Giordano Cecchetti1, Federica Agosta2, Silvia Basaia4, Edoardo Spinelli7, Camilla Cividini4, Marco Cursi5, Elisa Canu4, Michela Leocadi4, Roberto Santangelo6, Francesca Caso6, Giovanna Fanelli5, Fabio Minicucci5, Giuseppe Magnani6, Massimo Filippi3
1Neurology Unit, Neurophysiology Service, and Neuroimaging Research Unit, Division of Neuroscience, 2Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, 3Neuroimaging Research Unit, Division of Neuroscience, Neurology Unit, Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University, 4Neuroimaging Research Unit, Division of Neuroscience, 5Neurophysiology Service, 6Neurology Unit, IRCCS San Raffaele Scientific Institute, 7Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Neurology Unit, IRCCS San Raffaele Scientific Institute
Objective:
The aim of this study is to explore the value of EEG analysis in the characterization of the three clinical presentations of primary progressive aphasia (PPA).
Background:
The analysis of EEG cortical sources is promising for the investigation of neurodegenerative disorders.
Design/Methods:
A resting-state 19-channel EEG was obtained in 48 patients diagnosed with PPA (21 nonfluent/agrammatic variant PPA [nfv-PPA], 18 logopenic variant PPA [lv-PPA], 9 semantic variant PPA [sv-PPA]) and in 21 matched healthy controls. Applying seed-based analysis on 3T fMRI data of an independent group of young healthy controls (n.40), we built the maps of three networks belonging to the left perisylvian language network (nodes: middle temporal gyrus– MTG, inferior frontal gyrus– IFG, anterior temporal lobe– ATL) and the maps of default-mode network (DMN) and salience network (SN). Using eLORETA, EEG current source density (CSD) and linear-lagged connectivity (LLC) values were estimated and compared. CSD and LLC analysis were performed at whole-brain level and at network level, respectively.
Results:
Patients showed a low-to-moderate cognitive impairment. At CSD analysis lv-PPA patients showed a higher delta density than nfvPPA, svPPA and healthy subjects. They also showed a higher theta density relative to controls. Level of statistical significance showed a pronounced descending posterior-to-anterior and left-to-right gradient over the brain cortex at theta band. Also nfvPPA patients deviated from healthy subjects in terms of widespread higher theta density. LLC analysis pointed out a significantly higher connectivity at delta and theta frequency bands characterizing all three groups of patients relative to controls in language networks. Connectivity disruption was also evident in non-language networks.
Conclusions:
Findings in PPA patients suggest that Alzheimer’s disease (AD), but not fronto-temporal degeneration (FTD), might induce a characteristic disruption of the cortical electrical activity in lvPPA patients, detectable by EEG. EEG might thus help in the differential diagnosis between AD-related and FTD-related PPA variants.