Investigating Functional Connectivity Changes in Mild Cognitive Impairment and Alzheimer's Disease: Insights from Word Generation Tasks and Resting-State fMRI

Abstract: Objective: The objective of this study was to investigate the functional changes associated with mild cognitive impairment (MCI) using independent cluster analysis (ICA) with the word derivation task and resting-state fMRI.Methods: Participants included 17 MCI patients and 17 age- and education-matched healthy controls. All participants underwent resting-state and task-based fMRI while performing the word derivation task. Independent cluster analysis was used to identify the relevant independent components (ICs) and their associated networks. The Dice Coefficiency method was used to determine the relevance of the ICs to the networks of interest.Results: Results showed that IC-14 was relevant to language networks in both resting-state and task-based fMRI. Resting-state ICA was more powerful than task-based fMRI in voxel size, but it is evaluated as compensation mechanism in the MCI group in the language network. The lingual gyrus was found to be more active in MCI patients during the resting state, indicating a hyperconnectivity state that may be a protective mechanism but can also be harmful to connected neurons. Additionally, compensatory activity was observed in the right temporal occipital fusiform cortex, right hippocampus, and right thalamus during the word derivation task.Conclusion: Task-based evaluations are important in detecting cognitive impairments in individuals with MCI, particularly in language processing. Our findings provide important insights into the neural mechanisms underlying cognitive impairments in MCI and highlight the significance of reducing interference in language and frontoparietal areas. Keywords: mild cognitive impairment, language network, task-based fMRI, resting-state fMRI, independent component analysis.