數理資優大腦白質網路結構分析之研究
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Date
2019-03-??
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國立臺灣師範大學教育心理學系
Department of Educational Psychology, NTNU
Department of Educational Psychology, NTNU
Abstract
近期研究已普遍指出數理資優個體的大腦結構與常人不同。然而，多數研究較著重於認知功能與單一大腦區域的運作之關係。本研究首從圖形理論取向探討數理資優、智力與大腦白質網路結構之關係。參與者為42 位神經功能正常的成年男性，數理資優與一般成人各21 人，其年齡分別為年齡為21.00 ± 1.67 歲及年齡為21.48 ± 2.29 歲。研究者採用魏氏成人智力測驗第三版評估個體智商，並進行擴散張量影像掃瞄，再依此建構大腦白質網路，使用圖形理論計算大腦網路屬性及各節點之連結效率。結果發現，數理資優組在大腦局部區域內節點之間的傳遞效率較佳，並以左側額上回尤甚。進一步控制數理資優與一般組的智力均等，數理資優組在大腦局部區域內的節點訊息傳輸效率仍占有優勢，並以涉及空間處理能力的左側枕上回群聚程度最佳。其後，分別分析數理資優與一般組在智力與大腦網路拓樸屬性之相關結果指出，僅一般成人作業智力與大腦網路全局效率為正相關，數理資優成人的智力與大腦網路連結則無直接關聯。上述結果不僅提供數理資優與常人在大腦白質結構差異情形的實徵證據，更從大腦拓樸網路之取向區辨數理資優、數理能力以及智力之異同，將可做為往後評估資賦優異的參考。
Recent studies have highlighted that people with mathematical and scientific talents develop a different brain structure fromthose with typical development. However, most of these studies have focused on the relationship between cognitive functionsof the brain and the operation of a single area of the brain. This study explores the connections among the network structureswith relation to mathematical and scientific talents, intelligence, and white matter. The study recruited 42 men with normalnerve functions. The experimental group comprised 21 participants with mathematical and scientific talents and an age of21.00 ± 1.67 years; the control group comprised 21 participants with typical developmental and an age of 21.48 ± 2.29 years.The mathematical and scientific talent and typical developmental groups consisted of 21 people each. The researchersadopted the third version of the Wechsler Adult Intelligence Test to evaluate individual intelligence, conduct diffusion tensorimaging of participants, and construct a network of white matter to analyze the overall network attributes and nodalefficiencies using graph theory. The results show that the communication efficiency among the nodes inside the local regionis relatively better in people with mathematical and scientific talents, particularly the in the superior prefrontal gyrus.Moreover, when intelligence was equal between the two groups, the mathematical and scientific talent group outperformedthe other in terms of node efficiency in local regions and the clustering coefficient in the superior occipital gyrus. Therelationship between the topological properties and the intelligence of the mathematical and scientific talent group and the typical developmental group showed that only the intelligence of the typical developmental group was positively connectedwith integrated efficiency across several regions of the brain; however, no direct correlation was shown in the mathematicaland scientific talents group. The results not only provided empirical evidence for the disparity in white matter structurebetween mathematical and scientific talent and typical development groups but also distinguished mathematical and scientifictalents, mathematical ability, and intelligence based on the topological network of the brain, which can be used in futureassessments for people with mathematical and scientific talents.
Recent studies have highlighted that people with mathematical and scientific talents develop a different brain structure fromthose with typical development. However, most of these studies have focused on the relationship between cognitive functionsof the brain and the operation of a single area of the brain. This study explores the connections among the network structureswith relation to mathematical and scientific talents, intelligence, and white matter. The study recruited 42 men with normalnerve functions. The experimental group comprised 21 participants with mathematical and scientific talents and an age of21.00 ± 1.67 years; the control group comprised 21 participants with typical developmental and an age of 21.48 ± 2.29 years.The mathematical and scientific talent and typical developmental groups consisted of 21 people each. The researchersadopted the third version of the Wechsler Adult Intelligence Test to evaluate individual intelligence, conduct diffusion tensorimaging of participants, and construct a network of white matter to analyze the overall network attributes and nodalefficiencies using graph theory. The results show that the communication efficiency among the nodes inside the local regionis relatively better in people with mathematical and scientific talents, particularly the in the superior prefrontal gyrus.Moreover, when intelligence was equal between the two groups, the mathematical and scientific talent group outperformedthe other in terms of node efficiency in local regions and the clustering coefficient in the superior occipital gyrus. Therelationship between the topological properties and the intelligence of the mathematical and scientific talent group and the typical developmental group showed that only the intelligence of the typical developmental group was positively connectedwith integrated efficiency across several regions of the brain; however, no direct correlation was shown in the mathematicaland scientific talents group. The results not only provided empirical evidence for the disparity in white matter structurebetween mathematical and scientific talent and typical development groups but also distinguished mathematical and scientifictalents, mathematical ability, and intelligence based on the topological network of the brain, which can be used in futureassessments for people with mathematical and scientific talents.