» Articles » PMID: 30254710

Usefulness of EEG Techniques in Distinguishing Frontotemporal Dementia from Alzheimer's Disease and Other Dementias

Overview
Journal Dis Markers
Publisher Wiley
Specialty Biochemistry
Date 2018 Sep 27
PMID 30254710
Citations 15
Authors
Affiliations
Soon will be listed here.
Abstract

The clinical distinction of frontotemporal dementia (FTD) and Alzheimer's disease (AD) may be difficult. In this narrative review we summarize and discuss the most relevant electroencephalography (EEG) studies which have been applied to demented patients with the aim of distinguishing the various types of cognitive impairment. EEG studies revealed that patients at an early stage of FTD or AD displayed different patterns in the cortical localization of oscillatory activity across different frequency bands and in functional connectivity. Both classical EEG spectral analysis and EEG topography analysis are able to differentiate the different dementias at group level. The combination of standardized low-resolution brain electromagnetic tomography (sLORETA) and power parameters seems to improve the sensitivity, but spectral and connectivity biomarkers able to differentiate single patients have not yet been identified. The promising EEG findings should be replicated in larger studies, but could represent an additional useful, noninvasive, and reproducible diagnostic tool for clinical practice.

Citing Articles

Resting-State EEG Power Spectral Density Analysis Between Healthy and Cognitively Impaired Subjects.

Walters K, Shukla R, Kumar V, Schueren S, Yadav H, Schilaty N Brain Sci. 2025; 15(2).

PMID: 40002506 PMC: 11853412. DOI: 10.3390/brainsci15020173.


Screening of Aβ and phosphorylated tau status in the cerebrospinal fluid through machine learning analysis of portable electroencephalography data.

Hata M, Miyazaki Y, Mori K, Yoshiyama K, Akamine S, Kanemoto H Sci Rep. 2025; 15(1):2067.

PMID: 39820097 PMC: 11739687. DOI: 10.1038/s41598-025-86449-2.


Classification of Alzheimer's Disease and Frontotemporal Dementia Using Electroencephalography to Quantify Communication between Electrode Pairs.

Ma Y, Bland J, Fujinami T Diagnostics (Basel). 2024; 14(19).

PMID: 39410593 PMC: 11475635. DOI: 10.3390/diagnostics14192189.


Tracking EEG network dynamics through transitions between eyes-closed, eyes-open, and task states.

Krukow P, Rodriguez-Gonzalez V, Kopis-Posiej N, Gomez C, Poza J Sci Rep. 2024; 14(1):17442.

PMID: 39075178 PMC: 11286934. DOI: 10.1038/s41598-024-68532-2.


Visual Electroencephalography Assessment in the Diagnosis and Prognosis of Cognitive Disorders.

Michels D, van Marum S, Arends S, Tavy D, Wirtz P, de Bruijn B J Clin Neurophysiol. 2024; 42(3):243-250.

PMID: 39051913 PMC: 11864052. DOI: 10.1097/WNP.0000000000001107.


References
1.
Knopman D, Boeve B, Parisi J, Dickson D, Smith G, Ivnik R . Antemortem diagnosis of frontotemporal lobar degeneration. Ann Neurol. 2005; 57(4):480-8. DOI: 10.1002/ana.20425. View

2.
Wang J, Williamson S, Kaufman L . Magnetic source images determined by a lead-field analysis: the unique minimum-norm least-squares estimation. IEEE Trans Biomed Eng. 1992; 39(7):665-75. DOI: 10.1109/10.142641. View

3.
Ferreri F, Vecchio F, Guerra A, Miraglia F, Ponzo D, Vollero L . Age related differences in functional synchronization of EEG activity as evaluated by means of TMS-EEG coregistrations. Neurosci Lett. 2017; 647:141-146. DOI: 10.1016/j.neulet.2017.03.021. View

4.
Locatelli T, Cursi M, Liberati D, Franceschi M, Comi G . EEG coherence in Alzheimer's disease. Electroencephalogr Clin Neurophysiol. 1998; 106(3):229-37. DOI: 10.1016/s0013-4694(97)00129-6. View

5.
Yu M, Gouw A, Hillebrand A, Tijms B, Stam C, van Straaten E . Different functional connectivity and network topology in behavioral variant of frontotemporal dementia and Alzheimer's disease: an EEG study. Neurobiol Aging. 2016; 42:150-62. DOI: 10.1016/j.neurobiolaging.2016.03.018. View