Neuro-plasticity Studies Based On Large-scale Brain Connectivity Network Analyses

Brain plasticity refers to the capacity of the nervous system to change its structure and function over a lifetime, in reaction to environmental diversity. At birth, the human brain consists of approximately10billion neurons, with rough and redundancy synaptic connections. A decrease in synapses is seen after a period of development, learning and training:synapses that are frequently used have strong connections while rarely used synapses are eliminated. In terms of neuroscience, learning is the process of forming new synaptic connections, and practice is the process of consolidating and strengthening the existing connections. Excaming the brain plasticity changes after learning and training is a major trend of the current neuroplasticity studies. Previous researches demonstrated that neuroplasitcity occurs on a variety of levels, ranging from neurons, columes, functional areas, and even, the large-scale functional networks. On macro scale, dispite the fact that, specific brain regions mediate specific functions, the networks consisted by those regions as well as their interaction and intercoordinations are the basis of the overall human behavior. Therefore, it has extremely important theoretic and application significance to explore the neuroplasticiy changes induced by brain development, learning and trainning, on the level of large-scale functional connectivity brain networks.The current work dedicated to investigating the brain plasticity changes on the large-scale brain network level, by means of functional magnetic resonance imaging (fMRI), as well as a newly introduced functional-funcitonal (task-rest), and functional-strutural(rest-VBM) multi-modal fusion methods. Two aspects of this dissertation have been put forword:The first part investigated the brain plasticity changes on the level of large-scale brain network after long-term and intensive learning and trainning of high level cognitive expertise. In this part, we studied the brain network differences between world-level Chinese chess grandmaters and noices.First, we excamined the influence of cognitive expertise on four networks associated with cognitive task performance:the default mode network (DMN) and three other cognitive networks (central-executive network, dorsal attention network, and salience network), both during task and rest. We found that, in those four networks, the chess grandmasters and noives only showed significant differences in the DMN.Secondly, according to the changed functional connectivity in the DMN, we combined the structural and fucntioanl MRI, and found the structural changes of the striatum as well as striatum-DMN connectivity in chess grandmaters.Thirdly, by means of the functional connectivity analysis and graph theoretical analysis, we investigated the whole-brain functional connectivity network and its topological properties of chess grandmaster. Increased small-world topology and clustering coefficient were found in chess grandmasters, which indicated that long-term cognitive skill learning leaded to a more efficient organization of the brain networks.Finally, we used functional connectivity density mapping analysis to quantificationally depict the short-range and long-range functional connectivity density. We aimed to explore more delicate alteration in the brain of chess grandmasters after long-term training on high-level cognitive expertise.In the second part of this dissertation, we investigated the plasticity changes in the learning-and memory-related networks induced by brain natural development. In this part, we focused on the functional organization of the medial temporal lobe (MTL) network and differences in this network between children and adults.First, we provided a comprehensive intrinsic functional connectivity analysis of seven distinct subdivisions of the human MTL to delineate the functional circuitry of the MTL for better understanding the contributions of its subregions to learning and memory.Secondly, we investigated developmental changes in functional connectivity of the MTL system in twenty-four7-to9-year-old typically developing children, nineteen13-to17-year-old adolescents, and twenty-four19-to22-year-old health adults. Adults showed significantly stronger intrinsic connectivity analysis of the hippocampus with widely-distributed cortical and subcortical areas, demonstrating the functional integration of the MTL system after brain development.