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Electrophysiological neuroimaging: ...

Ding, Lei.

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Electrophysiological neuroimaging: New models and computational methods.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Electrophysiological neuroimaging: New models and computational methods./
作者:	Ding, Lei.
面頁冊數:	244 p.
附註:	Adviser: Bin He.
Contained By:	Dissertation Abstracts International68-02B.
標題:	Engineering, Biomedical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3252490

Electrophysiological neuroimaging: New models and computational methods.
Ding, Lei.

Electrophysiological neuroimaging: New models and computational methods. - 244 p.

Adviser: Bin He.

Thesis (Ph.D.)--University of Minnesota, 2007.

Electrophysiological neuroimaging has played a prominent role in neuroscience research and clinical practice. The major challenge this valuable non-invasive technology is facing, includes its limited spatial resolution, its resolvability of imaging complex neural activation patterns, and its limited ability in understanding communications between neuron populations.Subjects--Topical Terms:

1017684
Engineering, Biomedical.

Electrophysiological neuroimaging: New models and computational methods.
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245 1 0 $a Electrophysiological neuroimaging: New models and computational methods.
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500 $a Source: Dissertation Abstracts International, Volume: 68-02, Section: B, page: 1113.
502 $a Thesis (Ph.D.)--University of Minnesota, 2007.
520 $a Electrophysiological neuroimaging has played a prominent role in neuroscience research and clinical practice. The major challenge this valuable non-invasive technology is facing, includes its limited spatial resolution, its resolvability of imaging complex neural activation patterns, and its limited ability in understanding communications between neuron populations.
520 $a The present dissertation research aims at developing new methods for the electrophysiological neuroimaging by advancing forward models and inverse computational methods. The first part of this dissertation is to develop high spatial resolution inverse methods with enhanced neural source imaging performance for both discrete source reconstruction and distributed source reconstruction. The second part is to develop a novel low dimensional physiological realistic source model to represent extended neural activation in real stimuli or brain events. With new model developed, complex neural activation with multiple sources can be more accurately reconstructed and investigated. In the third part of this dissertation, it is to develop a new connectivity imaging technique with the outcome from neural source reconstruction. These techniques are the essential and integral elements of the electrophysiological neuroimaging with non-invasive EEG measurements. The dissertation also consists of the research studies concerning the clinical application of the electrophysiological neuroimaging on the non-invasive identification of epileptogenic zones in epilepsy patients. Our results obtained so far indicate that the electrophysiological neuroimaging based on EEG may provide important tools for non-invasive diagnosis of brain abnormalities, and may improve our understandings on the problems arising from neuroscience.
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