Increased functional connectivity patterns in mild Alzheimer's disease: A rsfMRI study

Lucía Penalba-Sánchez; Patrícia Oliveira-Silva; Alexander Luke Sumich; Ignacio Cifre

doi:10.3389/fnagi.2022.1037347

Increased functional connectivity patterns in mild Alzheimer's disease: A rsfMRI study

Front Aging Neurosci. 2023 Jan 9:14:1037347. doi: 10.3389/fnagi.2022.1037347. eCollection 2022.

Authors

Lucía Penalba-Sánchez^{1

2

3}, Patrícia Oliveira-Silva², Alexander Luke Sumich³, Ignacio Cifre¹

Affiliations

¹ Facultat de Psicologia, Ciències de l'educació i de l'Esport, Blanquerna, Universitat Ramon Llull, Barcelona, Spain.
² Human Neurobehavioral Laboratory (HNL), Research Centre for Human Development (CEDH), Faculdade de Educação e Psicologia, Universidade Católica Portuguesa, Porto, Portugal.
³ NTU Psychology, School of Social Sciences, Nottingham Trent University, Nottingham, United Kingdom.

Abstract

Background: Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder. In view of our rapidly aging population, there is an urgent need to identify Alzheimer's disease (AD) at an early stage. A potential way to do so is by assessing the functional connectivity (FC), i.e., the statistical dependency between two or more brain regions, through novel analysis techniques.

Methods: In the present study, we assessed the static and dynamic FC using different approaches. A resting state (rs)fMRI dataset from the Alzheimer's disease neuroimaging initiative (ADNI) was used (n = 128). The blood-oxygen-level-dependent (BOLD) signals from 116 regions of 4 groups of participants, i.e., healthy controls (HC; n = 35), early mild cognitive impairment (EMCI; n = 29), late mild cognitive impairment (LMCI; n = 30), and Alzheimer's disease (AD; n = 34) were extracted and analyzed. FC and dynamic FC were extracted using Pearson's correlation, sliding-windows correlation analysis (SWA), and the point process analysis (PPA). Additionally, graph theory measures to explore network segregation and integration were computed.

Results: Our results showed a longer characteristic path length and a decreased degree of EMCI in comparison to the other groups. Additionally, an increased FC in several regions in LMCI and AD in contrast to HC and EMCI was detected. These results suggest a maladaptive short-term mechanism to maintain cognition.

Conclusion: The increased pattern of FC in several regions in LMCI and AD is observable in all the analyses; however, the PPA enabled us to reduce the computational demands and offered new specific dynamic FC findings.

Keywords: Alzheimer’s disease; dynamic functional connectivity; functional connectivity; mild cognitive impairment; point process analysis; resting state fMRI.