Autocorrection If→of Function Words in Reading Aloud: A Novel Marker of Alzheimer's Risk

Objective: The present study investigated cognitive mechanisms underlying the ability to stop "autocorrect" errors elicited by unexpected words in a read-aloud task, and the utility of autocorrection for predicting Alzheimer's disease (AD) biomarkers.

Method: Cognitively normal participants (total = 85; = 64 with cerebrospinal fluid [CSF] biomarkers) read aloud six short paragraphs in which 10 critical target words were replaced with autocorrect targets, for example, . Autocorrect targets either replaced the most expected/ completion (i.e., ) or a less expected/ completion (i.e., ), and within each paragraph half of the autocorrect targets were content words (e.g., ) and half were function words (e.g., ). Participants were instructed to avoid autocorrecting.

Results: Participants produced more autocorrect errors in paragraphs with dominant than with nondominant targets, and with function than with content targets. Cognitively normal participants with high CSF Tau/Aβ42 (i.e., an AD-like biomarker profile) produced more autocorrect total errors than those below the Tau/Aβ42 threshold, an effect also significant with dominant-function targets alone (e.g., saying instead of ). A logistic regression model with dominant-function errors and age showed errors as the stronger predictor of biomarker status (sensitivity 83%; specificity 85%).

Conclusions: Difficulty stopping autocorrect errors is associated with biomarkers indicating preclinical AD, and reveals promise as a diagnostic tool. Greater vulnerability of function over content words to autocorrection in individuals with AD-like biomarkers implicates monitoring and attention (rather than semantic processing) in the earliest of cognitive changes associated with AD risk. (PsycInfo Database Record (c) 2023 APA, all rights reserved).