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IntroductionCardiorespiratory exercise has emerged as a promising candidate to modify disease progression in Huntington's disease (HD). In animal models, exercise has been found to alter biomarkers of neuroplasticity and delay evidence of disease, and some interventions-including exercise-have shown benefits in human HD patients. In healthy human populations, increasing evidence suggests that even a single bout of exercise can improve motor learning. In this pilot study, we investigated the effect of a single bout of moderate intensity aerobic exercise on motor skill learning in presymptomatic and early manifest HD patients. MethodsParticipants were allocated to either an exercise (n = 10) or control (n = 10) group. They performed either 20 min of moderate intensity cycling or rest before practicing a novel motor task, the sequential visual isometric pinch force task (SVIPT). After 1 week, the retention of the SVIPT was measured in both groups. ResultsWe found that the exercise group performed significantly better during initial task acquisition. There were no significant differences in offline memory consolidation between groups, but total skill gain across both acquisition and retention sessions was greater in the group who exercised. The better performance of the exercise group was driven by improvements in accuracy, rather than speed. DiscussionWe have shown that a single bout of moderate intensity aerobic exercise can facilitate motor skill learning in people with HD gene-expansion. More research is needed to investigate the underlying neural mechanisms and to further explore the potential for neurocognitive and functional benefits of exercise for people with HD., Frontiers in Psychology, 14, ISSN:1664-1078

Attempts to enhance human memory and learning ability have a long tradition in science. This topic has recently gained substantial attention because of the increasing percentage of older individuals worldwide and the predicted rise of age-associated cognitive decline in brain functions. Transcranial brain stimulation methods, such as transcranial magnetic (TMS) and transcranial electric (tES) stimulation, have been extensively used in an effort to improve cognitive functions in humans. Here we summarize the available data on low-intensity tES for this purpose, in comparison to repetitive TMS and some pharmacological agents, such as caffeine and nicotine. There is no single area in the brain stimulation field in which only positive outcomes have been reported. For self-directed tES devices, how to restrict variability with regard to efficacy is an essential aspect of device design and function. As with any technique, reproducible outcomes depend on the equipment and how well this is matched to the experience and skill of the operator. For self-administered non-invasive brain stimulation, this requires device designs that rigorously incorporate human operator factors. The wide parameter space of non-invasive brain stimulation, including dose (e.g., duration, intensity (current density), number of repetitions), inclusion/exclusion (e.g., subject’s age), and homeostatic effects, administration of tasks before and during stimulation, and, most importantly, placebo or nocebo effects, have to be taken into account. The outcomes of stimulation are expected to depend on these parameters and should be strictly controlled. The consensus among experts is that low-intensity tES is safe as long as tested and accepted protocols (including, for example, dose, inclusion/exclusion) are followed and devices are used which follow established engineering risk-management procedures. Devices and protocols that allow stimulation outside these parameters cannot claim to be “safe” where they are applying stimulation beyond that examined in published studies that also investigated potential side effects. Brain stimulation devices marketed for consumer use are distinct from medical devices because they do not make medical claims and are therefore not necessarily subject to the same level of regulation as medical devices (i.e., by government agencies tasked with regulating medical devices). Manufacturers must follow ethical and best practices in marketing tES stimulators, including not misleading users by referencing effects from human trials using devices and protocols not similar to theirs., Clinical Neurophysiology Practice, 7, ISSN:2467-981X

Several studies in the recent past have demonstrated how Brain Computer Interface (BCI) technology can uncover the neural mechanisms underlying various tasks and translate them into control commands. While a multitude of studies have demonstrated the theoretic potential of BCI, a point of concern is that the studies are still confined to lab settings and mostly limited to healthy, able-bodied subjects. The CYBATHLON 2020 BCI race represents an opportunity to further develop BCI design strategies for use in real-time applications with a tetraplegic end user. In this study, as part of the preparation to participate in CYBATHLON 2020 BCI race, we investigate the design aspects of BCI in relation to the choice of its components, in particular, the type of calibration paradigm and its relevance for long-term use. The end goal was to develop a user-friendly and engaging interface suited for long-term use, especially for a spinal-cord injured (SCI) patient. We compared the efficacy of conventional open-loop calibration paradigms with real-time closed-loop paradigms, using pre-trained BCI decoders. Various indicators of performance were analyzed for this study, including the resulting classification performance, game completion time, brain activation maps, and also subjective feedback from the pilot. Our results show that the closed-loop calibration paradigms with real-time feedback is more engaging for the pilot. They also show an indication of achieving better online median classification performance as compared to conventional calibration paradigms (p = 0.0008). We also observe that stronger and more localized brain activation patterns are elicited in the closed-loop paradigm in which the experiment interface closely resembled the end application. Thus, based on this longitudinal evaluation of single-subject data, we demonstrate that BCI-based calibration paradigms with active user-engagement, such as with real-time feedback, could help in achieving better user acceptability and performance., Frontiers in Human Neuroscience, 15, ISSN:1662-5161

Previous research suggests that anodal transcranial direct current stimulation (tDCS) over the primary motor cortex (M1) modulates NMDA receptor dependent processes that mediate synaptic plasticity. Here we test this proposal by applying anodal versus sham tDCS while subjects practiced to flex the thumb as fast as possible (ballistic movements). Repetitive practice of this task has been shown to result in performance improvements that reflect use-dependent plasticity resulting from NMDA receptor mediated, long-term potentiation (LTP)-like processes. Using a double-blind within-subject cross-over design, subjects (n=14) participated either in an anodal or a sham tDCS session which were at least 3 months apart. Sham or anodal tDCS (1 mA) was applied for 20 min during motor practice and retention was tested 30 min, 24 hours and one week later. All subjects improved performance during each of the two sessions (p < 0.001) and learning gains were similar. Our main result is that long term retention performance (i.e. 1 week after practice) was significantly better when practice was performed with anodal tDCS than with sham tDCS (p < 0.001). This effect was large (Cohen’s d=1.01) and all but one subject followed the group trend. Our data strongly suggest that anodal tDCS facilitates long-term memory formation reflecting use-dependent plasticity. Our results support the notion that anodal tDCS facilitates synaptic plasticity mediated by an LTP-like mechanism, which is in accordance with previous research., PLoS ONE, 10 (5), ISSN:1932-6203

Social deficits are a core symptom of autism spectrum disorder; however, the perturbed neural mechanisms underpinning these deficits remain unclear. It has been suggested that social prediction errors—coding discrepancies between the predicted and actual outcome of another’s decisions—might play a crucial role in processing social information. While the gyral surface of the anterior cingulate cortex signalled social prediction errors in typically developing individuals, this crucial social signal was altered in individuals with autism spectrum disorder. Importantly, the degree to which social prediction error signalling was aberrant correlated with diagnostic measures of social deficits. Effective connectivity analyses further revealed that, in typically developing individuals but not in autism spectrum disorder, the magnitude of social prediction errors was driven by input from the ventromedial prefrontal cortex. These data provide a novel insight into the neural substrates underlying autism spectrum disorder social symptom severity, and further research into the gyral surface of the anterior cingulate cortex and ventromedial prefrontal cortex could provide more targeted therapies to help ameliorate social deficits in autism spectrum disorder., Brain: A Journal of Neurology, 140 (1), ISSN:0006-8950, ISSN:1460-2156

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity., Scientific Data, 4, ISSN:2052-4463

Background The COVID-19 pandemic has broadly disrupted biomedical treatment and research including non-invasive brain stimulation (NIBS). Moreover, the rapid onset of societal disruption and evolving regulatory restrictions may not have allowed for systematic planning of how clinical and research work may continue throughout the pandemic or be restarted as restrictions are abated. The urgency to provide and develop NIBS as an intervention for diverse neurological and mental health indications, and as a catalyst of fundamental brain research, is not dampened by the parallel efforts to address the most life-threatening aspects of COVID-19; rather in many cases the need for NIBS is heightened including the potential to mitigate mental health consequences related to COVID-19. Objective To facilitate the re-establishment of access to NIBS clinical services and research operations during the current COVID-19 pandemic and possible future outbreaks, we develop and discuss a framework for balancing the importance of NIBS operations with safety considerations, while addressing the needs of all stakeholders. We focus on Transcranial Magnetic Stimulation (TMS) and low intensity transcranial Electrical Stimulation (tES) - including transcranial Direct Current Stimulation (tDCS) and transcranial Alternating Current Stimulation (tACS). Methods The present consensus paper provides guidelines and good practices for managing and reopening NIBS clinics and laboratories through the immediate and ongoing stages of COVID-19. The document reflects the analysis of experts with domain-relevant expertise spanning NIBS technology, clinical services, and basic and clinical research – with an international perspective. We outline regulatory aspects, human resources, NIBS optimization, as well as accommodations for specific demographics. Results A model based on three phases (early COVID-19 impact, current practices, and future preparation) with an 11-step checklist (spanning removing or streamlining in-person protocols, incorporating telemedicine, and addressing COVID-19-associated adverse events) is proposed. Recommendations on implementing social distancing and sterilization of NIBS related equipment, specific considerations of COVID-19 positive populations including mental health comorbidities, as well as considerations regarding regulatory and human resource in the era of COVID-19 are outlined. We discuss COVID-19 considerations specifically for clinical (sub-)populations including pediatric, stroke, addiction, and the elderly. Numerous case-examples across the world are described. Conclusion There is an evident, and in cases urgent, need to maintain NIBS operations through the COVID-19 pandemic, including anticipating future pandemic waves and addressing effects of COVID-19 on brain and mind. The proposed robust and structured strategy aims to address the current and anticipated future challenges while maintaining scientific rigor and managing risk., Brain Stimulation, 13 (4), ISSN:1935-861X, ISSN:1876-4754

Background In the last decade, interest in combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) approaches has grown substantially. Aside from the obvious artifacts induced by the magnetic pulses themselves, separate and more sinister signal disturbances arise as a result of contact between the TMS coil and EEG electrodes. New method Here we profile the characteristics of these artifacts and introduce a simple device – the coil spacer – to provide a platform allowing physical separation between the coil and electrodes during stimulation. Results EEG data revealed high amplitude signal disturbances when the TMS coil was in direct contact with the EEG electrodes, well within the physiological range of viable EEG signals. The largest artifacts were located in the Delta and Theta frequency range, and standard data cleanup using independent components analysis (ICA) was ineffective due to the artifact’s similarity to real brain oscillations. Comparison with existing method While the current best practice is to use a large coil holding apparatus to fixate the coil ‘hovering’ over the head with an air gap, the spacer provides a simpler solution that ensures this distance is kept constant throughout testing. Conclusions The results strongly suggest that data collected from combined TMS-EEG studies with the coil in direct contact with the EEG cap are polluted with low frequency artifacts that are indiscernible from physiological brain signals. The coil spacer provides a cheap and simple solution to this problem and is recommended for use in future simultaneous TMS-EEG recordings., Journal of Neuroscience Methods, 294, ISSN:0165-0270, ISSN:1872-678X

Functional magnetic resonance imaging (fMRI) has become a mainstay technique to non-invasively monitor brain activity and infer brain function in humans. However, given the more stringent ethical limitations in clinical research, it remains a matter of correlating the acquired signal to states of health and disease. In recent years, technical as well as procedural progress has brought fMRI to the preclinical field of rodent neuroscience. With a plethora of methods available to monitor, control, and tune neuronal activity, multimodal fMRI in rodents presents a unique opportunity to link microscopic activity to meso- and macroscopic scales and as such, provide a causal account of obtained fMRI signals. In this thesis, we combined temporally and spatially precise optogenetic modulation in two prominent systems of the anaesthetized mouse brain with fMRI (opto-fMRI) to gain a better understanding of how changes at the neuronal level can map onto systems-level brain function. First, we tested the hypothesis of a functional antagonism between direct (D1R) and indirect (D2R) pathway neurons of the ventrolateral (vl) striatum within the basal ganglia (BG) - thalamocortical system. Using the combined opto-fMRI approach, we found differential but not the commonly theorized opposing effects of D1R and D2R cells along the canonical direct and indirect pathways. Importantly, these functional characteristics extended beyond the BG – thalamocortical system to include prefrontal and cerebellar regions, findings which were further corroborated by effective connectivity analysis using regression dynamic causal modelling (rDCM). Second, we investigated how physiologically relevant tonic and burst-like firing patterns of noradrenergic neurons in the locus coeruleus (LC) affect global brain activity and dynamics. We demonstrated that optogenetic LC stimulation evokes whole-brain activity that is specific to both its firing frequency and firing pattern. Furthermore, we provided evidence that different intensities of LC activity across the tonic range convey local activity profiles in a heterogeneous manner, including non-linear and inverted U-shaped modulation. Taken together, these results highlight the power of combining spatiotemporally precise optogenetic stimulation with fMRI for visualising long-range changes in brain activity downstream of the target region and providing a causal explanation thereof.

Spinal cord injury (SCI) is a devastating and life-changing incident that leads to immediate and usually persisting motor, sensory, and autonomic dysfunctions, such as impairments in bladder and bowel function. These are often accompanied by the development of chronic pain and psychological concomitants, for instance depression or cognitive decline, which are negatively associated with rehabilitation and quality of life after SCI. Trauma-induced mechanical disruption and dislocation of the spinal vertebral column lead to an immediate damage of the spinal cord which is characterized by neuronal and glial cell death and disruption of axons and the spinal vasculature. This primary injury initiates a multifaceted cascade of secondary injury processes which is hallmarked by the recruitment of reactive astrocytes forming a glial scar to encapsulate the toxic environment of the lesion core that represents an inhibitory barrier to axonal regrowth. Injury-induced neurodegenerative and neuroinflammatory processes can last for years, spreading to supralesional levels and exacerbating the initial damage. Early post-injury treatment includes neuroprotective and neuroregenerative medication, aiming at preventing secondary damage and increasing the intramedullary regenerative potential, beyond endogenous plasticity and attempts of repair. Evaluation of the efficacy of distinct treatment approaches in interventional trials calls for assessments that can sensitively detect changes of clinically relevant markers. Clinical examinations usually lack the necessary sensitivity as they use ordinal scales for the classification of patients, and are also unspecific to structural correlates underlying the clinical deficits. Magnetic resonance imaging (MRI) is a non-invasive and objective method which enables the qualitative and quantitative assessment of macroscopic and microscopic changes within the neural tissue after SCI. It can thus improve our understanding of pathological primary and secondary injury processes along the whole neuraxis post-SCI and how these change during the course of recovery and relate to clinical outcomes. Previous studies found MRI-derived cervical spinal cord atrophy above the lesion level of up to 30% at 5 years post-injury. Volumetric changes in clinically relevant motor and sensory regions in the brain were also detected, which were paralleled by decreased tract integrity, pathological reductions in myelin-sensitive markers, and increases in neuroinflammatory metabolites in chronic SCI. The overall goal of this thesis was to improve our understanding of conventional and advanced MRI-derived structural, molecular, and functional changes at the lesion site and above the lesion following SCI and to explore their value as biomarkers for characterization of lesion severity and neurological disability, prediction of clinical outcome, and potential implementation as surrogate markers in interventional trials. In the first study, we investigated the longitudinal spatiotemporal dynamics of the lesion extent and the width of injury-spared tissue bridges in paraplegic SCI patients by means of conventional MRI and how baseline lesion characteristics relate to clinical outcome. At 1 month following SCI, after widespread edema and hemorrhage have resolved, midsagittal lesion segmentation was reliably and accurately performable. Over the course of 2 years, the lesion extent slightly decreased while tissue bridges' width increased, possibly due to the cystic cavity getting fully demarcated at around three to four weeks post-SCI. Crucially, patients of traumatic or ischemic etiology showed similar lesion evolutions and courses of neurological recovery, its magnitude being associated with the size of the lesion and spared tissue bridges in both patient groups. The second study aimed at exploring the value of conventional MRI-derived spared tissue bridges for prediction of neurological recovery at 1 year post-SCI, focusing not only on the width, as in most previous studies, but also on the localization of tissue bridges. Larger 1-month ventral and dorsal tissue bridges demonstrated a predictive relationship with higher American Spinal Injury Association Impairment Scale (AIS) grade conversion rates at 1 year follow-up. Using unbiased recursive partitioning conditional inference tree (URP-CTREE) analysis, ventral tissue bridges were identified as predictors of pin prick and motor scores and dorsal tissue bridges as predictors of functional independence scores, adding value to baseline clinical scores for improved stratification of patients into more homogenous and recovery-specific sub-groups. In the third study, we explored the role of spared tissue bridges for the development of neuropathic pain (NP), which represents one of the main burdens following SCI and is often refractory to treatment. We found that 1-month ventral tissue bridges were larger in patients with NP when compared to pain-free SCI patients. Representing a proxy for spinothalamic tract function, ventral tissue bridges were furthermore predictive of 1-year pin prick score and pain intensity. Crucially, the URP-CTREE algorithm identified a critical cut-off in ventral tissue bridges’ width (≤2.1mm or >2.1mm), dividing patients into sub-groups of higher and lower scores of pin prick sensation and pain intensity. These two studies highlight the potential of spared tissue bridges to improve prediction of outcome and optimize stratification of SCI patients in interventional trials. The fourth study aimed at identifying neurochemical biomarkers of chronic NP after SCI above the lesion level by means of advanced and quantitative proton magnetic resonance spectroscopy (MRS). At the remote cervical spinal cord at level C2/3, we revealed a pain-specific molecular fingerprint of increased neuroinflammatory but similar neurodegenerative metabolite concentrations in patients with NP when compared to pain-free SCI patients. Increased neuroinflammatory metabolite levels were furthermore associated with less cord atrophy and higher pin prick scores, which might represent molecular surrogate markers of NP and potentially provide new NP treatment targets. In the fifth study, we investigated whether the right hippocampus is pathologically affected in chronic SCI patients, using a multimodal approach including structural MRI, quantitative MRS, and memory performance. Previous studies reported that SCI patients suffer from cognitive impairments including deficits in learning and memory, possibly caused by brain inflammation. In this study, no secondary supralesional changes were detected in terms of an altered metabolic profile indicative of potential neurodegeneration or neuroinflammation, hippocampal atrophy, or memory impairments. SCI thus does not seem to directly affect the hippocampal integrity and post-SCI cognitive deficits might be attributable to secondary concomitants of SCI or methodological study differences. In conclusion, the studies in this thesis made use of conventional and advanced MRI for characterization of the primary injury at the focal lesion site and investigation of far-reaching structural, molecular, and functional biomarkers above the lesion level which are indicative of remote secondary injury processes following SCI, such as neurodegeneration, neuroinflammation, or reorganization. We were able to identify preserved tissue bridges adjacent to the lesion as predictive neuroimaging biomarkers of tract-specific neurological recovery and pathological somatosensory function in terms of NP. This thesis expands previous knowledge of secondary neurodegenerative and demyelinating processes at the remote cervical spinal cord and reveals a NP-related neuroinflammatory metabolic profile in the upper cervical cord in chronic SCI patients by means of advanced quantitative MRS. At the same time, the hippocampus was not found to be pathologically affected on a structural or molecular level after SCI. Conventional and advanced MRI-derived quantitative biomarkers have the potential to detect subclinical changes post-SCI and to be used as surrogate markers in interventional trials for monitoring of recovery processes and treatment effects with the ultimate goal of improving personalized patient care and achieving clinically meaningful recovery following SCI. Adding complementary value to neurological and electrophysiological assessments, clinically applicable conventional and advanced MRI might be especially powerful when used synergistically and acquired longitudinally across different centers. This could help us to improve our understanding of neuropathological and reorganizational processes along the neuraxis post-injury and to identify the most reliable and sensitive neuroimaging biomarkers to evaluate the efficacy of interventions aiming at reducing neurodegeneration and enhancing recovery following SCI.

In everyday life countless stimuli are delivered to our central nervous system from the environment. The processing of incoming information is not free of noise. Even though it is counterintuitive at first, some level of background noise can have a positive impact on signal processing in the central nervous system. It has been hypothesized that neural processing can benefit from added noise via a Stochastic Resonance (SR) phenomenon. SR is a general mechanism that enhances the response of nonlinear systems to weak subthreshold signals by adding an optimal level of random noise. Using transcranial random noise stimulation (tRNS), electrical noise can be added centrally to cortical circuits to modulate brain function. In this thesis, we investigated the immediate online effects of noise on the central nervous system. We probed the responsiveness of motor and visual systems in the presence and absence of electrical noise. Additionally, we explored the effects of high-frequency non- stochastic electrical stimulation on sensory processing. We began by reviewing the current literature and delineating the effects of electrical noise at the cellular, systems, and behavioral levels. We discussed the putative mechanism underpinning the effect of electrical noise stimulation on neural processing and how electrical noise might be utilized to augment sensory and motor function. In the first study, we investigated the acute effects of noise on the neural population level in awake human participants. We showed that the responsiveness of the primary motor cortex (M1) increases immediately when electrical noise is added via tRNS. In the second study, we explored the acute effects of tRNS delivered to two connected yet anatomically remote neural populations within the visual system, namely the primary visual cortex (V1) and the retina. We observed a significant decrease in the visual contrast detection threshold compared to baseline during tRNS delivery to V1 but not to the retina, suggesting that tRNS affects these neural populations differently. In the third study, we empirically tested the theoretical prediction that in addition to stochastic signals, non-stochastic signals can also cause resonance effects. We found that non-random high-frequency transcranial alternating current stimulation (hf-tACS) applied to V1 lowers the contrast detection threshold, reflecting enhanced visual detection performance. Altogether our work addresses the potential use of acute electrical noise added to cortical circuits to modulate physiology and enhance brain function. Our findings are consistent with the hypothesis that neural processing can benefit from added noise via a SR phenomenon, but also demonstrate the potential use of alternative waveforms to induce resonance-like effects. More broadly, our work sheds new light on a possible mechanism underpinning the effect of acute electrical noise stimulation on neural processing and provides a new paradigm for testing SR theory predictions in the human brain. Our results highlight the general importance and relevance of SR-like mechanisms in the human brain and will potentially lead to new developments and applications across various disciplines, including basic neuroscience, neurophysiology, computational biology, and clinical research.

The human wrist is to the hand, as what the pen is to the poet. The latter cannot work without the former. The wrist not only serves to orientate the hand before a grasp, but also to stabilize it during a grasp. These two functions of the upper limb are inseparable, and a disorder of the wrist joint negatively affects dexterity and grip strength of the hand. Upper limb paresis is the most common impairment following neurological disorders such as stroke, and affects more than 3'700 individuals in Switzerland each year. Stroke survivors often suffer from abnormal muscle tone such as spasticity, tremors, and pain, which affects wrist function and negatively impacts independence and quality of life. The rehabilitation of these functions is possible during conventional therapy and can be enhanced through high dose and intensive movement-based training delivered by robotic systems. Robot-assisted therapy promotes active participation combined with proprioceptive feedback that reinforces motor learning and somatosensory recovery. By quantitatively assessing the recovery and providing a motivating environment, robot-assisted therapy stands as an adequate candidate to supplement conventional therapy. Nevertheless, therapy administered via robotic devices remains in the minority of treatments and many patients after discharge from the hospital suffer from persistent wrist and hand impairments. Therefore, novel and accessible technologies that empower the patient to self-initiate and continue rehabilitation training must be developed and made commonplace. Home-based rehabilitation using robotic technologies is a promising and growing field that has triggered the development of many devices. In addition to promoting independent rehabilitation training, powered wearable devices have the potential to provide assistance during functional everyday tasks. However, besides meeting the requirements for supporting a given motor function, the development of such solutions must strike a balance between functionality, usability and wearability. In particular, the ease to mount and unmount (don and doff) is an essential aspect that has so far been rarely addressed in many projects targeting home-based therapy. The aim of this thesis was to develop, characterize and evaluate a fully wearable wrist exoskeleton - the eWrist - that actively supports extension and flexion movements. Envisioned as a tool for assistance during daily tasks, the development focused on usability and wearability of the device. Furthermore, this thesis aimed at implementing a robust and intuitive control scheme on a wearable exoskeleton that promotes voluntary effort using physiological signals. To achieve this goal, existing technologies targeting the upper limb were reviewed and requirements for a wearable wrist exoskeleton were determined. Weight, size, actuation torque, angular velocity, range of motion, and most importantly ease of implementation were aspects considered when choosing an appropriate transmission type that meets the requirements. With the goal of building a device for independent use, a mechanism to don the eWrist with a single hand was implemented. Moreover, the development of the first prototype and subsequent iterations prioritized the selection of widespread and affordable components, and the use of 3D printing techniques and open-source software that would facilitate potential integration into maker communities. The non-backdrivability of the transmission imposed the implementation of an admittance control scheme that allowed smooth and stable interactions between the user and the robot. To investigate the feasibility of intuitive control promoting voluntary effort, an sEMG-based controller was implemented and evaluated on a single healthy subject. The results showed that the fastening system enabled quick and easy donning and doffing, and a firm attachment to the forearm and hand. Moreover, the sEMG controller proved to drive the assistance support in accordance with the intention of the user. To further improve functionality and wearability, a new iteration of the eWrist was characterized and evaluated in fifteen healthy participants and two stroke survivors. Shortcomings of the previous iteration were addressed by: reducing weight and physical profile, increasing durability, improving interaction with the device, and further improving the donning procedure. A novel fastening system including electronics and battery was developed that enabled donning of the entire exoskeleton using one hand. Standardized human-robot interaction metrics and impedance planes were used to characterize and evaluate the various behaviours that can render the device. Based on the established requirements, the developed solution fulfilled or even outperformed expectations. The time required to mount the eWrist revealed that after a few practice trials participants could don it independently in about 1 min. In addition, standardized usability questionnaires completed by the participants showed that they all embraced the device and found its attachment system efficient and simple to use. The non-backdrivability of the transmission combined with a stiffening of the wrist joint generates instabilities in the physical human-robot interaction (pHRI) that were assessed in a goal-directed visuomotor task. A variable admittance control scheme was implemented to detect and dampen these disturbances, and was evaluated in ten healthy participants and six stroke survivors performing the task. In addition, an improved sEMG-based controller, together with a gravity compensation controller were implemented to promote voluntary effort and support wrist weakness. The stability and transparency of the pHRI, characterized by metrics such as jerk, interaction force, and angular velocity/acceleration, was used to assess the effectiveness of the variable admittance scheme. In the context of the visuomotor task, the variable admittance controller proved to significantly reduce instabilities in the human-robot interaction with healthy participants. Additionally, both controllers could enhance wrist functionality of stroke survivors, especially in the most extreme angular positions and more impaired patients. After many iterations, the latest version of the eWrist exoskeleton has resulted in a solution that combines lightweight, low physical profile, ease of donning, and intuitive control to support extension and flexion wrist function in patients with neuromotor impairment. Furthermore, the portability of the eWrist makes it suitable for deployment in various environments whether in a clinic or at an individual's home. Finally, thanks to a focus on accessibility and simplicity throughout the design process, the eWrist meets an optimal trade-off between complexity and functionality to increase access to affordable orthoses for stroke rehabilitation.

Optic neuritis (ON) is an acute inflammatory, demyelinating event affecting the optic nerve, and a common manifestation in multiple sclerosis (MS). It can affect MS patients throughout their disease course, and 20 % of patients present with acute ON as their initial symptom. ON primarily affects the optic nerve in its myelinated portion, but also triggers neurodegeneration in the entire afferent visual pathway (AVP) through retrograde and anterograde (trans-synaptic) degeneration. Visual outcomes are diverse, including severe persistent visual impairment. High-dose corticosteroids are the current mainstay in the therapy of acute autoimmune ON. However, despite clear acceleration of functional visual recovery in the short-term, any mid- to long-term impact on visual outcomes remains unproven. Apart from its high prevalence and clinical relevance, ON also offers a unique model to study neurodegeneration as well as the potential of neuroprotective and –regenerative therapies: a clinical episode of acute ON can be assigned in its occurrence to an approximate time window, and in its impact on tissue integrity to a discrete, anatomically isolated structure. The AVP is retinotopically organized, linking its structural integrity with clinical function. Almost the entire AVP can be probed using imaging tools of different modalities, including optical coherence tomography (OCT) and structural magnetic resonance imaging (MRI) techniques such as diffusion-tensor-imaging (DTI). Furthermore, the function of the AVP can be assessed by simple but sensitive measurements such as low-contrast visual acuity (LCVA). Therefore, ON provides an optimal paradigm to study the consequences of an MS-relapse on tissue integrity and function. In the first section of this thesis, we reviewed the growing relevance of monitoring the thicknesses of different retinal layers using OCT to reveal AVP damage in MS. We summarized that the thicknesses of the macular ganglion cell and inner plexiform layer (GCIP) and the peripapillary retinal nerve fiber layer (pRNFL) are informative with regard to early detection of neuronal degeneration and long-term axonal damage, respectively, of the retinal ganglion cells (RGCs) in MS. A significant body of literature demonstrates that OCT-derived measures are not only associated with visual function, but also with other clinically relevant parameters such as grey matter atrophy or the Expanded Disability Status Scale (EDSS) score − a standard measure of overall disability in MS. Additionally, based on current research in the field, the review paper also highlights the possible role of the macular inner nuclear layer (INL) in detecting inflammatory disease activity and response to treatment in MS. Taking into account that ON is the main driver of neuro-axonal retinal damage in MS, we highlighted the further importance of the application of OCT in patients with ON. Although a great number of cross-sectional OCT studies in ON have been published to date, longitudinal studies remain relatively rare but are indispensable in order to achieve better knowledge of the temporal dynamics and magnitude of retinal neuro-axonal and functional visual damage following ON. Therefore, in a retrospective longitudinal study, we attempted to describe the changes in retinal structure and visual function over one year following clinically first-ever unilateral ON in both affected and unaffected eyes, using OCT as well as high- contrast visual acuity (HCVA) and LCVA testing. We found that the GCIP and pRNFL had substantial thinning in ON eyes, with early GCIP thinning (74.5 % of the total reduction occurring within the first month), and slightly later thinning of pRNFL (87.8 % within the first three months following ON). Furthermore, we found that the INL thickness was significantly increased in ON eyes (by month 1), but also, and more surprisingly, in the contralateral non-ON (NON) eyes (by month 12) following clinically unilateral ON, which is a novel finding. It is possible that subclinical involvement of the fellow eye resulted in this INL increase, indicating bilateral retinal pathology, although further research is needed to confirm this hypothesis. Additionally, we observed severely impaired visual acuity in ON eyes at onset of symptoms. Even though we detected functional improvement over time, particularly in HCVA, LCVA remained clinically impaired up to the final study time point. Overall, this data can have an impact on future therapeutic strategies by highlighting the particular importance of early treatment of ON. Pathology of the optic nerve and retina has also been described in murine models of MS, including myelin oligodendrocyte glycoprotein (MOG) peptide-induced experimental autoimmune encephalomyelitis (EAE). Therefore, in a longitudinal EAE study, we aimed to further investigate the mechanisms involved in ON-induced pathology of the AVP using a multimodal imaging approach. Because the retina is void of myelin, an important contributor to chronic neuro-axonal damage following ON, namely demyelination, cannot be assessed using OCT. Therefore, we assessed the utility of DTI as a means to investigate AVP pathology following ON, allowing the assessment of the myelinated portion of the optic nerve and tract. Consistent with previous literature, we found a gradual decrease in fractional anisotropy values in the optic nerve and tract implying white matter tissue damage in EAE. In parallel, radial diffusivity (RD) significantly increased in EAE mice, likely reflecting ongoing demyelination. Hence, we concluded, that DTI is valuable in capturing demyelination of the optic nerve and tract in EAE. In order to avoid permanent neuro-axonal tissue loss and associated disability, the search for new strategies to either prevent demyelination or enhance remyelination is of increasing importance in the field of MS. Therefore, eligible outcome measures should be able to capture these target mechanisms, pointing out the valuable role of RD as a biomarker. Currently, there are no satisfactory neuroprotective therapies or visual rehabilitation programs available for patients with ON. As visual function has been rated as one of the most important bodily functions by MS patients, the high prevalence of visual impairment in MS following episodes of ON remains a major unsolved problem in the disease management. With the aim of finding new therapeutic options that specifically target long-term prevention of persistent visual disability, we performed an interdisciplinary literature review. We found a significant body of preclinical as well as clinical evidence showing that low-current electrical stimulation of the retina and optic nerve in optic neuropathies of different causes may have neuroprotective and - restorative effects on RGCs. Clinical research exploring the potential of this so-called repetitive transorbital alternating current stimulation (rtACS) in patients with autoimmune ON has not yet been performed. We discussed why we would expect a beneficial effect of rtACS on remyelination, on other repair-promoting mechanisms in RGCs, and also on visual outcomes in patients with a first-ever acute ON. Moreover, we presented an optimal study design to investigate the safety, tolerability and preliminary efficacy of rtACS in this specific patient cohort.

Closed-loop auditory stimulation (CLAS) of slow waves, characterized by low degree of invasiveness and high target specificity, is established as a highly promising tool in both basic and clinical sleep research. It constitutes a first of a kind alternative to the burdened pharmacological interventions currently dominating sleep medicine. For that reason, the application of CLAS in animal models is essential for a mechanistic understanding and technical optimization. Firstly, we report the development and characterization of what we believe is the first rodent model of phase-locked CLAS during slow wave sleep. Thus, we tested the effects of up- and down phase CLAS on proportions and spectral characteristics of sleep in healthy rats during the training-phase of the single pellet-reaching task. Without affecting 24-h sleep-wake behaviour, CLAS specifically altered SWA and sigma power over a chronic period of stimulation. Down-phase CLAS exerted a detrimental effect on engagement and success rate in this behavioural test. Therefore, modulation of SWA, altering the nesting of memory-consolidating spindle activity and, additionally, regulating intrinsic motivational states, appears as responsible for modified learning performance in our novel rodent model of CLAS. Secondly, we implemented this technique in a TBI rat model. In this context, elevated SWA is believed to be essential for efficient intracellular and extracellular clearance of trauma-related noxious subproducts, such as amyloid-β precursor protein (APP). Our past work showed that both sleep induction (GHB administration) and sleep restriction (SR) in TBI rats promoted enhanced SWA, resulting in increased APP clearance and improved cognition. Although promising, these sleep modulatory procedures have several drawbacks, including lack of specificity. Therefore, we used CLAS to precisely modulate SWA immediately after trauma. Up phase CLAS enhanced SWA, reduced APP+ axonal bulbs in the corpus callosum and improved cognitive ability in TBI animals. Conversely, targeting the down-phase of slow waves down-regulated slow oscillatory activity, and did not offer any beneficial effect over TBI-sequalae. Overall, we attempt to address a fundamental gap in technology — i.e. the implementation of CLAS to the rodent brain — that has so far hindered our understanding of the mechanistic link of auditory-modulated slow waves with learning and memory, as well as other brain processes strongly influenced by slow-wave sleep, such as the glymphatic function. At the very same time, given that it allows for specific and physiological modulation of sleep depth, this rodent technology represents a unique approach to explore the open questions of sleep functions. Our results provide proof of principle evidence that phase-targeted CLAS of slow waves is effective, safe and stable over chronic experimental periods, and offer pre-clinical indication of potential non pharmacologic slow-wave modulatory clinical applicability with therapeutic implications.

Eating, washing and dressing oneself are just a few examples of upper limb tasks we perform every day with little effort. For people suffering from a stroke, these tasks can become challenging due to sensorimotor impairments of the upper limb. Consequently, providing efficient and evidence based therapeutic strategies is crucial to improve their quality of life and independence. Cooperative, object-oriented hand movements underlie an enhanced neural coupling of the upper limbs reflected in a strong bilateral neural organization including enhanced bilateral muscle reflexes and sensory processing after unilateral nerve stimulation. This neural characteristic is partly preserved in stroke survivors indicating that tracts of the non-affected hemisphere are strongly involved in the control of the affected arm. A training of cooperative hand movements based on this neural behaviour might be promising for a better sensorimotor recovery of the upper limb. Still, not much is known about the neural control of these movements and no therapy approach focussing on these movements is currently available. Thus, the aim of this thesis was to get a more profound understanding of the sensorimotor control underlying cooperative hand movements and to evaluate their potential for stroke rehabilitation.

The human brain is a heavily interconnected structure giving rise to complex functions. While brain functionality is mostly revealed during wakefulness, the sleeping brain might offer another view into physiological and pathological brain connectivity. Furthermore, there is a large body of evidence supporting that sleep mediates plastic changes in brain connectivity. Although brain plasticity depends on environmental input which is provided in the waking state, disconnection during sleep might be necessary for integrating new into existing information and at the same time restoring brain efficiency. The analysis of sleep-dependent restoration therefore may provide additional insight into the mechanisms underlying healthy and altered brain function. The overarching aim of this thesis was to examine alterations in markers of brain connectivity and sleep-dependent restoration in clinical populations. To this end, we first evaluated structural, molecular, and electrophysiological markers of brain connectivity and sleep-dependent restoration using Magnetic Resonance Imaging and electroencephalography in a healthy population. More specifically, this was carried out in the framework of healthy brain development, as this time window is characterized by major changes in brain connectivity and plasticity and therefore represents an ideal setting to test these markers. In a second step, we translated the gained findings into two clinical populations in which alterations in brain connectivity have been described, the neuropsychiatric disorder attention-deficit/hyperactivity disorder (ADHD) and the neurologic disorder thalamic ischemic stroke. Results of the first part validated previously established markers of brain connectivity. These included the structural marker gray matter volume, the electrophysiological markers slow wave activity (SWA) and slow wave slope, and the molecular marker glutamate + glutamine (GLX). In addition, the decrease of SWA and slow wave slope across the night were confirmed as markers for sleep-dependent restoration. Although overnight GLX changes seemed a promising marker for sleep-dependent restoration in healthy young adults, this was not confirmed in healthy children and adolescents. In the second part, we demonstrated alterations in SWA and overnight slope changes in ADHD and in thalamic ischemic stroke. Moreover, these markers were shown to be linked to core symptoms in the investigated disorders. Taken together, our results indicate that SWA and overnight slope changes constitute promising biomarkers to assess alterations in brain connectivity and sleep-dependent restoration in clinical populations. Furthermore, these findings provide valuable insight into the mechanisms of pathophysiology in ADHD and in thalamic ischemic stroke. Finally, this data suggests a bi-directional relationship between brain connectivity and sleep-dependent restoration which needs to be investigated further in future studies.

Ageing is a natural process that is accompanied by several structural and functional changes leading to an increase in blood pressure (BP), reduced sleep, a decrease in pulmonary function, and reduced exercise capacity. Physical exercise is an effective strategy to improve many of the variables that are known to deteriorate with advancing age, including BP, sleep and exercise capacity. However, whether sleep is disrupted after an acute bout of evening exercise, thus potentially increasing the risk to develop hypertension, is currently unknown and needs to be tested. Further, due to an age-associated increase in prevalence of conditions affecting the musculoskeletal system, alternative strategies with similar beneficial effects as physical exercise are needed. Two such strategies could be respiratory muscle endurance training (RMET) and intermittent hypoxia (IH). The main goals of this thesis were twofold: to determine whether an acute bout of evening exercise compromises sleep and to test the acute and long term effects of RMET with and without IH on BP, sleep, pulmonary function and exercise capacity in healthy normotensive and prehypertensive elderly. To do so, we first performed a systematic review and meta-analysis including all studies that investigated the effects of a single session of evening exercise on sleep compared to a no-exercise control condition. We found that evening exercise does not compromise sleep (in fact rather the opposite), except for late-night intense exercise ending ≤ 1 h before bedtime. Second, we recruited 14 prehypertensive but otherwise healthy elderly to test whether one session of intermittent RMET alone and in combination with IH would result in a transient decrease in BP and improve sleep. Contrary to our expectation, there was no decrease in BP after one acute session of intermittent RMET, and the effects on sleep were inconclusive. Further, the addition of IH did not have any additional effects on sleep and BP when compared to an acute bout of RMET alone. Finally, we recruited 24 healthy elderly to evaluate whether long term RMET, without the addition of IH, would result in lower resting BP, better sleep, improved pulmonary function and increased exercise performance. Participants in the RMET group performed on average 21 sessions of normocapnic hyperpnea over the course of 4-5 weeks whereas participants in the placebo group inhaled 20 times a lactose powder from a mock asthma inhaler. We found that only participants in the training group improved respiratory muscle endurance and whole body endurance performance. BP, sleep and other indices of pulmonary function were not improved after RMET compared to placebo. We conclude that RMET could be used as an adjunct to whole body exercise to improve respiratory and whole body exercise performance, although it is questionable whether this has practical applications given the absence of improvements in other health-related parameters that are known to worsen with age.

Since the Moon race in the 60s, human kind has continuously been orbiting Earth. However, before we can envision a permanent settlement on the Moon and explore our solar system, human physiology adaptation challenges need to be answered. Adequate sleep quantity and quality are required for good cognitive performances and chronic sleep restriction comes with a high cost. Sleep quality and sleep quantity are regulated by two interacting processes, the homeostatic and the circadian process. Electroencephalographic (EEG) theta activity (5-7Hz) during wakefulness reflects both the homeostatic and the circadian process. The circadian influence can be seen by a diurnal oscillation of theta activity. The homeostatic component, on the other hand, builds up with the time awake. Theta activity is therefore considered a sleep pressure marker and was associated with alertness and subjective daytime sleepiness. Intracranial recordings in rats showed that an increase of sleep pressure was also linked to neuronal "off" periods during wakefulness, similar to what can be recorded during slow waves sleep. These local sleep-like events during wakefulness have also been studied in the human EEG as markers of sleep pressure and widespread local sleep-like events are thought to be responsible for the decrease in cognitive performances under high sleep pressure conditions. Sleep quality and quantity in space will be key for maintaining astronaut’s cognitive functions and improving missions’ success rate. Even though astronauts are allocated enough time to sleep, a decrease of sleep quantity was reported on the International Space Station (ISS). Furthermore, for proper dissipation of sleep pressure, the quality of sleep is also important. In space, sleep quality might be impacted by external factors such as microgravity, isolation, confinement, circadian misalignment, chronic stress, temperature, light and noise disturbances. Besides space missions, analogue missions are opportunities to study human acclimatisation to space-like environment. Concordia station in Antarctica is one of the most remote human outpost on Earth. Studies conducted in Antarctica suggested that isolation, high altitude and constant darkness might disturb sleep in a similar fashion as on the ISS. In this thesis we investigated sleep pressure markers on the ISS. Then, to disentangle the effects of space environmental factors, we studied sleep pressure markers during a space analogue mission on Earth. Additionally, we studied sleep pressure's impact on cognitive performances and we explored novel countermeasures to enable human deep space travel. In this regard, we subdivided our work into three lines of research with three associated research papers.

Investigation of the influence of reward and reward-related cues on behaviour has a longstanding tradition in animal research and dates back to typical Pavlovian and operant conditioning experiments from famous behaviourists such as Thorndike, Skinner and Pavlov. However, recent developments in neuroimaging (i.e. new imaging and analysis techniques) and new concepts from neuroeconomics and decision making have led to the field’s rise in popularity in human neuroscience. This thesis investigated how reward and reward-predicting cues influence: 1) human motor behaviour / control and 2) goal-directed / motivated behaviour. Understanding the influence of reward on these behavioural domains will help develop our understanding of psychiatric diseases characterised by impaired reward and / or learning processes (i.e. autistic spectrum disorder, addictive behaviour), and improve motor performance in sports or rehabilitation. The first study investigated how reward can be used to modulate a phenomenon called motor slowing (i.e. decrease / slowing in maximal finger tapping speed over time). Behavioural data were combined with neuroimaging data (electroencephalography (EEG), functional magnetic resonance imaging (fMRI)) to establish the neurophysiological correlates / markers of this phenomenon. We show that reward decreases motor slowing significantly by increasing neural activity within the motor network. These findings stress the strong link between the reward and motor system, putatively via a dopaminergic pathway. The second study investigated the influence of reward-predicting cues on goal-directed behaviour by using an experimental paradigm called Pavlovian-to-instrumental transfer (PIT). Multiple types of reward, such as money, food, or social approval, are capable of driving human behaviour. However, most previous investigations have only focused on one of these reward classes in isolation, and even fewer have equated the value of different reward classes. Therefore it is not clear whether different reward classes have a unique influence on behaviour or whether the subjective value of the reward, rather than reward type per se, is most important for driving behaviour. Our findings suggest that individually matched monetary, food and social rewards are equally effective as appetitive reinforcers. These findings strengthen the hypotheses that subjective value is crucial for determining how much reward-related stimuli influence behaviour. In a third study we apply a similar experimental paradigm (i.e. PIT) to a clinical population, and additionally measure the participant’s eye movements. Obese individuals have been shown to exhibit abnormal sensitivity to rewards and reward-predicting cues, such as food-associated cues frequently used in advertisements. It has also been shown that food-associated cues can increase goal-directed behaviour but it is unknown whether this effect differs between normal-weight, overweight, and obese individuals. Our results suggest that overweight individuals are more susceptible to food-related cues than normal-weight controls and obese individuals. These findings might also have clinical implications, for example, in targeting overweight individuals with a behavioural therapy (e.g. extinction training, attentional control training, response training). Finally, we discuss the practical relevance of our results and suggest future directions for the two lines of research. To conclude, rewards and reward-predicting cues strongly influence human motor behaviour / control and goal-directed / motivated behaviour, which makes it relevant for practical applications and further basic / translational research., Forschung zum Einfluss von Belohnungen und Hinweisen, die mit Belohnungen assoziiert werden, haben eine lange Tradition. Diese reicht bis zu den klassischen Lernexperimenten (d.h. Pavlovsche und instrumentelle Konditionierung) von den berühmten Verhaltensforschern Thorndike, Skinner und Pavlov. Neuste Errungenschaften im Bereich der neurowissenschaftlichen Methoden und Analysetechniken sowie Konzepte aus der Neuroökonomie haben dieses Forschungsfeld auch am Menschen sehr populär gemacht. Diese Doktorarbeit untersucht wie Belohnungen und mit Belohnung assoziierte Hinweise das menschliche, motorische und zielgerichtete Verhalten beeinflussen. Dies ist möglicherweise relevant um psychische Krankheiten, die durch gestörte Belohnungs- oder Lernprozesse charakterisiert sind (z.B. Autismus, Suchterkrankungen) besser zu verstehen. Zudem können durch die Forschungsergebnisse die Bewegungsleistungen im Sport oder in der Rehabilitation positiv beeinflusst werden. In einer ersten Studie untersuchten wir einerseits, wie Belohnung eingesetzt werden kann um die sogenannte motorische Verlangsamung (d.h. mit der Zeit langsameres maximales Fingertippen) zu verringern. Andererseits suchten wir anhand funktioneller Magnetresonanztomografie (fMRT) und Elektroenzephalografie (EEG) die dazugehörigen neurologischen Korrelate / Erkennungszeichen. Wir zeigen, dass Belohnung die motorische Verlangsamung signifikant reduziert indem die neuronale Aktivität im motorischen System erhöht wird. Diese Resultate heben den Zusammenhang zwischen dem Belohnungs- und Bewegungssystem vermutlich durch dopaminerge Leitungsbahnen hervor. In einer zweiten Studie untersuchten wir den Einfluss von belohnungsassoziierten Hinweisen auf das zielgerichtete Verhalten anhand eines experimentellen Paradigmas, genannt Pavlovscher-instrumenteller Transfer (PIT). Verschiedene Belohnungstypen wie Geld, Nahrung oder soziale Bestätigung sind imstande, das menschliche Verhalten zu beeinflussen. Frühere Studien haben sich dennoch nur auf einen Belohnungstyp fokussiert oder die Belohnungstypen nicht ausgeglichen. Deshalb ist immer noch unklar, ob verschiedene Belohnungstypen einen speziellen Einfluss auf das Verhalten haben oder ob eher der subjektive Wert der Belohnung wichtig ist, um das Verhalten zu beeinflussen. Unsere Ergebnisse zeigen, dass alle individuell angepassten Belohnungstypen (d.h. Geld, Nahrung, soziale Bestätigung) gleich effektive positive Verstärker sind. Sie festigen die Hypothese, dass der subjektive Belohnungswert sehr wichtig dafür ist, wie stark belohnungsassoziierte Hinweise das Verhalten beeinflussen. In einer dritten Studie wandten wir ein gleiches experimentelles Paradigma (d.h. PIT) wie in der zweiten Studie an, dieses Mal jedoch auf eine klinische Population. Zusätzlich massen wir die Augenbewegungen der Studienteilnehmenden. Es wurde früher gezeigt, dass adipöse Personen eine abnormale Sensitivität gegenüber Belohnungen und belohnungsassoziierten Hinweisen haben (wie z.B. Werbung). Es wurde auch nachgewiesen, dass solche nahrungsassoziierten Hinweise zielgerichtetes Verhalten beeinflussen können. Es ist jedoch unklar, ob sich dieser Effekt zwischen normalgewichtigen, übergewichtigen und adipösen Personen unterscheidet. Unsere Ergebnisse zeigen, dass übergewichtige Personen empfindlicher auf nahrungsassoziierte Hinweise reagieren als normalgewichtige und adipöse Personen. Diese Resultate haben auch eine klinische Relevanz, wobei besonders übergewichtige Personen als Zielgruppe für Verhaltenstherapie interessant sein könnten (z.B. Auslöschungstraining, Aufmerksamkeitskontrolltraining, Reaktionstraining). Abschliessend diskutieren wir die praktische Relevanz unserer Resultate und schlagen eine zukünftige Ausrichtung der beiden Forschungsfelder vor. Belohnungen und belohnungsassoziierte Hinweise beeinflussen das motorische und zielgerichtete Verhalten des Menschen sehr stark, was es für praktische Anwendungen aber auch für weitere Grundlagen- und translatorische Forschung relevant macht.

Multivariate decoding methods have revolutionized cognitive neuroimaging in recent years by enabling the extraction of spatially distributed neuronal responses not accessible to traditionally used univariate methods. Importantly, in addition to providing increased analytical sensitivity, these new approaches have also led to fundamental neuroscientific paradigm shifts. The possibility to extract spatially distributed neuronal information for instance has fortified the proposition that cortical function is not organized in an exclusively modular fashion. The options to analyze individual subject data and quantify neuronal information content based on pattern dissimilarities have further paved the way for new neuroscientific questions. We make use of these new possibilities and combine multivariate methods, such as classifiers from Machine Learning (ML) or Representational Similarity Analysis (RSA), with traditional univariate approaches to address open questions within three research areas in cognitive neuroimaging. In the first research topic, we assess the potential of classification methods from ML to advance clinical diagnosis of psychiatric disorders based on multi-site resting-state functional magnetic resonance imaging (RS-fMRI) data. Conventional diagnostic approaches face a variety of challenges as they commonly require a team of specialists and a battery of behavioral tests. This approach is often costly and time consuming, with the potential to deliver ambiguous results. The ability of ML classifiers to extract distributed neuronal information from RS-fMRI data promises to advance the establishment of biomarkers underlying psychiatric disorders, since such disorders commonly affect cortical structure and function in a global manner. With Autism Spectrum Disorders as an example, we ask how accurately ML classifiers can make diagnostic predictions based on RS-fMRI data, assess a variety of auxiliary methods from ML which can increase diagnostic sensitivity, and investigate how remaining caveats can be addressed. In the second research topic, we assess the effect of expectation on somatosensory processing based on behavioral and fMRI data. It has been previously shown that expectation dampens the mean BOLD signal while concurrently improving behavioral dissociation performance. The underlying neuronal mechanisms leading to this seemingly contradictory effect are, however, still under debate. In accordance with previous studies, we ask if expectation recruits fewer neuronal units, that specialize in encoding the expected stimuli with high selectivity. This would imply increased signal-to-noise ratio in favor of the expected stimuli, and could explain the decrease in mean BOLD signal associated with behavioral improvements. Multivariate decoding methods allow us to empirically test this hypothesis, as an increase in signal-to-noise ratio should improve the decoding of neuronal activity patterns associated with expected stimuli. The decision outcome of classifiers can be matched to the behavioral decisions of individual subjects. This allows us to connect the two experimental levels for a systematic explanation of the observed effects induced by expectation. In a third research topic, we turn our attention to Brain-Computer Interface (BCI) technology, which promises to pave the way for assistive devices or for devices employed in therapeutic settings. In order to optimise future BCI technology, more reliable read-outs of neuronal states are necessary to provide a basis for the control of external devices. We ask if ML classifiers can reliably predict the up- and down-regulation of motor excitability based on individual subject electroencephalography (EEG) measurements. In a rst step, subjects learn within a neurofeedback paradigm to attain the desired motor states. This is accomplished with a new protocol, where subjects are trained to modulate their motor states through real-time visual feedback of motor evoked potential (MEP) amplitude in response to transcranial magnetic stimulation (TMS). Once subjects learn a robust regulation of their motor excitability, EEG data associated with both states is acquired. Based on these EEG measurements, we assess the capability of Machine Learning classifiers to predict the motor states. In addition, we employ feature selection techniques to assess which components of the EEG signal are most relevant for the prediction. Feature selection can aid robust prediction, and promises to elucidate underlying neuronal mechanisms associated with the up- and down-regulation of the motor system. The capability of Machine Learning methods to draw inference from single subject data and based on only a few trials promises to enable real-time BCIs tailored to the needs of individual subjects. In summary, the three research projects presented in this thesis show how the application of multivariate decoding analysis can lead to fundamental neuroscientific insights which provide a basis for practical applications and a better understanding of the mechanisms underlying sensory processing.

Multimodal imaging based on simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a viable approach for investigating human brain function. EEG provides a direct measure of oscillatory electrophysiological activity, which originates from the firing of cortical neurons. It has high temporal resolution, on the scale of milliseconds. fMRI has proved to be very accurate in displaying brain activations with a spatial resolution of a few millimeters. It detects the slow hemodynamic fluctuations, which are measured using the Blood Oxygenation Level Dependent (BOLD) contrast, and are only indirectly associated with neuronal activity. Accordingly, the integration of EEG and fMRI allows the visualization of the same phenomenon, the brain activation, through two different spatial-temporal windows of analysis, each of them able to show particular features. Though, the EEG-fMRI integration is methodologically challenging, as it may compromise data quality and raise concerns on subject safety. Growing efforts have been made to tackle these challenges, resulting in the introduction of specifically magnetic resonance (MR)-compatible designed EEG instrumentation, and the development of more and more advanced techniques for dealing with artifactual sources. Despite consistent improvements over the years, the EEG signals recorded during simultaneous fMRI scanning are still contaminated by strong artifacts, induced by the interactions between the MR environment, the EEG equipment and the participant. For an accurate characterization of the measured brain signals, they should be removed before any further analysis. The gradient artifact, generated by the fMRI acquisition process, has a massive effect, but can be relatively easily removed due to its high reproducibility. Gradient artifact aside, the EEG recordings are still heavily corrupted by the presence of the ballistocardiographic (BCG) artifact, which is associated with the ongoing cardiac activity of the participant. Despite some methods to remove the BCG exist, this processing step is very challenging due to the complex BCG spatio-temporal dynamics. Once EEG data are cleaned from the MR-related artifacts, they are given as an input for conventional, out of MR scanner, EEG analyses. This includes further pre-processing steps and, eventually, EEG source localization. For the latter, the major issue raises from the definition of the volume conduction model, constructed by the integration of information about the subject’s head anatomy, tissues biophysical, e.g. electrical and physical, properties, and position of the EEG sensors over the scalp. This model is meant to theoretically establish how brain sources can generate specific distributions of EEG potentials, and its accuracy is strongly influenced by the correctness of the information given in input. Thus, the availability of clean EEG data and the definition of a reliable volume conduction model are essential requirements for accurate EEG neural sources imaging. Once EEG data are cleaned from the MR-related artifacts, they are given as an input for conventional, out of MR scanner, EEG analyses. This includes further pre-processing steps and, eventually, EEG source localization. For the latter, the major issue raises from the definition of the volume conduction model, constructed by the integration of information about the subject’s head anatomy, tissues biophysical, e.g. electrical and physical, properties, and position of the EEG sensors over the scalp. This model is meant to theoretically establish how brain sources can generate specific distributions of EEG potentials, and its accuracy is strongly influenced by the correctness of the information given in input. Thus, the availability of clean EEG data and the definition of a reliable volume conduction model are essential requirements for accurate EEG neural sources imaging.

Emerging evidence indicates that age-related decline in higher order cognitive processing, e.g. attention and executive functioning, is associated with impaired gait and is important in relation to falls in older adults (Yogev-Seligmann et al., 2008; de Bruin and Schmidt, 2010; Mirelman et al., 2012). There are strong indications that the most important risk factors for cognitive decline, dementia, impaired gait, and falls in older adults are interconnected and are modifiable through physical activity and training as well as partly through cognitive training (Stenhagen et al., 2013; Baumgart et al., 2015; Hortobagyi et al., 2015; Van Abbema et al., 2015; Liu et al., 2016). However, since to date, to the best of our knowledge, no interventions have studied synergistic or cumulative effects from multicomponent physical exercise programs with additional cognitive training to improve cognitive performance, brain function, gait, and prevent falls. Moreover, the neurophysiological mechanisms mediating the effects of physical training on cognition and brain function in older adults remain unclear. Therefore, the aim of this thesis is to illuminate the effects of interactive simultaneous cognitive–motor training modalities on cognitive and brain function, cognitive–motor dual-task walking, and fall prevention in older adults. Study 1 (chapter 3) addresses the question of how good the cognitive and physical fitness status of Swiss older adults, as assessed with cognitive–motor dual-task gait speed measurements, is in relation to the requirements that are necessary to stay independent as a pedestrian in an urban environment. This cross-sectional study with 120 participants establishes the relevance of investigating effective training interventions for older adults, which are in the focus of the subsequent interventional studies 2a/b and 3. Thus, as a second step, a 6-month longitudinal training intervention study with a 1-year follow-up is performed, including 89 participants, to investigate both broad cognitive (study 2a, chapter 4) and physical adaptations, including dual-task gait measures and fall frequency (study 2b, chapter 5). Finally, in a third step, a shorter 8 weeks lasting training intervention study is conducted, including 42 participants, to address the question if the training-induced cognitive behavioral adaptations, that were observed in study 2a, would be reflected in brain functional adaptations in older adults (study 3, chapter 6). The main findings from study 1 include that about every third (35.6%) older person at the age of 70–79 years and almost three-quarters (73.8%) of persons ≥80 years cannot walk faster than 1.2 m/s, which is required to cross streets safely within the green–yellow phase of pedestrian lights, under cognitively challenging conditions. Study 2a demonstrates, first, that the two interactive simultaneous cognitive–motor programs are partially advantageous to boost performance in two measures of executive function (switching attention and working memory) compared to an exclusively physical training program; and second, that cognitive performance, including executive functions, long-term visual memory (episodic memory), and processing speed, is maintained until 1-year follow-up after all three interventions. Study 2b shows, first, that the two interactive simultaneous cognitive–motor programs result in a significant advantage in dual-task costs of walking compared to the exclusively physical program but not in any other gait variables; second, that the two simultaneous cognitive–motor interventions lead to different training-specific adaptations in the rhythm and variability domains of gait; and third, that each of the three training programs very effectively reduced fall frequency for ~77%. Finally, Study 3 reports, first, that both the video game dancing and the balance interventions reduce left and right hemispheric prefrontal cortex (PFC) oxygenation during the acceleration of walking, while video game dancing showed a larger reduction at the end of the walking phase compared to balance training in the left PFC; and second, that the exercise training-induced modulations in PFC oxygenation are associated with improved executive functions. The main conclusions from this thesis imply that the fitness status of many older adults is not appropriate to safely encounter the requirements for pedestrians in urban areas, which reinforces the need for regular cognitive and physical training in the older population (study 1). Interactive simultaneous cognitive–motor training should be integrated in training programs aiming to improve cognition, gait performance, physical functioning, and reduce fall frequency in older persons. Such programs may potentially counteract the large prevalence of cognitive and gait impairments, as well as reduce fall fre- quency, inherently leading to more independence and a better quality of life (studies 2a/b). Finally, training-induced brain functional adaptations in the PFC seem to reduce the need of prefrontal resources of executive function and attention involved in challenging treadmill walking. This effect may liberate cognitive resources to focus on other processes while walking in attention demanding real-life situations such as crossing streets or walking while talking and could potentially reduce the risk of falling (study 3).