應用動態因素分析探索語言網絡: 靜息態近紅外線腦血流分析

Exploring the Language Network Using Dynamic Factor Analysis: A Resting-State Near-Infrared Spectroscopy Study

黃慶峯(Ching-Feng Huang)

指導教授 ： 陳欣進

國立中正大學/社會科學院/心理學系/碩士(2012年)

摘要

目前對於語義整合所涉及的大腦區域尚無定論。過去普遍使用作業誘發反應所激發的大腦區域來推論其功能上的定位，然而這種區域定位理論低估了不同的大腦區域間既存的內在功能性整合。靜息態功能性連結表示在無外來刺激下空間上遙距的神經元自發性活動的同步性。靜息態功能性連結意味著大腦的內在功能架構，因為功能上相似或相關的區域通常其神經元自發性活動會有所關聯（神經元共振）。在本研究中，我們證實了近紅外線光譜儀在研究左外側裂周圍語言區靜息態功能性連結的實用性。我們選取自發性超慢振盪頻率介於0.01-0.1赫茲的數據來分析，且應用動態因素分析證實遞延共變異數結構模型用來研究時間序列資料功能性連結的可行性。相較於簡單相關分析，動態因素分析所得出之功能性連結更為直接而清楚，且推論性較強。動態因素分析除了能提供靜息態功能性連結，也可以進一步將此功能性連結解構成次連結系統並比較次連結間的相關性。利用動態因素分析，三種不同的血流動力參數（帶氧血紅素、去氧血紅素與總量血紅素之濃度變化）的結果具有會聚性與一致性。研究結果顯示左下額葉區、左前上顳葉腦迴與左前顳葉在靜息態時緊密關聯。此外，左上緣迴、雙側上額葉腦迴與左角迴群聚形成左側化之額頂葉網絡 (背側注意力網絡)。我們也發現左外側裂周圍語言區與左上緣迴在靜息態時緊密關聯，此結果與左下頂葉的前端透過間接路徑與布洛卡區相連的推論相符。這些結果顯示靜息態功能性連結反映了在大腦預設模式下語言網絡的結構性連結，也暗示近紅外線光譜儀導出之靜息態功能性連結的差異或許能提供在不同年齡層閱讀障礙的辨識、失語症患者的復健治療計劃與癲癇病患之術前評估。

關鍵字

靜息態功能性連結 ； 近紅外線光譜儀 ； 動態因素分析

並列摘要

There is still considerable disagreement about which brain regions are involved in semantic integration. Although event related task-evoked response is widely used to infer functional localization, this localizationism discounts the intrinsic functional integration among different brain areas. Resting-state functional connectivity (RSFC) represents the synchrony of spatially remote spontaneous neural activity in the absence of external stimuli. RSFC implies the intrinsic functional architecture of the human brain, because regions involved in similar or related function tend to be correlated in their spontaneous activities (neuronal oscillations). In the present study, we examined the applicability of near-infrared spectroscopy (NIRS) in investigating the RSFC of the left perisylvian language network. Applying the dynamic factor analysis (DyFA) on the time series data of spontaneous infra-slow fluctuations with the frequency of 0.01- 0.1 Hz, we confirmed the feasibility of using lagged covariance structure models on the RSFC. Compared with the simple correlation analysis frequently adopted in studying RSFC, the results implied by DyFA is more straightforward and clear-cut, and is more inferential. In addition to providing the RSFC, DyFA decomposes the RSFC into the connectivity within each network and between pairs of networks with factors clustered. For the hemodynamic variables of HbO2, HbR, and HbT, their results with DyFA are convergent and consistent. The present results suggest that the left inferior frontal area, left anterior superior temporal gyrus, and left anterior temporal lobe are tightly connected in the resting state. Moreover, left supramarginal gyrus, bilateral superior frontal gyri, and left angular gyrus are clustered in such a way that they are related to the left lateralized parietal-frontal network (the dorsal attention network). The results also show that the left anterior perisylvian language areas and the left supramarginal gyrus are correlated in the RSFC, which is in accordance with the finding of an anterior segment of the left inferior parietal lobule connecting Broca’s area through an indirect pathway. These findings indicate that RSFC reflects structural connectivity in the default mode network, and imply that lateral differences in the NIRS-based RSFC could be used to identify reading disorders in different age groups, as well as help in developing treatment plans for the rehabilitation of aphasic patients, and the pre-surgical evaluation of epileptic patients.

並列關鍵字

resting-state functional connectivity ； near-infrared spectroscopy ； dynamic factor analysis

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