Browsing by Subject "Magnetoencephalography"

Now showing 1 - 4 of 4
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    BEHAVIORAL AND NEURAL MECHANISMS UNDERLYING SPATIAL EXPLORATION AND DECISION
    (2014-06) Sakellaridi, Sofia
    The ability to explore novel environments and make decisions is a fundamental component of human and animal behavior. Even though significant progress has been made in recent years in understanding the mechanisms of exploration and decision-making, little is known on how the brain extracts, encodes and processes information from the environment to make decisions. The primary goal of this thesis is to understand the behavioral and neural mechanisms underlying the processing of spatial information, acquired during exploration of realistic environments to make spatial decisions. We designed a novel task, in which subjects had to explore maps from various U.S. cities to decide where to build a City Hall, while neuromagnetic fluxes were recorded from their heads using a whole-head MEG device. We found that ongoing neuronal activity in a network of cortical regions was associated with particular spatial parameters of the city maps. This network involved predominantly the right frontal and prefrontal areas of the brain, suggesting that these areas have an important role in processing spatial information for making decisions. Additionally, we found other brain areas that were also involved in the processing of spatial information, such as right temporal areas and the cerebellum. These results indicate that processing spatial information for making a decision is a complex process that requires the involvement of more than one regions. Finally, we found that the associations between changes in the ongoing neural activity and spatial parameters were modulated by the street network type. This suggests that, depending on the type of street network, people may use different spatial information to explore the map and make a spatial decision.We also studied how people make spatial decisions in realistic environments when they were forced to select between a limited set of choices. In this experiment, individuals had to explore maps from various U.S. cities, but now to select between two locations to build a hypothetical Post Office. We recorded subjects' eye positions and analyzed the gaze behavior to characterize how people explored maps to select between these options. We found that subjects were continuously exploring the areas around the two options and the center of the map, by looking back and forth between them before making a decision. Unlike economic choices, in which people follow similar strategies by looking repeatedly at the available options, in our experiment individuals were also exploring the area around the center of the map. These findings suggest that the subjects might have mentally placed themselves at the center of the map and evaluated the alternative options with respect to their current location. We also found other similarities with economic choice paradigms, such as people spent more time exploring the area around the option ultimately chosen. Finally, subjects showed a strong bias to select the option they initially explored.
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    Characteristic information required for human motor control:Computational aspects and neural mechanisms.
    (2010-08) Christopoulos, Vassilios N.
    Motor behavior involves creating and executing appropriate action plans based on goals and relevant information. This information characterizes the state of environment, the task and the state of actions performed. The perceptual system gathers this information from different sources: touch, vision, audition, scent and taste. Despite the richness of environment and the sophistication of our sensory system, it is not possible to extract a complete and accurate representation of the required states for motor behavior because of noise and ambiguity. Consequently, people effectively have “limited information” and therefore may not be certain about the outcomes of specific actions. For motor behavior to be robust to uncertainty, the brain needs to represent both relevant states and their uncertainties, and it needs to build compensation for uncertainty into its motor strategy. Generating motor behavior requires the brain to convert goals and information into action sequences, and the flexibility of human motor behavior suggests that brain implements a complex control model. The primary goal of this work is to improve the characterization of this control model by studying motor compensation for uncertainty and determining the neural mechanisms underlying information processing and the control model. Part of this thesis focuses on studying human compensation strategies in natural tasks like grasping. We experimentally tested the hypothesis that people compensate for object position uncertainty by adopting strategies that minimize the impact of uncertainty in grasp success. As we hypothesized, we found that people compensate for object position uncertainty by approaching the object along the direction of maximal position uncertainty. Additionally, we modeled the grasping task within the optimal control framework and found that human strategies share many characteristics with optimal strategies for grasping objects with position uncertainty. We are also interested to understand how the brain encodes and processes information relevant to movements. To accomplish this, we studied the spatial and temporal interactions of cortical regions underlying continuous and sequential movements using magnetoencephalography (MEG). Particularly, we took data from a previous study, in which subjects continuously copied a pentagon shape for 45 s using an XY joystick. Using Box-Jenkins time series analysis techniques, we found that neural interactions and variability of movement direction are integrated in a feedforward-feedback scheme. MEG sensors related to feedforward scheme were distributed around the left motor cortex and the cerebellum, whereas sensors related to feedback scheme had a strong focus around the parietal and the temporal cortices.
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    A magnetoencephalographic (MEG) study of brain mechanisms in temporomandibular disorder.
    (2009-12) Alonso DDS, Aurelio Abdalla MS.
    The main goal of this study was to investigate, using MEG, the dynamic neural mechanisms underlying facial tactile stimulation in two groups of subjects, namely a control group (without pain) and a TMD pain group (arthromyalgia), by stimulating the facial skin with a non-painful air-driven plastic membrane. Our first specific aim was to investigate and compare the spatial and temporal features of the ECDs following innocuous tactile stimuli in both groups. And t he second specific aim was to investigate the differences in dynamic brain function between these two groups using a time-frequency analysis of the MEG data. In summary, innocuous tactile stimulation proved to be a successful way to measure brain spatio-temporal dynamics in two group population. We were able to demonstrate very clear the differences in brain organization and dynamics between these two groups using an innocuous stimulus and without causing an unpleasant feeling. The results obtained allow for a paradigm shift in future research of brain mechanisms in pain by the use of non-painful tactile stimuli to evaluate brain function in various orofacial (or other) pain conditions, including neurovascular and neuropathic pains and other complex orofacial pain disorders.
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    Melodies in space: neural processing of musical features
    (2013-03) Dumas, Roger Edward
    With modern digital technology, it is now possible to capture, store and describe the brain's response to musical stimuli with some degree of confidence. Increasing financial and materiel resources are being made available to music-brain researchers and, as a result, the number of music perception and cognition publications is expanding exponentially (Levitin & Tirovolas, 2011). Many neuro-musicologists have access to at least one of the two most popular brain-imaging technologies, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). EEG measures the electric brain signal passing through soft tissues, which becomes 'smeared' and difficult to separate from signals measured elsewhere on the scalp. fMRI measure the blood-oxygen level dependent (BOLD) signal, however this signal develops too slowly (2-5 seconds) to accurately capture the brain's swift processing of individual melodic notes. In contrast, magneto-encephalography (MEG) affords high temporal resolution (1 ms) and high fidelity (i.e. the clean, direct measurement of undistorted electromagnetic fluctuations in neural populations) and is therefore the most suitable method for matching the brain's dynamic, interacting sub-networks to the processing of melodies played at normal tempos. To explore my idea that this evolving process is both observable and quantifiable, I have performed a series of MEG experiments involving human subjects listening to melodic stimuli. This dissertation details my examination of the brain's response to melodic pitch, contour, interval distance and next-note probability.