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1
Cortical microstructure in primary progressive aphasia: a multicenter study.
In: Alzheimer's research & therapy, vol 14, iss 1 (2022)
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2
A Preliminary Report of Network Electroencephalographic Measures in Primary Progressive Apraxia of Speech and Aphasia
In: Brain Sciences; Volume 12; Issue 3; Pages: 378 (2022)
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3
Primary and Secondary Progressive Aphasia in Posterior Cortical Atrophy
In: Life; Volume 12; Issue 5; Pages: 662 (2022)
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4
A 'Mini Linguistic State Examination' to classify primary progressive aphasia. ...
Patel, Nikil; Peterson, Katie A; Ingram, Ruth U. - : Apollo - University of Cambridge Repository, 2022
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5
A 'Mini Linguistic State Examination' to classify primary progressive aphasia. ...
Patel, Nikil; Peterson, Katie A; Ingram, Ruth U. - : Apollo - University of Cambridge Repository, 2022
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6
Improving the diagnostic accuracy of primary progressive aphasia using cognitive tests
Foxe, David Gordon. - : The University of Sydney, 2022. : Faculty of Science, School of Psychology, 2022
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7
Neural substrates of verbal repetition deficits in primary progressive aphasia.
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8
Resting functional connectivity in the semantic appraisal network predicts accuracy of emotion identification.
Yang, Winson FZ; Toller, Gianina; Shdo, Suzanne. - : eScholarship, University of California, 2021
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9
Neural dynamics of semantic categorization in semantic variant of primary progressive aphasia.
Borghesani, V; Dale, CL; Lukic, S. - : eScholarship, University of California, 2021
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10
Uniform data set language measures for bvFTD and PPA diagnosis and monitoring.
In: Alzheimer's & dementia (Amsterdam, Netherlands), vol 13, iss 1 (2021)
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11
Resting functional connectivity in the semantic appraisal network predicts accuracy of emotion identification.
Yang, Winson FZ; Toller, Gianina; Shdo, Suzanne. - : eScholarship, University of California, 2021
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12
What Do We Mean by Behavioral Disinhibition in Frontotemporal Dementia?
Magrath Guimet, Nahuel; Miller, Bruce L; Allegri, Ricardo F. - : eScholarship, University of California, 2021
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13
Uniform data set language measures for bvFTD and PPA diagnosis and monitoring.
In: Alzheimer's & dementia (Amsterdam, Netherlands), vol 13, iss 1 (2021)
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14
What Do We Mean by Behavioral Disinhibition in Frontotemporal Dementia?
Magrath Guimet, Nahuel; Miller, Bruce L; Allegri, Ricardo F. - : eScholarship, University of California, 2021
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15
Primary Progressive Aphasia: Use of Graphical Markers for an Early and Differential Diagnosis
In: Brain Sciences ; Volume 11 ; Issue 9 (2021)
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16
Survival in the Three Common Variants of Primary Progressive Aphasia: A Retrospective Study in a Tertiary Memory Clinic
In: Brain Sciences ; Volume 11 ; Issue 9 (2021)
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17
Application of Machine Learning to Electroencephalography for the Diagnosis of Primary Progressive Aphasia: A Pilot Study
In: Brain Sciences ; Volume 11 ; Issue 10 (2021)
Abstract: Background. Primary progressive aphasia (PPA) is a neurodegenerative syndrome in which diagnosis is usually challenging. Biomarkers are needed for diagnosis and monitoring. In this study, we aimed to evaluate Electroencephalography (EEG) as a biomarker for the diagnosis of PPA. Methods. We conducted a cross-sectional study with 40 PPA patients categorized as non-fluent, semantic, and logopenic variants, and 20 controls. Resting-state EEG with 32 channels was acquired and preprocessed using several procedures (quantitative EEG, wavelet transformation, autoencoders, and graph theory analysis). Seven machine learning algorithms were evaluated (Decision Tree, Elastic Net, Support Vector Machines, Random Forest, K-Nearest Neighbors, Gaussian Naive Bayes, and Multinomial Naive Bayes). Results. Diagnostic capacity to distinguish between PPA and controls was high (accuracy 75%, F1-score 83% for kNN algorithm). The most important features in the classification were derived from network analysis based on graph theory. Conversely, discrimination between PPA variants was lower (Accuracy 58% and F1-score 60% for kNN). Conclusions. The application of ML to resting-state EEG may have a role in the diagnosis of PPA, especially in the differentiation from controls. Future studies with high-density EEG should explore the capacity to distinguish between PPA variants.
Keyword: Alzheimer’s disease; biomarkers machine learning; electroencephalography; frontotemporal dementia; graph theory; K-Nearest Neighbors; primary progressive aphasia; resting-state
URL: https://doi.org/10.3390/brainsci11101262
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18
Longitudinal Changes in Cognition, Behaviours, and Functional Abilities in the Three Main Variants of Primary Progressive Aphasia: A Literature Review
In: Brain Sciences ; Volume 11 ; Issue 9 (2021)
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19
Verbal Short-Term Memory Disturbance in the Primary Progressive Aphasias: Challenges and Distinctions in a Clinical Setting
In: Brain Sciences ; Volume 11 ; Issue 8 (2021)
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20
Treatment for Anomia in Bilingual Speakers with Progressive Aphasia
In: Brain Sciences ; Volume 11 ; Issue 11 (2021)
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