Integrated Cognitive Assessment: Speed and Accuracy of Visual Processing as a Reliable Proxy to Cognitive Performance

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作者
Seyed-Mahdi Khaligh-Razavi
Sina Habibi
Maryam Sadeghi
Haniye Marefat
Mahdiyeh Khanbagi
Seyed Massood Nabavi
Elham Sadeghi
Chris Kalafatis
机构
[1] Computer Science and Artificial Intelligence Laboratory,Department of Brain and Cognitive Sciences, Cell Science Research Center
[2] Massachusetts Institute of Technology,undefined
[3] Royan Institute for Stem Cell Biology and Technology,undefined
[4] ACECR,undefined
[5] Cognetivity ltd,undefined
[6] University of Tehran,undefined
[7] School of Cognitive Sciences (SCS),undefined
[8] Institute for Research in Fundamental Sciences (IPM),undefined
[9] South London & Maudsley NHS Foundation Trust,undefined
来源
Scientific Reports | / 9卷
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摘要
Various mental disorders are accompanied by some degree of cognitive impairment. Particularly in neurodegenerative disorders, cognitive impairment is the phenotypical hallmark of the disease. Effective, accurate and timely cognitive assessment is key to early diagnosis of this family of mental disorders. Current standard-of-care techniques for cognitive assessment are primarily paper-based, and need to be administered by a healthcare professional; they are additionally language and education-dependent and typically suffer from a learning bias. These tests are thus not ideal for large-scale pro-active cognitive screening and disease progression monitoring. We developed the Integrated Cognitive Assessment (referred to as CGN_ICA), a 5-minute computerized cognitive assessment tool based on a rapid visual categorization task, in which a series of carefully selected natural images of varied difficulty are presented to participants. Overall 448 participants, across a wide age-range with different levels of education took the CGN_ICA test. We compared participants’ CGN_ICA test results with a variety of standard pen-and-paper tests, such as Symbol Digit Modalities Test (SDMT) and Montreal Cognitive Assessment (MoCA), that are routinely used to assess cognitive performance. CGN_ICA had excellent test-retest reliability, showed convergent validity with the standard-of-care cognitive tests used here, and demonstrated to be suitable for micro-monitoring of cognitive performance.
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