本文選題：功能磁共振成像　切入點(diǎn)：靜息態(tài)　出處：《西安電子科技大學(xué)》2012年碩士論文

【摘要】：功能磁共振成像(functional Magnetic Resonance Imaging, fMRI)技術(shù)因其擁有較高的空間分辨率、時(shí)間分辨率、無(wú)輻射損傷以及可在活體上重復(fù)進(jìn)行檢測(cè)等優(yōu)勢(shì)，已成為當(dāng)今用于腦功能研究的主要技術(shù)。近年來(lái)的研究表明人腦在靜息態(tài)時(shí)仍然存在著明顯的活動(dòng)，能否快速、準(zhǔn)確的獲得這些活動(dòng)的過(guò)程、規(guī)律，靜息態(tài)fMRI數(shù)據(jù)分析方法起著至關(guān)重要的作用。 以往大多數(shù)基于靜息態(tài)腦功能連接度的研究都要假設(shè) 時(shí)不變‖，例如相關(guān)分析和一些數(shù)據(jù)驅(qū)動(dòng)的方法。然而基于任務(wù)的研究和動(dòng)物電氣生理學(xué)研究都表明功能連接存在動(dòng)態(tài)、瞬時(shí)的變化�；诖�，本文引進(jìn)了一種時(shí)頻特性方法——小波變換來(lái)探索靜息態(tài)功能連接的這種動(dòng)態(tài)變化行為。本文的主要研究區(qū)域有后扣帶回(posterior cingulated cortex, PCC)、靜息態(tài)默認(rèn)網(wǎng)絡(luò)中一些重要結(jié)點(diǎn)腦區(qū)以及激活較為明顯的一些負(fù)相關(guān)區(qū)域。 本文首先對(duì)靜息態(tài)功能磁共振成像數(shù)據(jù)處理流程做了詳細(xì)的介紹，包括數(shù)據(jù)預(yù)處理和一些常用的計(jì)算；其次介紹了靜息態(tài)功能連接性常用分析方法，包括局部一致性分析、種子點(diǎn)相關(guān)分析、獨(dú)立成分分析、時(shí)間聚類分析；再次用小波變換方法分析靜息態(tài)fMRI數(shù)據(jù)，分別做了連續(xù)小波變換、正交小波變換以及相干小波變換。最終三種變換的結(jié)果都表明大腦在靜息態(tài)時(shí)的主要活動(dòng)頻率在1/32Hz~1/16Hz,這與以往的研究結(jié)果吻合。相干小波變換的結(jié)果表明在1/4Hz時(shí)PCC與其它10個(gè)腦區(qū)的變化最為相似。另外，除了以往的靜息態(tài)默認(rèn)網(wǎng)絡(luò)外，PCC與R.DLPFC、R.insula、R.SMG等幾個(gè)負(fù)相關(guān)比較大的區(qū)域也有明顯的相似性。
[Abstract]:Functional Magnetic Resonance imaging (fMRI) has the advantages of high spatial resolution, temporal resolution, no radiation damage and repeated detection in vivo. Has become the main technology for brain function research. Recent studies have shown that there are still obvious activities in the resting state of the human brain, whether the processes and rules of these activities can be obtained quickly and accurately. The static fMRI data analysis method plays an important role. Most previous studies based on resting brain functional connectivity have assumed that time is constant. For example, correlation analysis and some data-driven methods. However, task-based studies and animal electrophysiological studies have shown that functional connections have dynamic, instantaneous changes. In this paper, a time-frequency characteristic method, wavelet transform, is introduced to explore the dynamic behavior of static functional connections. The main research areas in this paper are posterior cingulate cingulated cortexes, PCCs, and some important nodes in resting default networks. Brain area and activation of some of the more obvious negative correlation areas. In this paper, the data processing flow of resting functional magnetic resonance imaging (fMRI) is introduced in detail, including data preprocessing and some commonly used calculations, and then the commonly used analysis methods of resting functional connectivity, including local consistency analysis, are introduced in detail. Seed point correlation analysis, independent component analysis, time clustering analysis, wavelet transform method is used to analyze resting fMRI data. The results of orthogonal wavelet transform and coherent wavelet transform show that the main frequency of brain activity in resting state is 1 / 32 Hz / 1 / 16 Hz, which is consistent with previous results. The results of coherent wavelet transform show that PCC in 1/4Hz. Most similar to the other 10 brain regions. In addition, In addition to the previous resting default networks, there are obvious similarities between PCC and R. DLPFCU R. Peninsula R. SMG and other regions with relatively large negative correlation.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：R310

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本文編號(hào)：1691101