Trial reportScientific reports2017
Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing.
Trial report in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
44 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- From Single-Modal to Multi-Modal Artificial Intelligence in Alzheimer's Disease: A Systematic Review of Databases, Modalities, Diagnostic Performance, and Clinical Translation Challenges.Sensors (Basel, Switzerland) · 2026Pooled it
- Systematic Review: Genetic, Neuroimaging, and Fluids Biomarkers for Frontotemporal Dementia Across Latin America Countries.Frontiers in neurology · 2021Pooled it
- Quantitative EEG signatures of power and functional connectivity alterations in Alzheimer's disease and frontotemporal dementia.Scientific reports · 2026Article
- The use of electroencephalography in neurodegenerative disease and its utility in dementia.NPJ dementia · 2026Review
- Epilepsy and EEG abnormalities in neurodegenerative dementias: toward a system epilepsy framework.Frontiers in aging neuroscience · 2026Review
- Classification of AD and bvFTD using neuropsychological and neuropsychiatric variables: a machine learning study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- The Role of Quantitative EEG in the Diagnosis of Alzheimer's Disease.Diagnostics (Basel, Switzerland) · 2025Review
- Sink-index: a network-based EEG marker for frontotemporal dementia and Alzheimer's disease.Brain communications · 2025Article
- The role of quantitative EEG biomarkers in Alzheimer's disease and mild cognitive impairment: applications and insights.Frontiers in aging neuroscience · 2025Review
- Classification of Alzheimer's Disease and Frontotemporal Dementia Using Electroencephalography to Quantify Communication between Electrode Pairs.Diagnostics (Basel, Switzerland) · 2024Article
- Quantitative Electroencephalography Markers for an Accurate Diagnosis of Frontotemporal Dementia: A Spectral Power Ratio Approach.Medicina (Kaunas, Lithuania) · 2023Article
- The BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds.Scientific data · 2023Article
- Source space connectomics of neurodegeneration: One-metric approach does not fit all.Neurobiology of disease · 2023Article
- Article
- Temporal Irreversibility of Large-Scale Brain Dynamics in Alzheimer's Disease.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Using shallow neural networks with functional connectivity from EEG signals for early diagnosis of Alzheimer's and frontotemporal dementia.Frontiers in neurology · 2023Article
- Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference.Network neuroscience (Cambridge, Mass.) · 2023Article
- Alterations in resting-state functional connectivity after brain posterior lesions reflect the functionality of the visual system in hemianopic patients.Brain structure & function · 2022Article
- Genuine high-order interactions in brain networks and neurodegeneration.Neurobiology of disease · 2022Article
- Multi-feature computational framework for combined signatures of dementia in underrepresented settings.Journal of neural engineering · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Developing effective and affordable biomarkers for dementias is critical given the difficulty to achieve early diagnosis. In this sense, electroencephalographic (EEG) methods offer promising alternatives due to their low cost, portability, and growing robustness. Here, we relied on EEG signals and a novel information-sharing method to study resting-state connectivity in patients with behavioral variant frontotemporal dementia (bvFTD) and controls. To evaluate the specificity of our results, we also tested Alzheimer's disease (AD) patients. The classification power of the ensuing connectivity patterns was evaluated through a supervised classification algorithm (support vector machine). In addition, we compared the classification power yielded by (i) functional connectivity, (ii) relevant neuropsychological tests, and (iii) a combination of both. BvFTD patients exhibited a specific pattern of hypoconnectivity in mid-range frontotemporal links, which showed no alterations in AD patients. These functional connectivity alterations in bvFTD were replicated with a low-density EEG setting (20 electrodes). Moreover, while neuropsychological tests yielded acceptable discrimination between bvFTD and controls, the addition of connectivity results improved classification power. Finally, classification between bvFTD and AD patients was better when based on connectivity than on neuropsychological measures. Taken together, such findings underscore the relevance of EEG measures as potential biomarker signatures for clinical settings.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.