Search for dissertations about: "fMRI"

Showing result 1 - 5 of 121 swedish dissertations containing the word fMRI.

  1. 1. fMRI for mapping the plastic somatotopy of primary somatosensory cortex - Development and clinical applications

    Author : Andreas Weibull; Malmö Medicinsk strålningsfysik; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; smoothing; physiological noise; spatial resolution; primary somatosensory cortex; cortical reorganisation; brain plasticity; fMRI; partial volume effects;

    Abstract : Functional magnetic resonance imaging (fMRI) is a widely used tool for studying brain function in vivo. The technique is based on acquiring brain images sensitive to the physiological response following neural activation, and hence, allows brain activity to be examined and documented. READ MORE

  2. 2. Advanced clinical MRI for better outcome in epilepsy surgery. Focusing on fMRI and prediction of verbal memory decline

    Author : Maria Strandberg; Lund Neurologi; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; 3T MRI; surface coils; epilepsy surgery; fMRI; TLE; lateralization index; MTL; verbal encoding;

    Abstract : Abstract Aim: The aim of the thesis was to evaluate the use of advanced MRI technology to improve results of epilepsy surgery, with focus on language and memory functions. Methods: In paper I, 25 patients with drug-resistant epilepsy were retrospectively included in the study for having been referred to high resolution 3T MRI with and without surface coils. READ MORE

  3. 3. Scalable Bayesian spatial analysis with Gaussian Markov random fields

    Author : Per Sidén; Mattias Villani; Anders Eklund; Håvard Rue; Linköpings universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Spatial statistics; Bayesian statistics; Gaussian Markov random fields; fMRI; Machine learning; Spatial statistik; Bayesiansk statistik; Gaussiska Markov-fält; fMRI; Maskininlärning;

    Abstract : Accurate statistical analysis of spatial data is important in many applications. Failing to properly account for spatial autocorrelation may often lead to false conclusions. READ MORE

  4. 4. Human brains and virtual realities : Computer-generated presence in theory and practice

    Author : Daniel Sjölie; Lars-Erik Janlert; Johan Eriksson; Giuseppe Riva; Umeå universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Human brain function; virtual reality; presence; cognitive neuroscience; human-computer interaction; brain imaging; fMRI; BCI; neural correlates; HCI theory; reality-based interaction.;

    Abstract : A combined view of the human brain and computer-generated virtual realities is motivated by recent developments in cognitive neuroscience and human-computer interaction (HCI). The emergence of new theories of human brain function, together with an increasing use of realistic human-computer interaction, give reason to believe that a better understanding of the relationship between human brains and virtual realities is both possible and valuable. READ MORE

  5. 5. Machine learning for identification of brain activity patterns with applications in gentle touch processing

    Author : Malin Björnsdotter Åberg; Göteborgs universitet; Göteborgs universitet; Gothenburg University; []
    Keywords : Somatosensory; Machine learning; Pattern recognition; fMRI; Support vector machines; Neuroscience; Brain; BOLD; Signal processing; Artificial intelligence; Touch; Human; Unmyelinated; Sensory; Affective;

    Abstract : Since the first mention of artificial intelligence in the 1950s, the field of machine learning has provided increasingly appealing tools for recognition of otherwise unintelligible pattern representations in complex data structures. Human brain activity, acquired using functional magnetic resonance imaging (fMRI), is a prime example of such complex data where the utility of pattern recognition has been demonstrated in a wide range of studies recently (Haynes et al. READ MORE