Title Promoter Affiliations Abstract "Repetitive Transcranial Magnetic Stimulation over the dorsolateral prefrontal cortex combined with tomographic neurofeedback of the subgenual anterior cingulate cortex as a tailored antidepressant intervention with enduring effects." "Marie-Anne Vanderhasselt" "Department of Head and Skin, Department of Psychiatry and Medical Psychology" "I aim to develop an antidepressant intervention based on the modulation of the prefrontal/limbic network via two angles:(1) a cortical entry point (via neuro-cardiac guided neurostimulation)(2) a subcortical entry point (via neurofeedback).I hypothesize that the combined treatment will translate in synergistic effects on clinical outcome with enduring effects." "Real-time analysis of high-density EEG signals for neurofeedback applications" "Dante Mantini" "Movement Control & Neuroplasticity Research Group, Brain and Cognition" "The brain is the most complex organ of our body, and a large bulk of research is conducted to understand its basic mechanisms and its impairments associated with neurological deficits. Notably, there are a variety of empirical methods that allow scientists to examine brain functioning. In particular, it is necessary to rely on non-invasive techniques to study brain activity in healthy people and patients. An emerging technique for brain imaging is the high-density electroencephalography (hdEEG), which records the changes in electrical potential on the scalp. These variations are directly related to neuronal activity in the gray matter. HdEEG systems have more than 100 electrodes placed over the scalp. HdEEG data, if combined with precise information of the head anatomy and sophisticated source localization algorithms, permit the reconstruction of neural activity in the brain. However, several processing steps are needed to move from EEG recordings to 3-dimensional images of neuronal activity. Nowadays, hdEEG analyses have been conducted in an offline manner. Important technical issues need to be addressed for real-time hdEEG analyses.The purpose of this PhD thesis is to develop a complete analysis workflow for low complexity real-time analysis of source-level hdEEG data. To ensure reliable real-time source activity reconstruction using EEG, we aim to design computationally-efficient artifact removal techniques and source localization. A further goal is to develop a software package with a graphic user interface, which simplifies online analysis procedures.The results of the PhD thesis work suggest that it is possible to use hdEEG as a non-invasive technique for real-time estimation of neuronal activity. We believe that the tools we developed for real-time hdEEG data analysis can find several new applications, such as source-based neurofeedback and closed-loop neuromodulation, holding great potential for the enhancement of brain plasticity and the treatment of neurological diseases." "Repetitive transcranial magnetic stimulation of the dorsolateral prefrontal cortex combined with neurofeedback of the subgenual anterior cingulate cortex as a patient-specific intervention with lasting effects" "Marie-Anne Vanderhasselt" "Department of Head and Skin" "The goal of the project is to identify brain regions and brain networks related to the psychosocial stress response through means of electroencephalography, a neuroimaging technique. The project evaluates the effects of commonly employed paradigms, uses modern analysis techniques to uncover the spatiotemporal effect of psychosocial stress, and researches the neural effects of various psychosocial stress dimensions. This research is a first step towards specialized non-invasive neurostimulation techniques for stress-related mental disorders." "Listen very carefully! Online tracking of auditory attention via electroencephalography (EEG) in individuals and groups of learners" "Alexander Bertrand" "Dynamical Systems, Signal Processing and Data Analytics (STADIUS), Parenting and Special Education" "Attention plays a vital role in understanding how students learn and get distracted in classroom situations. Educational scientists study attention via post-hoc assessments (self-reports or cognitive tests), yet these are inaccurate and do not capture fluctuations in attention over time. On the other hand, biomedical engineers have recently made progress in objectively tracking attention to auditory stimuli via brain recordings such as electroencephalography (EEG), but these methods are not yet adapted to the complexity of the classroom context. We propose a strong interdisciplinary collaboration between biomedical engineers and educational neuroscientists, to develop novel EEG-based markers of auditory attention during learning. This will lead to new data-driven EEG-based algorithmic tools that quantify attention over time, both in groups and individuals. These tools will be used to identify student profiles and to investigate the effects of (neurofeedback) interventions." "Online measurement of auditory attention via electroencephalography (EEG) in individuals and groups of learners" "Bert De Smedt" "Dynamical Systems, Signal Processing and Data Analytics (STADIUS), Parenting and Special Education" "Attention plays a crucial role in our understanding of how students learn and are distracted in the classroom. However, there is little to no research on the auditory component of attention, yet it could help us to improve our understanding of (individual differences in) the learning process. Educational scientists study attention through post-hoc measurements, but these are inaccurate and do not account for fluctuations of attention over time. Biomedical engineers, on the other hand, have made progress in recent years in objectively measuring auditory attention via brain measurements such as electroencephalography (EEG), but these methods are not yet adapted to the complexity of the classroom context. Through a strong interdisciplinary collaboration between biomedical engineers and educational scientists, we aim to develop new EEG-based markers of auditory attention during learning. On the one hand, this should lead to new data-driven EEG-based algorithms that quantify attention over time in groups and individuals. On the other hand, these algorithms will be used to determine profiles of students and investigate effects of (neurofeedback) interventions." "Closing the loop: towards contemporary assessment and modulation of visual attention" "Céline Gillebert" "Brain and Cognition, Movement Control & Neuroplasticity Research Group" "Stroke-induced attention deficits have a large impact on activities of daily living as well as on the recovery from post-stroke disorders in the motor domain and other cognitive domains. An overarching approach that involves 1) a reliable, inclusive, and accessible assessment of attention, 2) a deep understanding of its neural mechanisms, and 3) a therapeutic intervention tailored to the individual is pivotal for the advancement of neuropsychological rehabilitation of attention deficits. The central aim of my doctoral research project is to examine and develop novel methods to assess and modulate visual attention. First, conventional cognitive neuropsychological assessment of visual attention has remained relatively stagnant in the past decades and tend to be lacking in reliability and sensitivity to characterise subtle deficits in visual attention. We integrated new technological developments and findings from experimental psychology to develop accessible and inclusive computerised assessments that deliver sensitive measures of visual attention (Chapters 2 and 3). Second, the intraparietal sulcus (IPS) plays a critical role in the control of attention at specific locations in the visual field, and typically shows a disrupted functionality in stroke patients with attention deficits. To further examine its properties, we related the IPS activity of neurologically healthy individuals to the allocation of attention to locations in the visual field with varying levels of eccentricity (Chapter 4). Third, we examined a novel technique named real-time functional magnetic resonance imaging (fMRI) neurofeedback, a non-invasive method that can train participants to gain control over their own brain activity. We first performed a systematic review of the literature, which showed that real-time fMRI neurofeedback allows for individualized training to improve task performance and stroke recovery (Chapter 5). Next, we constructed a real-time fMRI neurofeedback pipeline aimed at modulating visual attention, and used it to train participants to self-modulate their brain activity in the left and right IPS (Chapter 6). In sum, this dissertation presents the design of an accessible assessment of visual attention, an investigation of the neural mechanisms behind the allocation of attention, and the construction of a real-time fMRI neurofeedback-based training procedure built on these concepts to modulate visual attention. These new insights may offer important implications for how we approach rehabilitation of cognitive disorders following stroke in a holistic way encompassing the three pillars of rehabilitation: assessment, neural mechanisms, and therapeutic interventions." "Modeling and manipulation of attention control networks during early visual processing" "Gilles Pourtois" "Department of Data-analysis, Department of Experimental clinical and health psychology" "Attention control is an important ability, which is achieved by two processes: target selection and distractor suppression. The goal of this project is to shed light on them using behavioral and electro-encephalographic (EEG) methods. To this end, we propose to set up a valid computational model. After this first step, we will devise a series of experiments that will allow us to put to the test the main predictions deriving from this model regarding target selection and distractor suppression. Last, using this validated model, we will use neurofeedback to alter attention control. As such, this project will provide new insights into brain networks that give rise to target selection and distractor suppression. Moreover, it is anticipated that it will have a main impact for current theoretical models of attention in the psychology literature, but also in more applied settings where the training of attention control is sought." "EEG alpha-theta (cross-frequency) dynamics during arithmetic performance, mind wandering and meditative states" "Kaat Alaerts" "Research Group for Neurorehabilitation (eNRGy), Movement Control & Neuroplasticity Research Group" "Neural oscillations have been shown to be functionally relevant for human behaviour. In this way, brain rhythms oscillating at different frequencies have been associated to different cognitive functions. Consequently, the interplay between brain rhythms in different frequency ranges (i.e. cross-frequency coupling) is thought to be essential for cognition to emerge. This thesis focuses on cross-frequency dynamics between EEG alpha (8-14 Hz) and theta (4-8 Hz) rhythms during different cognitive states. Specifically, it investigates the functional relevance of alpha:theta cross-frequency numerical ratios during arithmetic performance, mind wandering and meditative states. This approach to alpha-theta cross-frequency dynamics is based on a recent theory positing that the formation of different cross-frequency numerical ratios between the peak frequencies of two brain rhythms is reflective of their level of interaction. In this way, it is proposed that harmonic cross-frequency arrangements (e.g. 2:1 numerical ratio) would enable cross-frequency coupling. The rationale behind this premise is that only harmonic cross-frequency ratios allow stable and regular excitatory phase meetings between two neural populations (i.e. coincidence of time periods in which spiking is more likely to occur).The working hypothesis in this thesis was that alpha and theta rhythms would arrange more often in harmonic positions during both working memory tasks and mind wandering. This hypothesis was based on previous literature suggesting that alpha (8-14Hz) and theta (4-8 Hz) rhythms reflect different components of working memory that need to be integrated when information has to be stored and manipulated in the brain. This hypothesis was assessed throughout the four studies encompassing this thesis. In the first study (Chapter 2), we assess the incidence of different alpha:theta cross-frequency ratios during an arithmetic task with a strong working memory component, rest and meditation practice. It was shown that alpha and theta rhythms separated in the frequency domain during arithmetic performance (relative to rest and meditation) thereby increasing the incidence of cross-frequency numerical ratios between 2 and 3 (and therefore 2:1 and 3:1 phase synchrony). These changes were accompanied by a decreased occurrence of ratios between 1 and 1.6. Interestingly, the separation between alpha and theta rhythms in the frequency domain (i.e. increased occurrence of ratios around 2 and 3 and decreased occurrence of ratios between 1 and 1.6) were positively associated to arithmetic performance, thereby underlining their functional relevance.  A similar pattern of results was observed in the second study (Chapter 3), in which the same paradigm was adopted but with participants that were highly experienced in meditation practice. In addition to the previously reported changes during arithmetic task (relative to rest and meditation practice), we report that meditation was associated to a decreased incidence of alpha:theta ratios between 2 and 3 and an increased incidence of alpha:theta ratios between 1 and 1.6 when compared to rest and arithmetic. Based on these latter results, it was speculated that these changes in alpha-theta cross-frequency dynamics could be attributed to reduced mind wandering during meditation. To further investigate the influence of meditation training in alpha:theta cross-frequency dynamics, we assessed in a third study (Chapter 4) whether the compliance to a meditation training course was significantly correlated to changes in the incidence of different alpha:theta cross-frequency ratios during meditation. In this way, we show that meditation training (i.e. minutes of attendance plus minutes of practice at home) was associated to an approximation of alpha and theta rhythms in the frequency domain (i.e. a decreased occurrence of alpha:theta cross-frequency ratios around 3 and an increased occurrence of cross-frequency ratios around 1.6). In line with the previous study, we speculated that these inter-individual differences in the incidence of different alpha:theta numerical ratios during mediation were associated to mind wandering. Finally, in the fourth study (Chapter 5) we directly assess whether the occurrence of different alpha:theta cross-frequency ratios were associated to mind wandering in the context of meditation practice. For this purpose, a sample of novice meditators were repeatedly interrupted during a breath focus meditation to report whether they were mind wandering or focusing on their breath. In line with previous findings, our results showed that mind wandering is associated to a separation of alpha and theta rhythms in the frequency domain (i.e. an increased incidence of alpha:theta ratios between 2 and 3 at the expense of the occurrence of alpha:theta ratios between 1 and 1.6).Together, our results consistently show a separation of alpha and theta rhythms in the frequency domain (higher mean alpha:theta numerical ratio) during both arithmetic performance (relative to rest) and mind wandering (in the context of meditation practice). Although these changes in alpha:theta cross-frequency ratios led to greater 2:1 and 3:1 harmonicity and phase synchrony between alpha and theta rhythms, the observed changes in the frequency architecture (as indexed by the incidence of different cross-frequency ratios) do not unequivocally reflect changes in the level of interaction between alpha (8-14Hz) and theta (4-8 Hz) rhythms.  Therefore, we cannot conclude that here studied cognitive states involve different levels of communication between the neural populations that are entrained by neural oscillations in the alpha and theta range. In this way, changes in the incidence of different ratios cross-frequency ratios would remain descriptive and open to interpretation until future studies empirically disentangle whether: i) alpha and theta rhythms encompass two separate neural oscillations with exclusively sinusoidal properties and ii) different cross-frequency ratios reflect different levels of information exchange between neural rhythms. Regardless the interpretation we give to the incidence of different alpha:theta ratios, the here presented studies suggest the existence of a neurocognitive mechanism that supports both working memory task performance and mind wandering.  " "Mobile EEG and Tensor Approaches for Auditory Attention Analysis in Real-life" "Sabine Van Huffel" "ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics" "In recent years there has been considerable interest in recording neurophysiological information from humans in natural environments. With the emergence of high quality mobile EEG equipment, new EEG applications may be within reach. However, to date, the number of studies using true mobile EEG recordings in natural scenarios is surprisingly limited, which questions the feasibility of recording reliable EEG in out-of-the-lab scenarios. Moreover, the cognitive functioning of humans in real-life scenarios is likely to deviate from artificially created lab environments. With the advent of real-life mobile EEG applications and real-time signal processing, current methods need to be re-evaluated, and new aspects of the EEG acquisition should be addressed. The effects of distractions, changes in cognitive load, physical engagement and subject behavioral variability in real-life scenarios are hypothesized to influence neurophysiological brain responses as described in traditional confined EEG experiments.This thesis seeks to address the feasibility of applying mobile EEG for research grade auditory attention experiments in real-life scenarios. Auditory attention is widely recognized as a very important concept that plays a vital role in the way humans process auditory information. It is inherently related to the user's current environment, making it a very relevant subject of study with mobile EEG outside a lab environment. We evaluated several aspects of EEG recording, analysis and interpretation that are of major importance for the application of mobile EEG. Specifically, we evaluate the response to acoustic stimuli in three-class auditory oddball and auditory attention detection (AAD) in natural speech paradigms. The former relies on event-related potentials (ERP) in the EEG in response to artificial stimuli, i.e. P300, which is one of the most studied potentials in EEG, predominantly for brain-computer-interfaces (BCI). In contrast, AAD is based on tracking cortical EEG responses, in relation to attended natural speech, which holds potential for application in assistive devices such as hearing aids. The usage of regular speech stimuli strengthens the natural character of our experimentation. The first part of this thesis focuses on the signal analysis in three-class auditory oddball paradigms. We introduce the concepts of canonical polyadic decompositions (CPD), and decompositions in multi linear (Lr,Lr,1) terms (LL1) of higher-order EEG data. We demonstrate their effectiveness in decomposing EEG datasets in a data-driven way, to obtain relevant components related to the P300. Additionally, we show that it is possible to eliminate the explicit subject-dependent calibration phase with a tensor-based decomposition (CPD/LL1) augmented with non-subject-specific templates, without sacrificing classification accuracy. This allows for instantaneous classification results that, on average, are similar to those of the subject-specific trained models. These tensor approaches lend themselves for use as data-driven classification methods of EEG that could conceivably lead to faster usage of BCI systems and provide meaningful information of the subject's performance from the mobile EEG in a more natural way.Besides classification, we gained considerable insight with regard to the factors in real-life recordings that influence the neurophysiological responses such as the P300. We evaluate the ERP and single-trial characteristics of a three-class auditory oddball paradigm recorded in outdoor scenarios while pedaling on a fixed bike or cycling around freely. In addition, we also carefully evaluate the trial-specific motion artifacts through independent gyroscope measurements and control for muscle artifacts. This work was the first to successfully examine such aspects simultaneously in one study. Our findings suggest that cognitive paradigms measured in natural real-life scenarios are influenced significantly by increased cognitive load due to being in an unconstrained environment. Furthermore, our study paved the way for other free cycling studies; very recently our results were replicated by others. All in all, these results have strengthened our conviction that the lack of subject response is often the bottleneck in active BCIs and the attentional efforts of the subject need to be carefully evaluated. In the last part we address the conscious attentional efforts in more realistic scenarios. To this end we evaluate mobile EEG recordings at-home for learning in an auditory context. We describe a closed-loop online analysis of AAD applied to natural speech in a cocktail party scenario. In addition, the effects of personalized training via neurofeedback are investigated. We conducted two experiments that took place in an office and home environment. The results prove the feasibility of AAD outside the lab, which is promising for future applications such as in auditory assistive devices. Moreover, the high variability between subjects in physiological responses as recorded with the EEG, highlight the importance of considering EEG training to increase the efficiency of the AAD. Preliminary evidence regarding changes in AAD performance during training was obtained and future studies are needed to examine these effects in more detail. Finally, this work suggests that multiple modalities, e.g. behavioral, physical and neurophysiological, need to be considered when evaluating users' cognitive performance exhaustively in real-life situations. To conclude, even though our investigations have only touched upon a limited section of the wide variety of neurophysiological processes, our results demonstrate the feasibility of truly mobile EEG applications. The prospect of being able to achieve (online) application of the auditory oddball and AAD in out-of-the-lab experiments, serves as a continuous incentive for future research. Furthermore, our results encourage future mobile EEG studies to consider a holistic approach in order to extend, in the best possible way, the current lab-based knowledge of cognitive brain monitoring to real-life scenarios."