Mild cognitive impairment (MCI) is generally regarded as a prodromal stage of Alzheimer's disease (AD). In coping with the challenges caused by AD, we analyzed resting-state functional magnetic resonance imaging data of 82 MCI subjects and 93 normal controls (NCs). The alteration of brain functional network in MCI was investigated on three scales, including global metrics, nodal characteristics, and modular properties. The results supported the existence of small worldness, hubs, and community structure in the brain functional networks of both groups. Compared with NCs, the network altered in MCI over all the three scales. In scale I, we found significantly decreased characteristic path length and increased global efficiency in MCI. Moreover, altered global network metrics were associated with cognitive level evaluated by neuropsychological assessments. In scale II, the nodal betweenness centrality of some global hubs, such as the right Crus II of cerebellar hemisphere (CERCRU2.R) and fusiform gyrus (FFG.R), changed significantly and associated with the severity and cognitive impairment in MCI. In scale III, although anatomically adjacent regions tended to be clustered into the same module regardless of group, discrepancies existed in the composition of modules in both groups, with a prominent separation of the cerebellum and a less localized organization of community structure in MCI compared with NC. Taking advantages of random forest approach, we achieved an accuracy of 91.4% to discriminate MCI patients from NCs by integrating cognitive assessments and network analysis. The importance of the used features fed into the classifier further validated the nodal characteristics of CERCRU2.R and FFG.R could be potential biomarkers in the identification of MCI. In conclusion, the present study demonstrated that the brain functional connectome data altered at the stage of MCI and could assist the automatic diagnosis of MCI patients.
Background:
Obsessive-compulsive disorder (OCD) and schizophrenia (SZ) as two severe mental disorders share many clinical symptoms, and have a tight association on the psychopathological level. However, the neurobiological substrates between these two diseases remain unclear. To the best of our knowledge, no study has directly compared OCD with SZ from the perspective of white matter (WM) networks.
Methods:
Graph theory and network-based statistic methods were applied to diffusion MRI to investigate and compare the WM topological characteristics among 29 drug-naive OCDs, 29 drug-naive SZs, and 65 demographically-matched healthy controls (NC).
Results:
Compared to NCs, OCDs showed the alterations of nodal efficiency and strength in orbitofrontal (OFG) and middle frontal gyrus (MFG), while SZs exhibited widely-distributed abnormalities involving the OFG, MFG, fusiform gyrus, heschl gyrus, calcarine, lingual gyrus, putamen, and thalamus, and most of these regions also showed a significant difference from OCDs. Moreover, SZs had significantly fewer connections in striatum and visual/auditory cortices than OCDs. The right putamen consistently showed significant differences between both disorders on nodal characteristics and structural connectivity.
Conclusions:
SZ and OCD present different level of anatomical impairment and some distinct topological patterns, and the former has more serious and more widespread disruptions. The significant differences between both disorders are observed in many regions involving the frontal, temporal, occipital, and subcortical regions. Particularly, putamen may serve as a potential imaging marker to distinguish these two disorders and may be the key difference in their pathological changes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.