Enhancement and optimization of a multi-command-based brain-computer interface

Brain-computer interfaces (BCI) assist disabled person to control many appliances without any physically interaction (e.g., pressing a button). SSVEP is brain activities elicited by evoked signals that are observed by visual stimuli paradigm. In this dissertation were addressed the problems which are oblige more usability of BCI-system by optimizing and enhancing the performance using particular design. Main contribution of this work is improving brain reaction response depending on focal approaches

Investigating the function of alpha frequency oscillatory activity

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonA fundamental challenge in modern neuroscience is to understand the role of synchronous oscillatory activity of groups of neurons in information processing. This thesis addressed the problem of how alpha frequency oscillatory activity might help control the flow of information from both the external world and from higher cognitive areas (responsible for inhibitory control, top-down and bottom-up information flow). A series of experiments investigated how alpha neuronal dynamics might aid/control cognition. In order to study the functional significance of alpha frequency oscillatory activity, the effects on performance in cognitive tasks of alpha activity directly elicited using photic stimulation were examined. Initially, we were interested in the role of alpha oscillations in information transfer across cortical areas, which was probed using a numerical Stroop task with every trial preceded by a flicker prime. The incongruent trials of the Stroop task introduce a conflict between competing responses which results in people being slower in responses to the task compared with congruent trials. That slower response has been related to increased communication between conflict processing fronto-parietal and early somatosensory regions. If alpha oscillations improve communication efficiency across the cortex it was predicted that inducing stronger alpha oscillations would affect the performance, (i.e. the Stroop cost would diminish). That hypothesis was tested in a series of three experiments. None of the manipulations (different frequencies, amplitudes induced and alpha phases where the Stroop task was initiated) showed that alpha oscillatory activity reduces the Stroop effect. However, the last task showed that people were faster when the task was preceded by an alpha frequency flicker prime, especially around 10Hz. The fourth experiment built on the well-established phenomena that when alpha activity is elicited in a particular hemisphere it attenuates processing of sensory information in that hemisphere, while the opposite hemisphere, is characterised by increased efficiency of information processing/flow. The study tested whether that could occur within a hemisphere by localised entrainment of part of the visual field. This hypothesis was tested by examining whether it could resolve differences in results previously published by Mathewson et al., (2012) and Spaak et al., (2014). In this study, a target circle was presented at time points after the offset of an alpha flicker prime, such that it was either in or out of phase with the prime. The target was displayed briefly, and then a masking ring appeared around the target location. There were two experimental conditions. First priming occurred at the central target location, and this was expected to inhibit perception at that location, (i.e. the target would be best detected at out of alpha phase time points). In contrast, in the second condition, the target surround area (e.g. the mask location) was stimulated, and this was expected to inhibit perception at that location, (i.e. the mask would be most effective in phase time points and so the target more easily detected). However, in both instances, target detection was best at in-phase time points and attenuated at out of phase time points, in line with Mathewson et al., (2012) results. This gives us some insight into the role of the alpha phase in allowing the external stimuli to be perceived/detected. The fifth experiment tested whether the level of spatial uncertainty of briefly presented target determines the alpha phase position for its best detection. This task used a similar masked circle paradigm as the fourth experiment, but the target could appear at one of two locations either side of fixation, which were both preceded by a flicker prime (either alpha frequency or randomly jittered) and followed by masking rings. The hypothesis was that the optimal alpha phase for target detection depends on whether people are pre-guided (by an arrow cue) to the target location or uncued (a higher level of spatial uncertainty). This hypothesis was again tested by examining whether it could resolve differences in results previously published by Mathewson et al., (2012) and Spaak et al., (2014). This experiment showed that the level of spatial uncertainty of briefly presented target determines the optimal alpha phase for its detection. Targets whose location was not pre-guided were the most likely to be detected when presented at time points out of phase with the entrained alpha prime; targets whose location was pre-guided by a brief arrow were the most likely to be detected when presented at time points in phase with the entrained alpha prime. The sixth experiment used EEG to investigate the neural dynamics underlying the behaviourally tested phenomenon in the previous experiment. Results showed that for targets with a high level of spatial uncertainty, the average alpha power peak was detected earlier in anterior electrodes compared with posterior electrodes, which is consistent with a greater reliance on alpha top-down dynamics. In contrast, for targets at a spatially cued location, the average alpha power peak was detected earlier at posterior electrodes, which suggests a greater reliance on bottom-up alpha neuronal dynamics. In summary, this thesis confirmed that mid-alpha phase determines the probability of detection of a briefly presented target. Also, it showed that optimal alpha phase for detecting briefly presented target would differ depending on the level of spatial uncertainty of that target. Targets at non-predictable locations are more likely to be detected at a trough in the phase of alpha activity whilst those at cued locations are most likely to be detected in-phase. Hence, perception depends not only on the internal neuronal alpha dynamics but also on the type of the visual percept. This difference may highlight the role of two different neuronal alpha sources which dominate in the different scenarios. When the target location is uncertain, top-down alpha dynamics dominate. However, when the target location is pre-guided, bottom-up alpha dynamics dominate

Human Duration Perception Mechanisms in the Subsecond Range: Psychophysics and Electroencephalography Investigations

In a world full of fleeting events, how do humans perceive time intervals as short as half a second? Unlike primary senses, there are no time receptors. Is sub-second time perception reconstructed from memory traces in the primary senses, or based on the output of a modality-independent internal clock? In analogy to bugs in computer programs or mutations in genetics studies, I studied two types of subjective time warp illusions in order to understand how time perception normally works. One illusion that I examined is called oddball chronostasis, which is a duration distortion effect that happens to an unusual item. The other illusion is called debut chronostasis, which is a time warp effect that occurs to the first item among other identical ones. Regarding oddball chronostasis, we solved a theoretical dispute over its underlying mechanisms and dissociated three causes. The necessary component is top-down attention to the target item. The other two components are contingent factors. This suggests that a pure sensory modality-dependent view of time perception mechanisms is less likely. Regarding debut chronostasis, we discovered auditory debut chronostasis and found that its illusion strength is about the same as the visual case. At first glance, this seems to suggest that time perception is independent of the primary sensory modalities. However, when visual and auditory events were compared against each other (inter-modal comparison), debut chronostasis disappeared. Therefore, modality-dependent mechanisms of time perception do exist. Further, we found a special factor that could counteract debut chronostasis and thus re-interpreted the main cause of debut chronostasis as internal duration template uncertainty. By examining both intra- and inter-modal comparisons, this uncertainty effect turned out to be a modality-independent effect. Therefore, modality-independent mechanisms of time perception also exist. In conclusion, this dissertation work contributed to novel theoretical understanding of two types of time perception illusions. Unlike many simplified theories in the literature either holding a modality-dependent or independent view, our findings altogether indicate that time perception involves both intra- and supra-modal stages. Future experimental work could thus target on separating intra- and supra-modal time perception mechanisms.</p

The role of occipital pre-stimulus alpha oscillations in selective attention

In everyday life relevant and distracting information often coincide and we rely on selective attention to efficiently discriminate between the pertinent information and the irrelevant noise. Existing research relates selective attention to neural oscillations in alpha frequency predominantly using spatial paradigms with one or no distractors, presented simultaneously with the target. In the current thesis the role of pre-stimulus alpha oscillations was investigated in the context of a visual search. First, the effect of visual stimulation on alpha oscillations and behavioural performance was investigated. No effects of stimulation were found and alpha oscillations were not successfully entrained. The relationship of spontaneous pre-stimulus alpha oscillations with performance was then explored. We demonstrated a negative correlation between the power of alpha oscillations and performance, indicating that high power is related to fast reaction times. Lastly, the effect of pre-stimulus alpha oscillations in the context of varying task demands was investigated. The results indicated that high alpha power is beneficial for performance when the target is presented simultaneously with multiple distractors, but not when presented with a singleton distractor. Moreover, the predictability of task demands resulted in modulation of pre-stimulus alpha oscillations, with higher power in anticipation of high task demands, as compared to low task demands

Investigating human visual processing using MEG and psychophysics

Our visual system organises sensory inputs into coherent object percepts. Knowledge and expectations about objects facilitate perceptual organisation via top-down processing. My PhD set out to investigate the neural mechanisms underpinning this process via frequency-tagging. Frequency-tagging studies embed flickers of different frequencies in a stimulus to drive narrow-band neural responses, which provide indices of spatial integration across the stimulus. My pilot experiments failed to robustly evoke this neural signature of perceptual organisation. Consequently, I conducted the following two lines of research. In a series of MEG studies, I systematically investigated the power of flicker-evoked neural responses as a function of stimulation frequency (Chapter 2). The resulting temporal response tuning profile showed substantial individual variability, which I assessed in relation to two other intrinsic properties of the individual’s visual system (Chapter 3). Spectral features of the temporal tuning profile were found to be associated with an individual’s perceptual temporal resolution but not with the peak frequency of visually-induced gamma oscillations. Moreover, the temporal resolution was found to be unrelated to visual gamma oscillations and the computationally modelled synaptic properties underlying visual gamma (Chapter 4). These MEG studies provide insights into dynamical properties of the visual system and form the methodological basis for future frequency-tagging studies. Besides the MEG research, I conducted a psychophysical study to investigate the top-down modulation of the perception of low-level features in an organised percept (Chapter 5). I found that whether the perceptual sensitivity to a low-level feature is enhanced by top-down processing depends on whether this feature contributes to the object percept. Future studies can investigate this effect further via frequency-tagging, by implementing flickers in the stimuli of the psychophysical task and choosing tagging frequencies informed by my MEG studies, to advance our understanding of the neural mechanisms underlying top-down processing in perceptual organisation

Towards a home-use BCI: fast asynchronous control and robust non-control state detection

Eine Hirn-Computer Schnittstelle (engl. Brain-Computer Interface, BCI) erlaubt einem Nutzer einen Computer nur mittels Gehirn-Aktivität zu steuern. Der Hauptanwendungszweck ist die Wiederherstellung verschiedener Funktionen von motorisch eingeschränkten Menschen, zum Beispiel, die Wiederherstellung der Kommunikationsfähigkeit. Bisherige BCIs die auf visuell evozierten Potentialen (VEPs) basieren, erlauben bereits hohe Kommunikationsgeschwindigkeiten. VEPs sind Reaktionen, die im Gehirn durch visuelle Stimulation hervorgerufen werden. Allerdings werden bisherige BCIs hauptsächlich in der Forschung verwendet und sind nicht für reale Anwendungszwecke geeignet. Grund dafür ist, dass sie auf dem synchronen Steuerungsprinzip beruhen, dies bedeutet, dass Aktionen nur in vorgegebenen Zeitslots ausgeführt werden können. Dies bedeutet wiederum, dass der Nutzer keine Aktionen nach seinem Belieben ausführen kann, was für reale Anwendungszwecke ein Problem darstellt. Um dieses Problem zu lösen, müssen BCIs die Intention des Nutzers, das System zu steuern oder nicht, erkennen. Solche BCIs werden asynchron oder selbstbestimmt genannt. Bisherige asynchrone BCIs zeigen allerdings keine ausreichende Genauigkeit bei der Erkennung der Intention und haben zudem eine deutlich reduzierte Kommunikationsgeschwindigkeit im Vergleich zu synchronen BCIs. In dieser Doktorarbeit wird das erste asynchrone BCI vorgestellt, welches sowohl eine annäherungsweise perfekte Erkennung der Intention des Nutzers als auch eine ähnliche Kommunikationsgeschwindigkeit wie synchrone BCIs erzielt. Dies wurde durch die Entwicklung eines allgemeinen Modells für die Vorhersage von sensorischen Reizen erzielt. Dadurch können beliebige visuelle Stimulationsmuster basierend auf den gemessenen VEPs vorhergesagt werden. Das Modell wurde sowohl mit einem "traditionellen" maschinellen Lernverfahren als auch mit einer deep-learning Methode implementiert und evaluiert. Das resultierende asynchrone BCI übertrifft bisherige Methoden in mehreren Disziplinen um ein Vielfaches und ist ein wesentlicher Schritt, um BCI-Anwendungen aus dem Labor in die Praxis zu bringen. Durch weitere Optimierungen, die in dieser Arbeit diskutiert werden, könnte es sich zum allerersten geeigneten BCI für Endanwender entwickeln, da es effektiv (hohe Genauigkeit), effizient (schnelle Klassifizierungen), und einfach zu bedienen ist. Ein weiteres Alleinstellungsmerkmal ist, dass das entwickelte BCI für beliebige Szenarien verwendet werden kann, da es annähernd unendlich viele gleichzeitige Aktionsfelder erlaubt.Brain-Computer Interfaces (BCIs) enable users to control a computer by using pure brain activity. Their main purpose is to restore several functionalities of motor disabled people, for example, to restore the communication ability. Recent BCIs based on visual evoked potentials (VEPs), which are brain responses to visual stimuli, have shown to achieve high-speed communication. However, BCIs have not really found their way out of the lab yet. This is mainly because all recent high-speed BCIs are based on synchronous control, which means commands can only be executed in time slots controlled by the BCI. Therefore, the user is not able to select a command at his own convenience, which poses a problem in real-world applications. Furthermore, all those BCIs are based on stimulation paradigms which restrict the number of possible commands. To be suitable for real-world applications, a BCI should be asynchronous, or also called self-paced, and must be able to identify the user’s intent to control the system or not. Although there some asynchronous BCI approaches, none of them achieved suitable real-world performances. In this thesis, the first asynchronous high-speed BCI is proposed, which allows using a virtually unlimited number of commands. Furthermore, it achieved a nearly perfect distinction between intentional control (IC) and non-control (NC), which means commands are only executed if the user intends to. This was achieved by a completely different approach, compared to recent methods. Instead of using a classifier trained on specific stimulation patterns, the presented approach is based on a general model that predicts arbitrary stimulation patterns. The approach was evaluated with a "traditional" as well as a deep machine learning method. The resultant asynchronous BCI outperforms recent methods by a multi-fold in multiple disciplines and is an essential step for moving BCI applications out of the lab and into real life. With further optimization, discussed in this thesis, it could evolve to the very first end-user suitable BCI, as it is effective (high accuracy), efficient (fast classifications), ease of use, and allows to perform as many different tasks as desired