Written Discourse Task Helps to Identify Progression from Mild Cognitive Impairment to Dementia

Machine Learning Classification of Patients with Amnestic Mild Cognitive Impairment and Non-Amnestic Mild Cognitive Impairment from Written Picture Description Tasks

Individuals with Mild Cognitive Impairment (MCI), a transitional stage between cognitively healthy aging and dementia, are characterized by subtle neurocognitive changes. Clinically, they can be grouped into two main variants, namely patients with amnestic MCI (aMCI) and non-amnestic MCI (naMCI). The distinction of the two variants is known to be clinically significant as they exhibit different progression rates to dementia. However, it has been particularly challenging to classify the two variants robustly. Recent research indicates that linguistic changes may manifest as one of the early indicators of pathology. Therefore, we focused on MCI's discourse-level writing samples in this study. We hypothesized that a written picture description task can provide information that can be used as an ecological, cost-effective classification system between the two variants. We included one hundred sixty-nine individuals diagnosed with either aMCI or naMCI who received neurophysiological evaluations in addition to a short, written picture description task. Natural Language Processing (NLP) and a BERT pre-trained language model were utilized to analyze the writing samples. We showed that the written picture description task provided 90% overall classification accuracy for the best classification models, which performed better than cognitive measures. Written discourses analyzed by AI models can automatically assess individuals with aMCI and naMCI and facilitate diagnosis, prognosis, therapy planning, and evaluation.

Written discourse in diagnosis for acquired neurogenic communication disorders: current evidence and future directions

Purpose

We aimed to perform the first review of research focusing on written discourse performance in people with acquired neurogenic communication disorders. In studies from 2000 onward, we specifically sought to determine: (1) the differences between patient populations and control groups, (2) the differences between different patient populations, (3) longitudinal differences between patient populations, and (4) modality differences between spoken and written discourse performance.

Methods

We completed a thorough search on MEDLINE, Embase, Cochrane, APAPsycinfo, Web of Science, and Scopus databases. We identified studies that focus on written discourse performance in people with aphasia, primary progressive aphasia, mild cognitive impairment, and Alzheimer's disease.

Results

Nineteen studies were identified from the review of literature, some of which addressed more than one of our review questions. Fifteen studies included a comparison between clinical populations and controls. Six studies compared different characteristics of patient populations. Three studies reported changes over time in progressive disorders. Six studies targeted different modalities of discourse.

Conclusion

Differences in linguistic features by patient populations are not yet clear due to the limited number of studies and different measures and tasks used across the studies. Nevertheless, there is substantial evidence of numerous linguistic features in acquired neurogenic communication disorders that depart from those of healthy controls. Compared to the controls, people with aphasia tend to produce fewer words, and syntactically simpler utterances compared to the controls. People with Alzheimer's disease produce less information content, and this feature increases over time, as reported in longitudinal studies. Our review imparts additional information that written and spoken discourse provide unique insights into the cognitive and linguistic deficits experienced by people with aphasia, Alzheimer's disease, mild cognitive impairment and primary progressive aphasia and provide targets for treatment to improve written communication in these groups.