Effective and Accurate Diagnosis of Subjective Cognitive Decline Based on Functional Connection and Graph Theory View

Abstract

Subjective cognitive decline (SCD) is considered the earliest preclinical stage of Alzheimer’s disease (AD) that precedes mild cognitive impairment (MCI). Effective and accurate diagnosis of SCD is crucial for early detection of and timely intervention in AD. In this study, brain functional connectome (i.e., functional connections and graph theory metrics) based on the resting-state functional magnetic resonance imaging (rs-fMRI) provided multiple information about brain networks and has been used to distinguish individuals with SCD from normal controls (NCs). The consensus connections and the discriminative nodal graph metrics selected by group least absolute shrinkage and selection operator (LASSO) mainly distributed in the prefrontal and frontal cortices and the subcortical regions corresponded to default mode network (DMN) and frontoparietal task control network. Nodal efficiency and nodal shortest path showed the most significant discriminative ability among the selected nodal graph metrics. Furthermore, the comparison results of topological attributes suggested that the brain network integration function was weakened and network segregation function was enhanced in SCD patients. Moreover, the combination of brain connectome information based on multiple kernel-support vector machine (MK-SVM) achieved the best classification performance with 83.33% accuracy, 90.00% sensitivity, and an area under the curve (AUC) of 0.927. The findings of this study provided a new perspective to combine machine learning methods with exploration of brain pathophysiological mechanisms in SCD and offered potential neuroimaging biomarkers for diagnosis of early-stage AD.

Complexity Analysis of the Default Mode Network Using Resting-State fMRI in Down Syndrome: Relationships Highlighted by a Neuropsychological Assessment

“…In relation to the results provided by studies on AD and people with SCD, the integration measures indicated some abnormalities. The increased values in the mean of the weighted path were similar to the results presented in [ 35 ]; thus, we can also argue that in DS people, the capacity to transmit and connect the information through the whole brain is altered. Nevertheless, related to [ 35 ] and specifically in their results on modularity, we were also able to affirm that the network segregation function is increased in people with lower cognitive performance.…”

“…The increased values in the mean of the weighted path were similar to the results presented in [ 35 ]; thus, we can also argue that in DS people, the capacity to transmit and connect the information through the whole brain is altered. Nevertheless, related to [ 35 ] and specifically in their results on modularity, we were also able to affirm that the network segregation function is increased in people with lower cognitive performance. In the current study, this increase in the DS population can be identified through measures of the global clustering coefficients, complexity, and number of triangles.…”

“…Nevertheless, the results obtained allow us to justify the necessity to explore in more detail the behavior of each subnetwork in the DS population. Most likely, subsequent studies should follow the analysis of recently published articles [ 35 , 62 ], which include studies on the topology of brain networks using the same (or similar) segregation and integration measures used in this paper.…”

“…Thus, the small world, defined by the optimal balance between these two measures [ 34 ], indicated altered brain connectivity. Nevertheless, a recent study [ 35 ] examined the topological attributes of the small world in patients with subjective cognitive decline (SCD; a clinical stage before the diagnosis of AD). The SCD sample presented global efficiency values lower than normal controls, while characteristic path length and modularity were higher.…”

Alterations in Dynamic Functional Connectivity in Individuals With Subjective Cognitive Decline

“…In contrast to the remarkable dynamic FC alterations, we did not find differences in either global or local topological parameters by graph theory approaches. Previous studies have shown topological alterations in SCD subjects (Chen et al, 2020 ; Xu et al, 2020 ), and we speculated that the discrepancies may be attributable to the different diagnostic criteria for SCD, the variations in demographics of the cohorts, and methodological aspects (Wang et al, 2020 ). These studies also revealed no group differences in the static analysis of global and local efficiency between AD dementia patients and NCs (Peraza et al, 2015 ; Schumacher et al, 2019 ).…”