Distinctive Oculomotor Behaviors in Alzheimer's Disease and Frontotemporal Dementia.
Oculomotor behavior can provide insight into the integrity of widespread cortical networks, which may contribute to the differential diagnosis between Alzheimer's disease and frontotemporal dementia. Three groups of patients with Alzheimer's disease, behavioral variant of frontotemporal dementia (bv...
| Publicado en: | Frontiers in Aging Neuroscience |
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| Autores principales: | , , , , , , , , , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Frontiers Media S.A.
2/4/2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=148496243&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 148496243 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16634365 BG2U jtl: Frontiers in Aging Neuroscience issn: 16634365 maglogo: N pubinfo: dt: 2/4/2021 pid: 40038 pub: Frontiers Media S.A. artinfo: ui: 148496243 10.3389/fnagi.2020.603790 148496243 ppct: 20 formats: tig: atl: Distinctive Oculomotor Behaviors in Alzheimer's Disease and Frontotemporal Dementia. aug: au: Lage, Carmen López-García, Sara Bejanin, Alexandre Kazimierczak, Martha Aracil-Bolaños, Ignacio Calvo-Córdoba, Alberto Pozueta, Ana García-Martínez, María Fernández-Rodríguez, Andrea Bravo-González, María Jiménez-Bonilla, Julio Banzo, Ignacio Irure-Ventura, Juan Pegueroles, Jordi Illán-Gala, Ignacio Fortea, Juan Rodríguez-Rodríguez, Eloy Lleó-Bisa, Alberto García-Cena, Cecilia E. Sánchez-Juan, Pascual affil: Institute for Research Marqués de Valdecilla (IDIVAL), University of Cantabria and Department of Neurology, Marqués de Valdecilla University Hospital, Santander, Spain sug: ab: Oculomotor behavior can provide insight into the integrity of widespread cortical networks, which may contribute to the differential diagnosis between Alzheimer's disease and frontotemporal dementia. Three groups of patients with Alzheimer's disease, behavioral variant of frontotemporal dementia (bvFTD) and semantic variant of primary progressive aphasia (svPPA) and a sample of cognitively unimpaired elders underwent an eye-tracking evaluation. All participants in the discovery sample, including controls, had a biomarker-supported diagnosis. Oculomotor correlates of neuropsychology and brain metabolism evaluated with 18F-FDG PET were explored. Machine-learning classification algorithms were trained for the differentiation between Alzheimer's disease, bvFTD and controls. A total of 93 subjects (33 Alzheimer's disease, 24 bvFTD, seven svPPA, and 29 controls) were included in the study. Alzheimer's disease was the most impaired group in all tests and displayed specific abnormalities in some visually-guided saccade parameters, as pursuit error and horizontal prosaccade latency, which are theoretically closely linked to posterior brain regions. BvFTD patients showed deficits especially in the most cognitively demanding tasks, the antisaccade and memory saccade tests, which require a fine control from frontal lobe regions. SvPPA patients performed similarly to controls in most parameters except for a lower number of correct memory saccades. Pursuit error was significantly correlated with cognitive measures of constructional praxis and executive function and metabolism in right posterior middle temporal gyrus. The classification algorithms yielded an area under the curve of 97.5% for the differentiation of Alzheimer's disease vs. controls, 96.7% for bvFTD vs. controls, and 92.5% for Alzheimer's disease vs. bvFTD. In conclusion, patients with Alzheimer's disease, bvFTD and svPPA exhibit differentiating oculomotor patterns which reflect the characteristic neuroanatomical distribution of pathology of each disease, and therefore its assessment can be useful in their diagnostic work-up. Machine learning approaches can facilitate the applicability of eye-tracking in clinical practice. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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