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P2‐515: CHARACTERISING SPOKEN LANGUAGE DEFICITS IN MILD ALZHEIMER'S DISEASE AND MILD COGNITIVE IMPAIRMENT
Author(s) -
Clarke Natasha,
Barrick Thomas Richard,
Garrard Peter
Publication year - 2018
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2018.06.1209
Subject(s) - dementia , psychology , cognition , spoken language , audiology , cognitive decline , cognitive impairment , disease , medicine , linguistics , pathology , psychiatry , philosophy
between participants with behavioural frontotemporal dementia (bvFTD), semantic dementia (SD) and healthy controls. In the present study, we aim to clarify whether the same test can help discriminate between the different sub-types of frontotemporal dementia (bvFTD, SD, progressive non-fluent aphasia (PNFA)), logopenic progressive aphasia (LPA) and between them and typical Alzheimer’s disease (tAD). Methods: Thirty-six patients (8 bvFTD, 8 SD, 4 LPA, 9 PNFA and 7 tAD) and 30 controls performed the spatial anticipation task (Fig 1). The task was part of an instructionless eyetracking test where participants looked at a computer screen in a free-viewing condition. Similar to Primativo et al. (2017), 7 positions on the screen were tested with a target moving around according to 12 possible patterns varying in degrees of complexity (Fig 1 shows two examples). Eye movements were recorded using a desk-mounted eyetracker (Eyelink 1000 plus). Results: Patients made fewer correct anticipations and more incorrect anticipations compared to healthy controls, consistent with Primativo et al. (2017) findings. The quantitative analysis of spatial anticipations can discriminate bvFTD patients from the other groups of patients and controls, while the qualitative analysis of the anticipatory errors can better differentiate patients’ subgroups. Conclusions: The relative ease of administration of this eyetracking task enables assessment of complex cognitive function in neurodegenerative diseases. Fine-grained oculomotor metrics can help discriminate between diagnostic groups and sub-groups and opens the route to the development of other instructionless eyetracking tests looking at multiple cognitive domains.