Structural connectivity of the brain: differences between a normal brain and a brain with pathology

Understanding the large-scale structural network formed by neurons is a major challenge in neuroscience. In this study we analyzed the structural connectivity of the human brain in 22 healthy subjects and in two patients with post-traumatic epilepsy. We evaluated the differences between these two gr...

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Bibliographic Details
Main Authors: Carmen Ferra, Hugo Alexandre Ferreira, Pedro Gonçalves Pereira, Rui Manaças, Alexandre Andrade
Format: Article
Language:English
Published: Escola Superior de Tecnologia da Saúde de Lisboa 2015-12-01
Series:Saúde & Tecnologia
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Online Access:https://web.estesl.ipl.pt/ojs/index.php/ST/article/view/1054
Description
Summary:Understanding the large-scale structural network formed by neurons is a major challenge in neuroscience. In this study we analyzed the structural connectivity of the human brain in 22 healthy subjects and in two patients with post-traumatic epilepsy. We evaluated the differences between these two groups. We also investigated differences in connectivity regarding gender and age in healthy individuals. For this purpose, we developed an analysis protocol using specialized software applications and we used graph theory metrics to characterize the structural connectivity between 118 different brain regions. Within the group of healthy subjects we found that men in general are those with higher average values of graph theory metrics. However, there were no significant differences in gender regarding global characterization of the brain. In addition, age was, in general, negatively correlated to the connectivity metrics. The brain regions where the most important differences were observed between healthy individuals and patients were: the Rolandic sulcus, the hippocampus, the pre-cuneus, the thalamus and the cerebellum bilaterally. These differences were consistent with theradiologic images of patients and the studied literature on post-traumatic epilepsy. Developments are expected for the study of the structural connectivity of the human brain, since its potential can be combined with other methods to characterize the disorders of brain circuits.
ISSN:1646-9704