PAIRED ASSOCIATES LEARNING: ADDING SENSITIVITY BY MEASURING REACTION TIMES

PAIRED ASSOCIATES LEARNING: ADDING SENSITIVITY BY MEASURING REACTION TIMES

Poster Presentations: Sunday, July 16, 2017 when data points not meeting integrity criteria were excluded. Conclusions: There was little difference i...

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Poster Presentations: Sunday, July 16, 2017

when data points not meeting integrity criteria were excluded. Conclusions: There was little difference in longitudinal slopes of any of the CogState tasks by mode of administration (PC or iPad). Therefore, once small cross-sectional differences in performance on computerized testing are accounted for, longitudinal data can be combined across different modes of administration. Further exploration of potential subtle differences across modes of administration and the differential frequency of meeting integrity criteria is needed.

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Paul Maruff1, Lisa Barnsby2, Yen Ying Lim3, Peter J. Snyder4, Karra D. Harrington5, Victor L. L. Villemagne6, Christopher C. Rowe7, Colin L. Masters8, 1The Florey Institute of Neuroscience and Mental Health, Parkville, Australia; 2Florey Institute for Neurosciences and Mental Health, Melbourne, Australia; 3Florey Institute of Neuroscience and Mental Health, Parkville, Australia; 4Alpert Medical School of Brown University, Providence, RI, USA; 5The Florey Institutes of Neuroscience and Mental Health, Melbourne, Australia; 6University of Melbourne, Austin Health, Melbourne, Australia; 7Austin Health, Melbourne, Australia; 8The University of Melbourne, Parkville, Australia. Contact e-mail: pmaruff@ cogstate.com Background: Secondary prevention clinical trials of amyloid (AB)

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PAIRED ASSOCIATES LEARNING: ADDING SENSITIVITY BY MEASURING REACTION TIMES

Pasquale Dente1, Francesca K. Cormack1, Rosemary A. Abbott1, Jennifer H. Barnett2, 1Cambridge Cognition, Cambridge, United Kingdom; 2Cambridge Cognition & University of Cambridge, Cambridge, United Kingdom. Contact e-mail: francesca. [email protected] Background: When evaluating memory performance, analysis is

typically restricted to the accuracy of recall. Computerised testing brings an unprecedented ability to capture more detailed information about responses: exactly where, when and in which order responses were made. This could provide novel insights into cognitive processes, and greater discriminatory power in predicting cognitive deficits and decline in Alzheimer’s and other diseases. Here we examined detailed performance on the Cantab Paired Associates Learning (PAL), a computerized task of visual memory and learning. We aimed to understand how the timing of response were related to task parameters, recall success and normal ageing. Methods: 94 healthy participants (female ¼ 46; age range ¼ 20-79 years) completed the Cantab PAL task. A series of linear mixedeffect models (GLMM) in R using maximum likelihood estimation tested the effect of age, gender, correctness of response, item position and difficulty of the level on reaction times (RT). In all models, subject and level difficulty were modelled as nested random factors to control for their associated interclass correlation. Models were compared with ANOVA using the Bayesian Information Criterion (BIC) to select the most parsimonious model. Results: Response times were significantly predicted by all factors (p < .001) with the exception of gender. Reaction times were shorter for younger participants; for example, the mean RT for participants <30 years was 1524ms, and 1824ms for participants above 60 years. There was a significant interaction (p < .001) between level of difficulty and serial position of the item; within each level of difficulty the mean reaction time decreased from the first to the last item recalled. Conclusions: Trial-by trial analysis of reaction time data in a computerised test of memory showed effects related to task structure and difficulty, as well as an impact of age on the speed of response. These systematic relationships suggest that the additional parameters captured by computerised assessments may complement traditional performance metrics, to better quantify the impact of pathology and treatment on memory.

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SENSITIVITY OF AN ALZHEIMER’S DISEASE COOPERATIVE STUDY: PRECLINICAL ALZHEIMER’S COGNITIVE COMPOSITE (PACC) BASED ON COMPUTERIZED TESTS TO AMYLOID LOAD IN PRECLINICAL AD

lowering drugs use the ADCS-PACC, a composite of verbal list learning, paragraph recall, executive function and the MMSE] as their primary endpoint. This study simulated the effect of lowering AB levels on estimates of cognition and clinical disease progression using data from participants who satisfy enrollment criteria for the A4 or EARLY studies but who had varying levels of amyloid. we compared the effect of lowering amyloid on PACC composite scores consisting of computerized and paper and pencil tests. Methods: Cognitively normal (CN) adults with data for 36 months of follow-up enrolled in the Australian Imaging Biomarkers and Lifestyle (AIBL) study and defined as having abnormally high AB from PET scanning were classified into two subgroups, AB+ (SUVR>1.4 and <1.9, n ¼ 138) and AB++ (SUVR ¼ />1.9, n ¼ 89]. AB groups were compared on rates of disease clinical progression using X2 and on rates of cognitive decline using ANCOVA. PAAC scores consisting of comnputerized tests from the Cogstate battery were compared to that consisting of verbal list learning, logical memory, coding and MMSE. Statistical models were adjusted for clinical or demographic factors that also differed between the groups. Results: ANCOVA models showed that rates of disease progression were lower in the AB+ [10%] than in AB++ group [5.6 %; OR 5.1 95%CI 3.4 -6.7]. ANCOVA showed that the rate of decline on the conventional ADCS-PACC was lower in the AB+ group than in the AB++ group: with [d ¼ 0.89] or without [d ¼ 0.65] progressors included in analyses. Using the Cogstate tests to measure episodic memory and executive function difference in rate of decline between AB+ and AB++ groups was equivalent with [d ¼ 0.86] or without [d ¼ 0.66] progressors included in analyses. Conclusions: This data provides a basis for the extent to which a change in amyloid levels, measured by amyloid plaque burden, could manifest in terms of change in cognition or clinical disease progression. Is also shows computerized measures can be used in PACC scores.

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ASSESSING ATTENTIONAL DEFICITS IN ALZHEIMER’S PATIENT: A CASE STUDY

Pooja Rai, Indramani Lal Singh, Tara Singh, Trayambak Tiwari, Banaras Hindu University, Varanasi, India. Contact e-mail: pooja. [email protected] Background: Alzheimer’s disease (AD) is one of the most common neurodegenerative disease and is considered to be the main cause of cognitive impairment in elderly people. Earlier Alzheimer’s disease has been viewed as age related memory disorder. Now research related to attention has revealed impaired selective attention which later accompanied by memory deficits in AD. Therefore, attention related cognitive assessment needs to be explored. Methods: In the present case study, a 76 years old female with Alzheimer disease