Diagnostic Performance of an Eye-Tracking Assisted Visual Inference Language Test in the Assessment of Cognitive Decline due to Alzheimer's Disease

Background: The assessment of language changes associated with visual search impairment can be an important diagnostic tool in the Alzheimer's disease (AD) continuum. Objective: Investigate the performance of an eye-tracking assisted visual inference language task in differentiating subjects with mild cognitive impairment (MCI) or AD dementia from cognitively unimpaired older adults (controls). Methods: We assessed a group of 95 older adults (49 MCI, 18 mild dementia due to AD, and 28 controls). The subjects performed the same task under multiple experimental conditions which generate correlated responses that need to be taken into account. Thus, we performed a non-parametric repeated measures ANOVA model for verbal answers, and a linear mixed model (LMM) or its generalized version for the analysis of eye tracking variables. Results: Significant differences were found in verbal answers across all diagnostic groups independently of type of inference, i.e., logic or pragmatic. Also, eye-tracking parameters were able to discriminate AD from MCI and controls. AD patients did more visits to challenge stimulus (Control-AD, -0.622, SE = 0.190, p = 0.004; MCI-AD, -0.514, SE = 0.173, p = 0.011), more visits to the correct response stimulus (Control-AD, -1.363, SE = 0.383, p = 0.002; MCI-AD, -0.946, SE = 0.349, p = 0.022), more fixations on distractors (Control-AD, -4.580, SE = 1.172, p = 0.001; MCI-AD, -2.940, SE = 1.070, p = 0.020), and a longer time to first fixation on the correct response stimulus (Control-AD, -0.622, SE = 0.190, p = 0.004; MCI-AD, -0.514, SE = 0.173, p = 0.011). Conclusion: The analysis of oculomotor behavior along with language assessment protocols may increase the sensitivity for detection of subtle deficits in the MCI-AD continuum, representing an important diagnostic tool.