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Updated: Jan 6, 2026

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
Published on: August 7, 2017
Comparative Analysis of Intracortical Causal Information Flow in Healthy Older Adults and Patients With Amnestic Mild
Giuseppe Caravaglios1, Emma Gabriella Muscoso1, Valeria Blandino2
1U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy.
Abstract:
BackgroundAlzheimer's disease is a neurodegenerative condition characterized by the accumulation of misfolded proteins disrupting connectivity between brain regions. Electroencephalography provides optimal temporal resolution for assessing neuronal communication.ObjectiveTo detect and compare the localization of brain rhythms and the directional flow of oscillatory activity among default mode network nodes during the resting state in patients with amnestic mild cognitive impairment (aMCI) and healthy older adults (HOA).MethodsWe recruited 94 aMCI patients and 66 HOA. We conducted functional localization and connectivity analyses using scalp recordings of neuronal activity, estimated by eLORETA approach. We calculated the effective connectivity by applying the isolated effective coherence method, allowing the frequency decomposition of the directional flow of oscillatory activity between pairs of brain regions. Eight brain regions from the default mode network were selected.ResultsAlthough trends in spectral power were noted, no statistically significant differences were found between groups. Concerning iCOH analysis, both groups showed increased information flow from the posterior to the anterior nodes. Specifically, the precuneus was dominant in transmitting information to the anterior nodes of the DMN. Furthermore, aMCI patients had lower effective connectivity values than HOA.ConclusionsiCOH analysis effectively profiles default mode nodes during the resting state, adding information on both localization and directionality of information flow, as well as the involved EEG oscillations. Furthermore, it is well-suited to detect between-group connectivity differences, suggesting its usefulness as a biomarker in the prodromal clinical stage of AD.
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