# White Matter Network Alterations in Alzheimer's Disease Patients
## 7 Discussion  
In this study, we comprehensively explored the whole brain network for WM changes in AD and MCI using TBSS, graph theoretical analysis and NBS. NBS and graph theory have become ideal tools for studying the changes that occur in brain network due to progression of AD and MCI. For graph theoretic analysis, achieving consistent results is the major issue while doing studies on different imaging modalities. Recent studies show that consistent results on graph metrics measured using cortical features and weighted network metrics can be achieved with fewer number of subjects in AD and control groups [38]. Thus, our study is more concerned about the use of graph theoretical analysis technique that generates stable results. The novel finding of this study is identification of topological changes in regions where observable alterations in network level have occurred. Thus, we performed the combined study of NBS and graph theoretic analysis to identify the graph theoretical metrics of regions where observable alterations of white matter are noticed. Additionally, in this study, we comprehensively examined the whole brain network to identify AD and MCI associated WM changes using TBSS. From our study we did not find that FA could reflect significant regional changes in brain. However, at network level observable alterations were noticed. Many previous studies [39] show the increase in randomization in brain functional network in AD, suggesting the elevation of small-worldness property. These studies further demonstrate the loss of global information integration in AD. Increased value of small-worldness and global efficiency in HC indicated more efficient use of neural resources in the absence of neurodegeneration process. These characteristics indicate that AD and MCI patients have significantly longer path lengths of their MRI graphs, thus suggesting a disruption in effective interactions between and across cortical regions and providing further support for the concept of AD as a disconnection syndrome. Consistent with prior studies, our study demonstrated that in the analysis of the global network parameters, no significant difference was found between the controls and patients, which suggests that global network analysis may not reflect the subtle changes of connectivity in MCI and AD, even after the neuro-degeneration process has begun. Additionally, our study shows increased clustering coefficient in HC, compared to MCI and AD. The view contradicts the recent study [40] that found subtle changes in global and local network metrics in AD and MCI. Another goal of our study is to investigate the disruption of structural connections between different regions of brain in AD and MCI patients, compared with HC. As predicted, compared to HC and MCI patients, AD patients showed wide-spread alterations in many regions of the brain, including frontal, temporal, limbic, parietal lobe, sub cortical grey nuclei and central and medial surfaces. Similarly, patients with MCI showed network alterations in sub cortical grey nuclei, frontal limbic and central region. As MCI is considered to be prodromal stage of AD, even in preclinical phase, our results collectively indicate that disruption begins in limbic lobe [40]. However, the disruption gradually increases as the disease progresses. We observed in our results that the disruption is mainly