北京師范大學(xué)認(rèn)知神經(jīng)科學(xué)學(xué)習(xí)研究所賀永老師及其合作者于2009年在Brain雜志上發(fā)表了題為“Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load”的研究論文。該篇文章是關(guān)于白質(zhì)多發(fā)性硬化病腦結(jié)構(gòu)網(wǎng)絡(luò)的拓?fù)湫逝c白質(zhì)病變體積的關(guān)聯(lián)研究,，由賀永老師和加拿大McGill大學(xué)的Alan Evans教授的研究團(tuán)隊(duì)合作完成。
白質(zhì)多發(fā)性硬化病(Multiple Sclerosis)是一種常見的以中樞神經(jīng)系統(tǒng)炎性脫髓鞘為特征的疾病,。早期的神經(jīng)影像學(xué)研究已經(jīng)發(fā)現(xiàn)病人在多個(gè)腦白質(zhì)結(jié)構(gòu)上具有病變，最近的研究也發(fā)現(xiàn)病人在局部灰質(zhì)結(jié)構(gòu)上具有異常,。但是,，在腦灰質(zhì)區(qū)域構(gòu)成的結(jié)構(gòu)網(wǎng)絡(luò)整合上是否表現(xiàn)出異常，目前仍不清晰,。在這項(xiàng)研究中,，賀永及其合作者利用磁共振成像技術(shù)獲得的腦結(jié)構(gòu)圖像，結(jié)合基于計(jì)算神經(jīng)解剖的皮層映射技術(shù)獲得的大腦皮層厚度數(shù)據(jù),，構(gòu)建了人腦的結(jié)構(gòu)連接網(wǎng)絡(luò)（圖1）,。進(jìn)而用現(xiàn)代圖論的計(jì)算方法定量描述了病人的腦結(jié)構(gòu)網(wǎng)絡(luò)效率是如何隨著白質(zhì)病變體積變化的,。
賀永及其合作者發(fā)現(xiàn),，病人的腦網(wǎng)絡(luò)即使在疾病條件下也具有高的局部和全局整合效率（即表現(xiàn)出“小世界”拓?fù)鋵傩裕@一研究結(jié)果與該研究團(tuán)隊(duì)先前在健康被試中的研究保持一致,。進(jìn)一步研究發(fā)現(xiàn),，白質(zhì)多發(fā)硬化病人的網(wǎng)絡(luò)效率隨著白質(zhì)病變的體積呈現(xiàn)出一定比例的減弱，而且最為嚴(yán)重的減弱發(fā)生在腦島,、中央前回及額顳葉皮層區(qū)域（圖2）,。這項(xiàng)研究表明了白質(zhì)多發(fā)硬化病人的白質(zhì)病變程度嚴(yán)重影響了腦結(jié)構(gòu)網(wǎng)絡(luò)的信息傳輸效率?；谏鲜鲅芯拷Y(jié)果,，他們提供了國(guó)際上第一個(gè)白質(zhì)多發(fā)硬化病腦結(jié)構(gòu)網(wǎng)絡(luò)整合異常的模型，為該疾病的“失連接”概念提供了結(jié)構(gòu)證據(jù),。
三位論文審稿人一致認(rèn)為,，該研究所采用的研究方法是高度創(chuàng)新的，結(jié)果是非常令人感興趣的,可能具有高的臨床研究?jī)r(jià)值,。（生物谷Bioon.com）
原文下載地址：
http://psychbrain.bnu.edu.cn/teachcms/res_base/teachcms/
upload/article/file/2010_3/9_10/iwn4gdwrab8c.pdf
生物谷推薦英文摘要：
Brain. 2009 Dec;132(Pt 12):3366-79. PMID: 19439423
Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load.
He Y, Dagher A, Chen Z, Charil A, Zijdenbos A, Worsley K, Evans A.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
White matter tracts, which play a crucial role in the coordination of information flow between different regions of grey matter, are particularly vulnerable to multiple sclerosis. Many studies have shown that the white matter lesions in multiple sclerosis are associated with focal abnormalities of grey matter, but little is known about the alterations in the coordinated patterns of cortical morphology among regions in the disease. Here, we used cortical thickness measurements from structural magnetic resonance imaging to investigate the relationship between the white matter lesion load and the topological efficiency of structural cortical networks in multiple sclerosis. Network efficiency was defined using a 'small-world' network model that quantifies the effectiveness of information transfer within brain networks. In this study, we first classified patients (n = 330) into six subgroups according to their total white matter lesion loads, and identified structural brain networks for each multiple sclerosis group by thresholding the corresponding inter-regional cortical thickness correlation matrix, followed by a network efficiency analysis with graph theoretical approaches. The structural cortical networks in multiple sclerosis demonstrated efficient small-world architecture regardless of the lesion load, an organization that maximizes the information processing at a relatively low wiring cost. However, we found that the overall small-world network efficiency in multiple sclerosis was significantly disrupted in a manner proportional to the extent of total white matter lesions. Moreover, regional efficiency was also significantly decreased in specific brain regions, including the insula and precentral gyrus as well as regions of prefrontal and temporal association cortices. Finally, we showed that the lesions also altered many cortical thickness correlations in the frontal, temporal and parietal lobes. Our results suggest that the white matter lesions in multiple sclerosis might be associated with aberrant neuronal connectivity among widely distributed brain regions, and provide structural (morphological) evidence for the notion of multiple sclerosis as a disconnection syndrome
