Comput Math Methods Med - Functional magnetic resonance imaging for imaging neural activity in the human brain: the annual progress.

Tópicos

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{ research(1085) discuss(1038) issu(1018) }
{ can(981) present(881) function(850) }
{ data(1737) use(1416) pattern(1282) }
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{ imag(1057) registr(996) error(939) }
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Resumo

Functional magnetic resonance imaging (fMRI) is recently developed and applied to measure the hemodynamic response related to neural activity. The fMRI can not only noninvasively record brain signals without risks of ionising radiation inherent in other scanning methods, such as CT or PET scans, but also record signal from all regions of the brain, unlike EEG/MEG which are biased towards the cortical surface. This paper introduces the fundamental principles and summarizes the research progress of the last year for imaging neural activity in the human brain. Aims of functional analysis of neural activity from fMRI include biological findings, functional connectivity, vision and hearing research, emotional research, neurosurgical planning, pain management, and many others. Besides formulations and basic processing methods, models and strategies of processing technology are introduced, including general linear model, nonlinear model, generative model, spatial pattern analysis, statistical analysis, correlation analysis, and multimodal combination. This paper provides readers the most recent representative contributions in the area.

Resumo Limpo

function magnet reson imag fmri recent develop appli measur hemodynam respons relat neural activ fmri can noninvas record brain signal without risk ionis radiat inher scan method ct pet scan also record signal region brain unlik eegmeg bias toward cortic surfac paper introduc fundament principl summar research progress last year imag neural activ human brain aim function analysi neural activ fmri includ biolog find function connect vision hear research emot research neurosurg plan pain manag mani other besid formul basic process method model strategi process technolog introduc includ general linear model nonlinear model generat model spatial pattern analysi statist analysi correl analysi multimod combin paper provid reader recent repres contribut area

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