity of attended speaker, thereby removing the need to learn such an artificial mapping. Our results from twelve human subjects show that a single cortical location over superior temporal gyrus or pre-motor cortex is typically sufficient to identify the attended speaker within 10 s and with 77% accuracy (50% accuracy due to chance). These results lay the groundwork for future studies that may determine the real-time performance of BCIs based on selective auditory attention to speech.

Comparing tactile and visual gaze-independent brain-computer interfaces in patients with amyotrophic lateral sclerosis and healthy users.

OBJECTIVE: Brain-computer interfaces (BCI) tested in patients often are gaze-dependent, while these intended users could possibly lose the ability to focus their gaze. Therefore, a visual and a tactile gaze-independent spelling system were investigated. METHODS: Five patients with amyotrophic lateral sclerosis (ALS) tested a visual Hex-o-Spell and a tactile speller. Six healthy participants were also included, mainly to evaluate the tactile stimulators. RESULTS: A significant attentional modulation was seen in the P300 for the Hex-o-Spell and in the N2 for the tactile speller. Average on-line classification performance for selecting a step in the speller was above chance level (17%) for both spellers. However, average performance was higher for the Hex-o-Spell (88% and 85% for healthy participants and patients, respectively) than for the tactile speller (56% and 53%, respectively). Likewise, bitrates were higher for the Hex-o-Spell compared with the tactile speller, and in the subjective usability a preference for the Hex-o-Spell was found. CONCLUSIONS: The Hex-o-Spell outperformed the tactile speller in classification performance, bit rate and subjective usability. SIGNIFICANCE: This is the first study showing the possible use of tactile and visual gaze-independent BCI spelling systems by ALS patients with mild to moderate disabilities.

Interactions between pre-processing and classification methods for event-related-potential classification: best-practice guidelines for brain-computer interfacing.

Detecting event related potentials (ERPs) from single trials is critical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging signal detection problem. Previous work has tended to focus on how best to detect a single ERP type (such as the visual oddball response). However, the underlying ERP detection problem is essentially the same regardless of stimulus modality (e.g., visual or tactile), ERP component (e.g., P300 oddball response, or the error-potential), measurement system or electrode layout. To investigate whether a single ERP detection method might work for a wider range of ERP BCIs we compare detection performance over a large corpus of more than 50 ERP BCI datasets whilst systematically varying the electrode montage, spectral filter, spatial filter and classifier training methods. We identify an interesting interaction between spatial whitening and regularised classification which made detection performance independent of the choice of spectral filter low-pass frequency. Our results show that pipeline consisting of spectral filtering, spatial whitening, and regularised classification gives near maximal performance in all cases. Importantly, this pipeline is simple to implement and completely automatic with no expert feature selection or parameter tuning required. Thus, we recommend this combination as a "best-practice" method for ERP detection problems.

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.

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 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.

P300 audio-visual speller.

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.

A graphical model framework for decoding in the visual ERP-based BCI speller.

We present a graphical model framework for decoding in the visual ERP-based speller system. The proposed framework allows researchers to build generative models from which the decoding rules are obtained in a straightforward manner. We suggest two models for generating brain signals conditioned on the stimulus events. Both models incorporate letter frequency information but assume different dependencies between brain signals and stimulus events. For both models, we derive decoding rules and perform a discriminative training. We show on real visual speller data how decoding performance improves by incorporating letter frequency information and using a more realistic graphical model for the dependencies between the brain signals and the stimulus events. Furthermore, we discuss how the standard approach to decoding can be seen as a special case of the graphical model framework. The letter also gives more insight into the discriminative approach for decoding in the visual speller system.

Transient and steady-state responses to mechanical stimulation of different fingers reveal interactions based on lateral inhibition.

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.

A linear feature space for simultaneous learning of spatio-spectral filters in BCI.

It is shown how two of the most common types of feature mapping used for classification of single trial Electroencephalography (EEG), i.e. spatial and frequency filtering, can be equivalently performed as linear operations in the space of frequency-specific detector covariance tensors. Thus by first mapping the data to this space, a simple linear classifier can directly learn optimal spatial + frequency filters. Significantly, if the classifier's loss function is convex, learning these filters is a convex minimisation problem. It is also shown how to pre-process the data such that the resulting decision function is robust to the biases inherent in EEG data. Further, based upon ideas from Max Margin Matrix Factorisation, it is shown how the trace norm can be used to select solutions which have low rank. Low rank solutions are preferred as they reflect prior information about the types of EEG signals we expect to see, i.e. that the classifiable information is contained in only a few spatio/spectral pairs. They are also easier to interpret. This feature-space transformation is compared with the Common-Spatial-Patterns on simulated and real Imagined Movement Brain Computer Interface (BCI) data and shown to give state-of-the-art performance.

Overlap and refractory effects in a brain-computer interface speller based on the visual P300 event-related potential.

We reveal the presence of refractory and overlap effects in the event-related potentials in visual P300 speller datasets, and we show their negative impact on the performance of the system. This finding has important implications for how to encode the letters that can be selected for communication. However, we show that such effects are dependent on stimulus parameters: an alternative stimulus type based on apparent motion suffers less from the refractory effects and leads to an improved letter prediction performance.

Sulphur isotopes and the search for life: strategies for identifying sulphur metabolisms in the rock record and beyond.

The search for life can only be as successful as our understanding of the tools we use to search for it. Here we present new sulphur isotope data (32S, 33S, 34S, 36S) from a variety of modern marine environments and use these observations, along with previously published work, to contribute to this search. Specifically, we use these new data to gain a sense of life's influences on the sulphur isotope record and to distinguish these biologically influenced signatures from their non-biological counterparts. This treatment extends sulphur isotope analyses beyond traditional (34S/32S) measures and employs trace isotope relationships (33S/32S, 36S/32S), as the inclusion of these isotopes provides unique information about biology and its role in the sulphur cycle through time. In the current study we compare and contrast isotope effects produced by sulphur-utilizing microorganisms (experimental), modern and ancient sedimentary records (observational) and non-biological reactions (theoretical). With our collective search for life now extending to neighbouring planets, we present this study as a first step towards more fully understanding the capability of the sulphur isotope system as a viable tool for life detection, both on Earth and beyond.

Mass-independent sulfur of inclusions in diamond and sulfur recycling on early Earth.

Populations of sulfide inclusions in diamonds from the Orapa kimberlite pipe in the Kaapvaal-Zimbabwe craton, Botswana, preserve mass-independent sulfur isotope fractionations. The data indicate that material was transferred from the atmosphere to the mantle in the Archean. The data also imply that sulfur is not well mixed in the diamond source regions, allowing for reconstruction of the Archean sulfur cycle and possibly offering insight into the nature of mantle convection through time.

Twins with oesophageal atresia and the CHARGE association.

Twins are rarely concordant for oesophageal atresia and tracheo-oesophageal fistula. Such a case is presented and their similar associated anomalies described. The CHARGE association is considered as a possible diagnosis and the aetiological implications considered.

Mass-independent isotopic compositions in terrestrial and extraterrestrial solids and their applications.

In 1983, Thiemens and Heidenreich reported the first chemically produced mass-independent isotope effect. This work has been shown to have a wide range of applications, including atmospheric chemistry, solar system evolution, and chemical physics. This work has recently been reviewed (Weston, R. E. Chem. Rev. 1999, 99, 2115-2136; Thiemens, M. H. Science 1999, 283, 341-345). In this Account, observations of mass-independent isotopic compositions in terrestrial and Martian solids are reviewed. A wide range of applications, including formation and transport of aerosols in the present atmosphere, chemistry of ancient atmospheres and oceans, history and coupling of the atmosphere-surface in the Antarctic dry valleys, origin and evolution of oxygen in the Earth's earliest environment, and the chemistry of the atmosphere and surface of Mars, are discussed.