3 research outputs found

    Human motor augmentation - spinal motor neurons control of redundant degrees-of-freedom

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    In 1963, Stan Lee introduced a new villain to the Spiderman Universe: Dr Octopus – a human equipped with multiple robotic arms that can be controlled seamlessly in coordination with his natural limbs. Throughout the last decades, turning such fiction into real-life applications gave rise to the research field of human motor augmentation, ultimately aiming to enable humans to perform motor tasks that are sheer impossible with our natural limbs alone. While a significant process was made in designing artificial supernumerary limbs, a central problem remains: identifying adequate bodily signals that allow moving supernumerary degrees-of-freedom together with our natural ones. So far, neural activity in the brain seems to hold the greatest potential for providing all the flexibility needed to ensure such coordination between natural and supernumerary degrees-of-freedom. However, accessing neural populations in the cortical regions is accompanied by an unacceptable risk for most users. A different group of neural cells can be found in the outmost layer of the motor pathway, driving the contraction of muscles and generation of force – spinal motor neurons. The development of novel neural interfaces has made it possible to study single motor neuron activity with minimal harm to the user. This allows a direct and non-invasive window into the neural activity orchestrating human movement. In this dissertation, I investigate whether these neurons innervating our muscles could provide supernumerary control signals. The results indicate, in essence, that features extracted non-invasively from motor neuron activity have the potential to overcome current limitations in supernumerary control and thus could significantly advance human motor augmentation.Open Acces

    Reducing the Effect of Spurious Phase Variations in Neural Oscillatory Signals

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    The phase-reset model of oscillatory EEG activity has received a lot of attention in the last decades for decoding different cognitive processes. Based on this model, the ERPs are assumed to be generated as a result of phase reorganization in ongoing EEG. Alignment of the phase of neuronal activities can be observed within or between different assemblies of neurons across the brain. Phase synchronization has been used to explore and understand perception, attentional binding and considering it in the domain of neuronal correlates of consciousness. The importance of the topic and its vast exploration in different domains of the neuroscience presses the need for appropriate tools and methods for measuring the level of phase synchronization of neuronal activities. Measuring the level of instantaneous phase (IP) synchronization has been used extensively in numerous studies of ERPs as well as oscillatory activity for a better understanding of the underlying cognitive binding with regard to different set of stimulations such as auditory and visual. However, the reliability of results can be challenged as a result of noise artifact in IP. Phase distortion due to environmental noise artifacts as well as different pre-processing steps on signals can lead to generation of artificial phase jumps. One of such effects presented recently is the effect of low envelope on the IP of signal. It has been shown that as the instantaneous envelope of the analytic signal approaches zero, the variations in the phase increase, effectively leading to abrupt transitions in the phase. These abrupt transitions can distort the phase synchronization results as they are not related to any neurophysiological effect. These transitions are called spurious phase variation. In this study, we present a model to remove generated artificial phase variations due to the effect of low envelope. The proposed method is based on a simplified form of a Kalman smoother, that is able to model the IP behavior in narrow-bandpassed oscillatory signals. In this work we first explain the details of the proposed Kalman smoother for modeling the dynamics of the phase variations in narrow-bandpassed signals and then evaluate it on a set of synthetic signals. Finally, we apply the model on ongoing-EEG signals to assess the removal of spurious phase variations

    Neuroimaging of human motor control in real world scenarios: from lab to urban environment

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    The main goal of this research programme was to explore the neurophysiological correlates of human motor control in real-world scenarios and define mechanism-specific markers that could eventually be employed as targets of novel neurorehabilitation practice. As a result of recent developments in mobile technologies it is now possible to observe subjects' behaviour and monitor neurophysiological activity whilst they perform natural activities freely. Investigations in real-world scenarios would shed new light on mechanisms of human motor control previously not observed in laboratory settings and how they could be exploited to improve rehabilitative interventions for the neurologically impaired. This research programme was focussed on identifying cortical mechanisms involved in both upper- (i.e. reaching) and lower-limb (i.e. locomotion) motor control. Complementary results were obtained by the simultaneous recordings of kinematic, electromyographic and electrocorticographic signals. To study motor control of the upper-limb, a lab­based setup was developed, and the reaching movement of healthy young individuals was observed in both stable and unstable (i.e. external perturbation) situations. Robot-mediated force-field adaptation has the potential to be employed in rehabilitation practice to promote new skills learning and motor recovery. The muscular (i.e. intermuscular couplings) and neural (i.e. spontaneous oscillations and cortico­muscular couplings) indicators of the undergoing adaptation process were all symbolic of adaptive strategies employed during early stages of adaptation. The medial frontal, premotor and supplementary motor regions appeared to be the principal cortical regions promoting adaptive control and force modulation. To study locomotion control, a mobile setup was developed and daily life human activities (i.e. walking while conversing, walking while texting with a smartphone) were investigated outside the lab. Walking in hazardous environments or when simultaneously performing a secondary task has been demonstrated to be challenging for the neurologically impaired. Healthy young adults showed a reduced motor performance when walking in multitasking conditions, during which whole-brain and task-specific neural correlates were observed. Interestingly, the activity of the left posterior parietal cortex was predictive of the level of gait stability across individuals, suggesting a crucial role of this area in gait control and determination of subject specific motor capabilities. In summary, this research programme provided evidence on different cortical mechanisms operative during two specific scenarios for "real­world" motor behaviour in and outside the laboratory-setting in healthy subjects. The results suggested that identification of neuro-muscular indicators of specific motor control mechanisms could be exploited in future "real-world" rehabilitative practice
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