Time-varying functional connectivity and dynamic neurofeedback with MEG: methods and applications to visual perception

Cognitive function involves the interplay of functionally-separate regions of the human brain. Of critical importance to neuroscience research is to accurately measure the activity and communication between these regions. The MEG imaging modality is well-suited to capturing functional cortical communication due to its high temporal resolution, on the millisecond scale. However, localizing the sources of cortical activity from the sensor measurements is an ill-posed problem, where different solutions trade-off between spatial accuracy, correcting for linear mixing of cortical signals, and computation time. Linear mixing, in particular, affects the reliability of many connectivity measures. We present a MATLAB-based pipeline that we developed to correct for linear mixing and compute time-varying connectivity (phase synchrony, Granger Causality) between cortically-defined regions interfacing with established toolboxes for MEG data processing (Minimum Norm Estimation Toolbox, Brainstorm, Fieldtrip). In Chapter 1, we present a new method for localizing cortical activation while controlling cross-talk on the cortex. In Chapter 2, we apply a nonparametric statistical test for measuring phase locking in the presence of cross-talk. Chapters 3 and 4 describe the application of the pipeline to MEG data collected from subjects performing a visual object motion detection task. Chapter 5 focuses on real-time MEG (rt-MEG) neurofeedback which is the real-time measurement of brain activity and its self-regulation through feedback. Typically neurofeedback modulates directly brain activation for the purpose of training sensory, motor, emotional or cognitive functions. Direct measures, however, are not suited to training dynamic measures of brain activity, such as the speed of switching between tasks, for example. We developed a novel rt-MEG neurofeedback method called state-based neurofeedback, where brain activity states related to subject behavior are decoded in real-time from the MEG sensor measurements. The timing related to maintaining or transitioning between decoded states is then presented as feedback to the subject. In a group of healthy subjects we applied the state-based neurofeedback method for training the time required for switching spatial attention from one side of the visual field to the other (e.g. left side to right side) following a brief presentation of a visual cue. In Chapter 6, we used our pipeline to investigate training-related changes in cortical activation and network connectivity in each subject. Our results suggested that the rt-MEG neurofeedback training resulted in strengthened beta-band connectivity prior to the switch of spatial attention, and strengthened gamma-band connectivity during the switch. There were two goals of this dissertation: First was the development of the MATLAB-based pipeline for computing time-evolving functional connectivity analysis in MEG and its application to visual motion perception. The second goal was the development of a real-time MEG neurofeedback method to train the dynamics of brain states and its application to a group of healthy subjects.2019-11-02T00:00:00

The neural architecture of semantic retrieval with and without cues: evidence from neuropsychology and neuroimaging

Everyday situations are conceptually rich, but not all of this knowledge is relevant at a given time. At the heart of adaptive cognition is flexibility, which allows us to focus on particular mental representations in a way that suits the changing context and goals. Previous work has highlighted the importance of semantic control mechanisms in retrieval, which allow cognition to diverge from dominant associations (Lambon Ralph et al., 2016). However, a clear understanding of the cognitive and neural substrates of semantic flexibility is currently lacking. This work collects evidence from different methods and experimental populations to tackle this broad question. We use novel multimodal semantic cues (i.e. affect and spatial locations) to examine the mechanisms that support flexible patterns of retrieval when the context is helpful or unhelpful. The first two empirical chapters examine behavioural effects of cues and miscues in patients with semantic aphasia (Chapter 2) and investigate whether patients with SA show greater benefits of coherent cue combinations compared to minimal levels of cueing (Chapter 3). The third chapter explores the neural bases of cued semantic retrieval, and tests the predictions of another recent framework which situates the default mode network at the top of a cortical hierarchy of abstraction (Margulies et al., 2016). The final chapter investigates whether the intrinsic connectivity of the brain at rest is predictive of the behavioural efficiency in cued semantic retrieval. Our findings provide evidence for the existence of two qualitatively distinct mechanisms for semantic flexibility, one driven by control processes (impaired in SA) and one driven by the integration of contextual information with long-term semantic knowledge (relatively intact in SA). In line with a growing body of work suggesting a role of default mode network in information integration, we show that more coherent patterns of retrieval which are driven by the context recruit this network. In contrast, multiple-demand regions appear to support more executive aspects of cued retrieval required for the maintenance of cue information. Finally, this thesis provide evidence that affect and location cues are both effective at shaping the activation of semantic knowledge. In summary, this thesis suggests that semantic flexibility is a complex and multi-faceted process which requires an interplay of different cognitive and neural components

To which extent can attention and/or modulation explains deficits in dyslexia?

This thesis investigates the visual deficits associated with developmental dyslexia, particularly that of visual attention. Visual attention has previously been investigated in a wide array of behavioural and psychophysical (amongst others) studies but not many have produced consistent findings. Attention processes are believed to play an integral part in depicting the overall "extent" of reading deficits in dyslexia, so it was of paramount importance to aim at such attention mechanisms in this research. The experiments in this thesis focused on signal enhancement and noise (distractor) exclusion. Given the flexibility of the visual search paradigms employed in this research, factors such as visual crowding and attention distribution was also investigated. The experiments systematically manipulated noise (by increasing distractor count, i.e. set-size), crowding (varying the spacing between distractors), attention allocation (use of peripheral cues to direct attention), and attention distribution (influence of one visual field over the other), all of which were tied to a critical factor, the "location/spatial/decisional uncertainty". Adults with dyslexia were: (i) able to modulate attention appropriately using peripheral pre-cues, (ii) severely affected by crowding, and (iii) unable to counteract increased set-sizes when post or un-cued, the latter signifying poor distractor (noise) suppression. By controlling for location uncertainty, the findings confirmed that adults with dyslexia were yet again affected by crowding and set-size, in addition to an asymmetric attention distribution. Confounding effects of ADHD symptoms did not explain a significant independent variance in performance, suggesting that the difficulty shown by adult dyslexics were not accounted for by co-morbid ADHD. Furthermore, the effects of crowding, set-size and asymmetric attention correlated significantly with literacy, but not ADHD measures. It is believed that a more diffuse and an asymmetric attention system (in dyslexia) to be the limiting factor concerning noise exclusion and attention distribution. The findings from this thesis add to the current understanding of the potential role of deficits in visual attention in dyslexia and in the literacy difficulties experienced by this population

MECHANISMS OF MEMORY CONSOLIDATION

Extensive research has shown that sleep supports memory. Newer work suggests that wakefulness can also benefit retention of new information. However, the exact mechanisms which govern memory consolidation in sleep and wake are largely unknown. The implementation of new technologies, which draw on these natural memory processes, allows some insight into their characteristics. This work aims at elucidating some aspects of memory consolidation processes in the realm of sleep and wake. Firstly, we train novel non-words, a material previously indicated to benefit from sleep-associated consolidation, with explicit and implicit methods to determine whether the implicit learning (via the Hebb repetition task) would facilitate lexical integration independently of sleep. The results reveal that lexical integration of novel words is contingent on a good level of explicit training, followed by a consolidation delay with sleep. We speculate that sleep-associated consolidation may be mediated by the degree of overlap between new and already known material. To further capitalise on these findings, we test whether applying non-verbal cues during sleep can improve learning of novel words and their integration within the lexicon using Targeted Memory Reactivation (TMR) paradigm. Our results indicate that reactivating novel lexical representations in sleep improves their consolidation and facilitates their recall. However, the lack of lexical integration observed suggests the need for future research. Finally, based on recent evidence that quiet wakeful rest can result in comparable memory increases to sleep, we explore the consolidation during awake state using transcranial direct current stimulation (tDCS). We found that applying tDCS to the right occipital-parietal site enhances memory for a list of words as compared to no stimulation. The findings imply that memory consolidation during quiet wakefulness can be manipulated externally, which may direct future research. Nevertheless, the exact neuro-correlates of memory consolidation in quiet wake are yet to be fully investigated

Electrophysiological Signatures of Fear Conditioning: From Methodological Considerations to Catecholaminergic Mechanisms and Translational Perspectives

Fear conditioning describes a learning mechanism during which a specific stimulus gets associated with an aversive event (i.e., an unconditioned stimulus; US). Thereby, this initially neutral or arbitrary stimulus becomes a so-called “conditioned” stimulus (CS), which elicits a conditioned threat response. Fear extinction refers to the decrease in conditioned threat responses as soon as the CS is repeatedly presented in the absence of the US. While fear conditioning is an important learning model for understanding the etiology and maintenance of anxiety and fear-related disorders, extinction learning is considered to reflect the most important learning process of exposure therapy. Neurophysiological signatures of fear conditioning have been widely studied in rodents, leading to the development of groundbreaking neurobiological models, including brain regions such as the amygdala, insula, and prefrontal areas. These models aim to explain neural mechanisms of threat processing, with the ultimate goal to improve treatment strategies for pathological fear. Recording intracranial electrical activity of single units in animals offers the opportunity to uncover neural processes involved in threat processing with excellent spatial and temporal resolution. A large body of functional magnetic resonance imaging (fMRI) studies have helped to translate this knowledge about the anatomy of fear conditioning into the human realm. fMRI is an imaging technique with a high spatial resolution that is well suited to study slower brain processes. However, the temporal resolution of fMRI is relatively poor. By contrast, electroencephalography (EEG) is a neuroscientific method to capture fast and transient cortical processes. While EEG offers promising opportunities to unravel the speed of neural threat processing, it also provides the possibility to study oscillatory brain activity (e.g., prefrontal theta oscillations). The present thesis contains six research manuscripts, describing fear conditioning studies that mainly applied EEG methods in combination with other central (fMRI) and peripheral (skin conductance, heart rate, and fear-potentiated startle) measures. A special focus of this thesis lies in methodological considerations for EEG fear conditioning research. In addition, catecholaminergic mechanisms are studied, with the ultimate goal of opening up new translational perspectives. Taken together, the present thesis addresses several methodological challenges for neuroscientific (in particular, EEG) fear conditioning research (e.g., appropriate US types and experimental designs, signal-to-noise ratio, simultaneous EEG-fMRI). Furthermore, this thesis gives critical insight into catecholaminergic (noradrenaline and dopamine) mechanisms. A variety of neuroscientific methods (e.g., EEG, fMRI, peripheral physiology, pharmacological manipulation, genetic associations) have been combined, an approach that allowed us (a) to translate knowledge from animal studies to human research, and (b) to stimulate novel clinical directions