A Brain Network Constructed on an L1-Norm Regression Model Is More Sensitive in Detecting Small World Network Changes in Early AD

Abstract

<jats:p>Most previous imaging studies have used traditional Pearson correlation analysis to construct brain networks. This approach fails to adequately and completely account for the interaction between adjacent brain regions. In this study, we used the L1-norm linear regression model to test the small-world attributes of the brain networks of three groups of patients, namely, those with mild cognitive impairment (MCI), Alzheimer’s disease (AD), and healthy controls (HCs); we attempted to identify the method that may detect minor differences in MCI and AD patients. Twenty-four AD patients, 33 MCI patients, and 27 HC elderly subjects were subjected to functional MRI (fMRI). We applied traditional Pearson correlation and the L1-norm to construct the brain networks and then tested the small-world attributes by calculating the following parameters: clustering coefficient (Cp), path length (Lp), global efficiency (Eg), and local efficiency (Eloc). As expected, L1 could detect slight changes, mainly in MCI patients expressing higher Cp and Eloc; however, no statistical differences were found between MCI patients and HCs in terms of Cp, Lp, Eg, and Eloc, using Pearson correlation. Compared with HCs, AD patients expressed a lower Cp, Eloc, and Lp and an increased Eg using both connectivity metrics. The statistical differences between the groups indicated the brain networks constructed by the L1-norm were more sensitive to detect slight small-world network changes in early stages of AD.</jats:p>

Brain Structural Network Compensation Is Associated With Cognitive Impairment and Alzheimer’s Disease Pathology

“…These findings are in line with previous studies reporting altered graph theoretical properties in these regions in ADspectrum patients (Shah et al, 2018;Liu et al, 2020). Most of the network graph theoretical properties referring to the frontal lobe, medial temporal lobe, and subcortical structures-areas that play a role in perception, executive control, episodic memory, and understanding-have consistently been found to be affected across the development of AD (Geib et al, 2017;Danti et al, 2018;Luo et al, 2018).…”

“…This study demonstrates the compensation related to cognitive impairments, which exists with a potential AD pathological basis behind them. Taken together, our findings and those from structural network studies suggest structural brain compensation in response to brain damage (Wook Yoo et al, 2015;Liu et al, 2020). However, the relationship between structural changes and disease progression remains controversial.…”

“…Research interest is transforming to increasingly earlier diagnoses, since the origin of AD and the key to treatment probably lie in preventing progression to a fully-fledged disease (Hem et al, 2016;Slot et al, 2018). It should be noted that compensation in the structural network has been shown to be manifested earlier in AD-spectrum patients (Liu et al, 2020), and there is increasing interest in the study of structural network alterations to assess the progression in subjects who have a higher risk of AD (Sanchez-Benavides et al, 2018). Therefore, it is essential to evaluate alterations in structural networks related to cognition and pathology (Dicks et al, 2020).…”

“…To reduce the number of local tests, the nodal network characteristics for nodes were averaged in 90 regions of interest as defined by the automatic anatomical labeling (AAL) brain atlas (Tzourio-Mazoyer et al, 2002;Jin et al, 2020). The network metrics were classified as "basic" or "higher-order" parameters (Liu et al, 2020). The basic parameters included the local and global degree and the small-worldness.…”

The Abnormal Alternations of Brain Imaging in Patients with Chronic Obstructive Pulmonary Disease: A Systematic Review

“…Wang 2020 [19] China N = 85 patients with stable COPD (45) and NCs (40) 67.93 Patients with COPD showed CI in visuospatial/executive, naming, attention, language, abstraction, delayed recall, and orientation.…”