18 resultados para Anatomical brain connectivity
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Structural connectivity models based on Diffusion Tensor Imaging (DTI) are strongly affected by the technique’s inability to resolve crossing fibres, either intra- or inter-hemispherical connections. Several models have been proposed to address this issue, including an algorithm aiming to resolve crossing fibres which is based on Diffusion Kurtosis Imaging (DKI). This technique is clinically feasible, even when multi-band acquisitions are not available, and compatible with multi-shell acquisition schemes. DKI is an extension of DTI enabling the estimation of diffusion tensor and diffusion kurtosis metrics. In this study we compare the performance of DKI and DTI in performing structural brain connectivity. Six healthy subjects were recruited, aged between 25 and 35 (three females). The MRI experiments were performed using a 3T Siemens Trio with a 32-channel head coil. The scans included a T1-weighted sequence (1mm3), and a DWI with b-values 0, 1000 and 2000 s:mm
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Dissertation presented at the Faculty of Science and Technology of the New University of Lisbon in fulfillment of the requirements for the Masters degree in Electrical Engineering and Computers
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The computations performed by the brain ultimately rely on the functional connectivity between neurons embedded in complex networks. It is well known that the neuronal connections, the synapses, are plastic, i.e. the contribution of each presynaptic neuron to the firing of a postsynaptic neuron can be independently adjusted. The modulation of effective synaptic strength can occur on time scales that range from tens or hundreds of milliseconds, to tens of minutes or hours, to days, and may involve pre- and/or post-synaptic modifications. The collection of these mechanisms is generally believed to underlie learning and memory and, hence, it is fundamental to understand their consequences in the behavior of neurons.(...)
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Dissertação apresentada na Faculdade de Ciências e Tecnologiea da Universidade Nova de Lisboa, para obtenção do Grau de Mestre em Engenharia Biomédica
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Spontaneous Generations 1:1 (2007)
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Dissertation submitted in Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the degree of Master in Biomedical Engineering
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Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina
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Dissertation presented to obtain the Ph.D degree in Biology
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Based on the report for the “Project III” unit of the PhD programme on Technology Assessment under the supervision of Prof. António B. Moniz. This report was discussed also at the 2nd Winter School on Technology Assessment held at Universidade Nova de Lisboa, Caparica Campus, Portugal on December 2011.
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Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Armin Grunwald (Karlsruhe Institute of Technology-ITAS, Germany). Other members of the thesis committee are Mário Forjaz Secca (FCT-UNL) and Femke Nijboer (University of Twente, Netherlands).
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Dissertação apresentada para a obtenção do Grau de Mestre em Genética Molecular e Biomedicina, pela Universidade N ova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertation submitted in Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the degree of Master of Biomedical Engineering
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Fundação para a Ciência e a Tecnologia - SFRH/BD/42848/2008, através do Programa MIT_Portugal em Sistemas de Bioengenharia; projectos PTDC/SAUNEU/104415/2008 e Projecto ref. 96542 da Fundação Caloust Gulbenkian
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Dissertation presented to obtain the Ph.D degree in Biology, Neuroscience
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Dissertation presented to obtain the Ph.D degree in Biology, Neuroscience