Analysis of macrolinguistic aspects of narratives from individuals with Alzheimer's disease, mild cognitive impairment, and no cognitive impairment

A preliminary investigation on core lexicon analysis in dementia of the Alzheimer's type

BACKGROUND

Core lexicon (CL) analysis is a time efficient and possibly reliable measure that captures discourse production abilities. For people with aphasia, CL scores have demonstrated correlations with aphasia severity, as well as other discourse and linguistic measures. It was also found to be clinician-friendly and clinically sensitive enough to capture longitudinal changes in aphasia. To our knowledge, CL has never been investigated in individuals with neurologically progressive disease.

AIMS

As a preliminary investigation, we sought to investigate (1) whether CL scores correlate with dementia severity, (2) whether CL scores correlate with measures of discourse quality, and (3) whether CL scores correlate with other measures of lexical/semantic access.

METHODS & PROCEDURES

Twelve participants with a cognitive impairment associated with dementia of the Alzheimer's type (DAT) completed several measures of language and cognitive ability, as well as provide a language sample from the wordless picture book, Picnic.

RESULTS & CONCLUSION

Results are informative, as they provide insight into characteristics of CL and provide support for potential use of CL in individuals with neurologically progressive disease. The results indicated that CL scores do correlate with dementia severity and several measures of language ability, indicating they may provide a useful measure of language abilities in DAT, but more research is needed.

WHAT THIS PAPER ADDS

What is already known on the subject Core lexicon (CL) analysis is an assessment measure of discourse ability, most closely related to informativeness or productivity, used in aphasiology that is easier to use and less time consuming than previous measures of informativeness, such as correct information units or type-token ratio (TTR). For people with aphasia, CL analysis correlates with aphasia severity, measures of informativeness, as well as other measures of discourse quality. It has also been shown to be faster and more reliable between scorers than other informativeness measures. What this study adds Core lexicon analysis is a new simple and online method for assessing the informativeness of a discourse sample without the need to record or transcribe the language sample. CL is receiving a lot of attention in aphasia, correlating with everything from aphasia severity to measures of productivity and lexical access, as well as measures of informativeness. Unfortunately, no one has investigated CL analysis in dementia. The study demonstrates the first evidence that CL analysis may be a useful measure for determining dementia severity and language quality in people with dementia. What are the clinical implications of this work? Core lexicon analysis may provide clinicians and researchers with an easy method for assessing the discourse of people with a cognitive impairment associated with dementia of the Alzheimer's type. This will improve initial assessment, as well as improve ongoing language assessment that may provide clues into their functional ability to communicate effectively.

Exploring Spoken Discourse and Its Neural Correlates in Women With Alzheimer's Disease With Low Levels of Education and Socioeconomic Status

PURPOSE

Early impairments in spoken discourse abilities have been identified in Alzheimer's disease (AD). However, the impact of AD on spoken discourse and the associated neuroanatomical correlates have mainly been studied in populations with higher levels of education, although preliminary evidence seems to indicate that socioeconomic status (SES) and level of education have an impact on spoken discourse. The purpose of this study was to analyze microstructural variables in spoken discourse in people with AD with low-to-middle SES and low level of education and to study their association with gray matter (GM) density.

METHOD

Nine women with AD and 10 matched (age, SES, and education) women without brain injury (WWBI) underwent a neuropsychological assessment, which included two spoken discourse tasks, and structural magnetic resonance imaging. Microstructural variables were extracted from the discourse samples using NILC-Metrix software. Brain density, measured by voxel-based morphometry, was compared between groups and then correlated with the differentiating microstructural variables.

RESULTS

The AD group produced a lower diversity of verbal time moods and fewer words and sentences than WWBI but a greater diversity of pronouns, prepositions, and lexical richness. At the neural level, the AD group presented a lower GM density bilaterally in the hippocampus, the inferior temporal gyrus, and the anterior cingulate gyrus. Number of words and sentences produced were associated with GM density in the left parahippocampal gyrus, whereas the diversity of verbal moods was associated with the basal ganglia and the anterior cingulate gyrus bilaterally.

CONCLUSIONS

The present findings are mainly consistent with previous studies conducted in groups with higher levels of SES and education, but they suggest that atrophy in the left inferior temporal gyrus could be critical in AD in populations with lower levels of SES and education. This research provides evidence on the importance of pursuing further studies including people with various SES and education levels.

WHAT IS ALREADY KNOWN ON THIS SUBJECT

Spoken discourse has been shown to be affected in Alzheimer disease, but most studies have been conducted on individuals with middle-to-high SES and high educational levels.

WHAT THIS STUDY ADDS

The study reports on microstructural measures of spoken discourse in groups of women in the early stage of AD and healthy women, with low-to-middle SES and lower levels of education.

CLINICAL IMPLICATIONS OF THIS STUDY

This study highlights the importance of taking into consideration the SES and education level in spoken discourse analysis and in investigating the neural correlates of AD.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.24905046.

Characteristics Scanning of Brain Structure and Function Changes in Patients with Different Degrees of Alzheimer's Disease

Through the case control study on structural magnetic resonance imaging (sMRI) scanning, MR spectrum (MRS), and neuropsychological assessment of the intracranial structures of Alzheimer's disease (AD), patients of different degrees (early, middle, and late), the early clinical features, imaging features, and neuropsychological characteristics of patients with AD were analyzed to provide help for the early diagnosis of AD. The data of MR scanning of the brain, bilateral MRS scan of the hippocampus, thyroid function and other laboratory indicators, and neuropsychological evaluation analysis were collected in 50 patients who had been diagnosed with AD. According to CDR, 50 patients were divided into the early AD group and the middle and advanced AD group, with 23 patients in the early AD group and 27 patients in the middle and advanced AD group. Retrospective study was conducted to analyze the general conditions, medial temporal lobe atrophy (MTA) grading, and the metabolic changes of bilateral MRS in the hippocampus of patients in both groups, so did the mini-mental state examination (MMSE), activities of daily living scale (ADL), and other neuropsychological assessment results. Moreover, the comparative analysis was carried out. The results showed that the MTA grade of medial temporal atrophy increased with the progressive severity of the disease in both groups. A statistical test was conducted on the reduction of hippocampal volume in the two groups, and the P was less than 0.05. Therefore, the MTA scale was of great value in the diagnosis and staging of early AD. However, when the diagnosis of early AD was treated by MTA visual evaluation alone, there was 23.8% false negative diagnosis. If the judgment of early AD only depended on the metabolic changes of hippocampus MRS or MR scanning of intracranial structures, it was likely to cause false negative diagnosis. Therefore, the combination of MRS analysis and MR scanning of intracranial structures was favorable for the early diagnosis and treatment of AD. Combined with neuropsychological assessment, AD patients were staged more effectively, which greatly improved the accuracy of AD diagnosis in the early stage.

Lower Education and Reading and Writing Habits Are Associated With Poorer Oral Discourse Production in Typical Adults and Older Adults

During normal aging there is a decline in cognitive functions that includes deficits in oral discourse production. A higher level of education and more frequent reading and writing habits (RWH) might delay the onset of the cognitive decline during aging. This study aimed at investigating the effect of education and RWH on oral discourse production in older adults. Picture-based narratives were collected from 117 healthy adults, aged between 51 and 82 years (68.6 ± 6.38) with 0-20 years of formal education (10.1 ± 5.69). Measures of macro, microlinguistic and modalizations were computed and entered as dependent variables in hierarchical regression analyses that included age, education and RWH as regressors. Results revealed that higher education explained a better performance at the macrostructure and microstructure dimensions. Higher frequency of RWH explained the production of fewer modalizations. These results demonstrate the positive effect of education and RWH in oral discourse production in older adults. Therefore, higher attention should be given to these social factors.

Speech- and Language-Based Classification of Alzheimer's Disease: A Systematic Review

Background: Alzheimer’s disease (AD) has paramount importance due to its rising prevalence, the impact on the patient and society, and the related healthcare costs. However, current diagnostic techniques are not designed for frequent mass screening, delaying therapeutic intervention and worsening prognoses. To be able to detect AD at an early stage, ideally at a pre-clinical stage, speech analysis emerges as a simple low-cost non-invasive procedure. Objectives: In this work it is our objective to do a systematic review about speech-based detection and classification of Alzheimer’s Disease with the purpose of identifying the most effective algorithms and best practices. Methods: A systematic literature search was performed from Jan 2015 up to May 2020 using ScienceDirect, PubMed and DBLP. Articles were screened by title, abstract and full text as needed. A manual complementary search among the references of the included papers was also performed. Inclusion criteria and search strategies were defined a priori. Results: We were able: to identify the main resources that can support the development of decision support systems for AD, to list speech features that are correlated with the linguistic and acoustic footprint of the disease, to recognize the data models that can provide robust results and to observe the performance indicators that were reported. Discussion: A computational system with the adequate elements combination, based on the identified best-practices, can point to a whole new diagnostic approach, leading to better insights about AD symptoms and its disease patterns, creating conditions to promote a longer life span as well as an improvement in patient quality of life. The clinically relevant results that were identified can be used to establish a reference system and help to define research guidelines for future developments.

Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment

Detecting early signs of cognitive decline is crucial for early detection and treatment of Alzheimer's Disease. Most of the current screening tools for Alzheimer's Disease represent a significant burden, requiring invasive procedures, or intensive and costly clinical testing. Recent findings have highlighted changes to speech and language patterns that occur in Alzheimer's Disease, and may be detectable prior to diagnosis. Automated tools to assess speech have been developed that can be used on a smartphone or tablet, from one's home, in under 10 min. In this study, we present the results of a study of older adults who completed a digital speech assessment task over a 6-month period. Participants were grouped according to those who scored above (N = 18) or below (N = 18) the recommended threshold for detecting cognitive impairment on the Montreal Cognitive Assessment (MoCA) and those with diagnoses of mild cognitive impairment (MCI) or early Alzheimer's Disease (AD) (N = 14). Older adults who scored above the MoCA threshold had better performance on speech composites reflecting language coherence, information richness, syntactic complexity, and word finding abilities. Those with MCI and AD showed more rapid decline in the coherence of language from baseline to 6-month follow-up, suggesting that this score may be useful both for detecting cognitive decline and monitoring change over time. This study demonstrates that automated speech assessments have potential as sensitive tools to detect early signs of cognitive impairment and monitor progression over time.

Preliminary assessment of connected speech and language as marker for cognitive change in late middle-aged Black/African American adults at risk for Alzheimer's disease

Background

Connected speech-language (CSL) has been a promising measure of assessing cognitive decline in populations at-risk for Alzheimer's disease and related dementias (ADRD) populations. A common way to obtain CSL is through using picture description tasks such as the most frequently used image Cookie Theft (CT). However, questions have been raised about using CT for diverse communities. Little is known about the CSL produced in response to this task in Black/African American (BAA) adults aged 48-74.

Goals

The present study's goals were to characterize CSL in BAA adults by sex and APOE-ε4 status from Milwaukee in the Wisconsin Registry for Alzheimer's Prevention (WRAP) study when presented with the CT picture description task and to identify differences in CSL output between BAAs and non-Hispanic Whites (NHW).

Methods and Procedures

We collected CSL samples from the CT picture from 48 BAA participants and 30 NHW participants from the WRAP participants in Milwaukee, WI group. CSL was analyzed using chi-square tests, T-tests, and ANCOVA. Linear mixed effect regression models were used to determine the association between cognitive status and longitudinal CSL in BAA participants with more than 1 timepoint.

Outcomes and Results

Declines in CSL of BAA participants were associated with subtle declines in cognition. Among BAA participants, we found no significant differences in speech measures in terms of sex and APOE-ε4 status. Our results showed no significant differences in speech measures between BAA and NHW groups.

Conclusions

CSL analysis provides an inexpensive way to evaluate preclinical changes in cognitive status that may not be as affected by other factors, such as ethnocultural background. Future studies with larger sample sizes and participants from other geographic locations can clarify these findings.

A Comparison of Connected Speech Tasks for Detecting Early Alzheimer’s Disease and Mild Cognitive Impairment Using Natural Language Processing and Machine Learning

Alzheimer’s disease (AD) has a long pre-clinical period, and so there is a crucial need for early detection, including of Mild Cognitive Impairment (MCI). Computational analysis of connected speech using Natural Language Processing and machine learning has been found to indicate disease and could be utilized as a rapid, scalable test for early diagnosis. However, there has been a focus on the Cookie Theft picture description task, which has been criticized. Fifty participants were recruited – 25 healthy controls (HC), 25 mild AD or MCI (AD+MCI) – and these completed five connected speech tasks: picture description, a conversational map reading task, recall of an overlearned narrative, procedural recall and narration of a wordless picture book. A high-dimensional set of linguistic features were automatically extracted from each transcript and used to train Support Vector Machines to classify groups. Performance varied, with accuracy for HC vs. AD+MCI classification ranging from 62% using picture book narration to 78% using overlearned narrative features. This study shows that, importantly, the conditions of the speech task have an impact on the discourse produced, which influences accuracy in detection of AD beyond the length of the sample. Further, we report the features important for classification using different tasks, showing that a focus on the Cookie Theft picture description task may narrow the understanding of how early AD pathology impacts speech.

Can discourse processing performance serve as an early marker of Alzheimer’s disease and mild cognitive impairment? A systematic review of text comprehension

A number of linguistic and cognitive deficits have been reported during the course of Alzheimer’s disease (AD) and its preceding stage of mild cognitive impairment (MCI), with some deficits appearing years before onset of clinical symptoms. It continues to be a critical task to identify tools that may serve as an early marker of pathology that are also reliably able to distinguish AD from normal ageing. Given the limited success of classic psychometric cognitive testing, a novel approach in assessment is warranted. A potentially sensitive assessment paradigm is discourse processing. The aim of this review was to synthesize original research studies investigating comprehension of discourse in AD and MCI, and to evaluate the potential of this paradigm as a promising avenue for further research. A literature search targeting studies with AD or MCI groups over 60 years of age was conducted in PubMed, Web of Science, and PsycINFO databases. Eight articles with good quality were included in the review. Six measures of discourse comprehension—naming latency, summary, lesson, main idea, proportion of inferential clauses, true/false questions—were identified. All eight studies reported significant deficits in discourse comprehension in AD and MCI groups on five of the six measures, when compared to cognitively healthy older adults. Mixed results were observed for associations with commonly used cognitive measures. Given the consistent findings for discourse comprehension measures across all studies, we strongly recommend further research on its early predictive potential, and discuss different avenues for research.

Using a Discourse Task to Explore Semantic Ability in Persons With Cognitive Impairment

This paper uses a discourse task to explore aspects of semantic production in persons with various degree of cognitive impairment and healthy controls. The purpose of the study was to test if an in-depth semantic analysis of a cognitive-linguistic challenging discourse task could differentiate persons with a cognitive decline from those with a stable cognitive impairment. Both quantitative measures of semantic ability, using tests of oral lexical retrieval, and qualitative analysis of a narrative were used to detect semantic difficulties. Besides group comparisons a classification experiment was performed to investigate if the discourse features could be used to improve classification of the participants who had a stable cognitive impairment from those who had cognitively declined. In sum, both types of assessment methods captured difficulties between the groups, but tests of oral lexical retrieval most successfully differentiated between the cognitively stable and the cognitively declined group. Discourse features improved classification accuracy and the best combination of features discriminated between participants with a stable cognitive impairment and those who had cognitively declined with an area under the curve (AUC) of 0.93.

Autobiographical narratives in the elderly with neurocognitive disorder: an integrative literature review

ABSTRACT Objective: to carry out an integrative review of the literature on autobiographical narratives as a discursive activity in the older adult with neurocognitive disorder. Methods: a descriptive study that covered the Scopus, SciELO, PubMed, and Science Direct databases, from 2009 to 2019, using the keywords autobiographical, narrative, dementia, reminiscence, the elderly, and the Boolean operator. A narrative synthesis was adopted considering the characteristics of the clinical, and methodological heterogeneity of the studies. Results: the results included 3 articles published between 2012 and 2018, in the English language, from the United Kingdom, Brazil, and Argentina, which highlighted the autobiographical narratives. Although in a strict sense they did not present the narrative as a specific objective of the autobiographical study, they did provide interesting and related data which justified their inclusion. Conclusion: it is observed that the literature researched presents a limited number of articles, adressing the autobiographical narrative as a discursive activity in the elderly with neurocognitive disorder.

Narrative impairment, white matter damage and CSF biomarkers in the Alzheimer's disease spectrum

BACKGROUND

Narrative discourse (ND) refers to one's ability to verbally reproduce a sequence of temporally and logically-linked events. Impairments in ND may occur in subjects with Amnestic Mild Cognitive Impairment (aMCI) and Alzheimer's Disease (AD), but correlates across this function, neuroimaging and cerebrospinal fluid (CSF) AD biomarkers remain understudied.

OBJECTIVES

We sought to measure correlates among ND, Diffusion Tensor Imaging (DTI) indexes and AD CSF biomarkers in patients within the AD spectrum.

RESULTS

Groups differed in narrative production (NProd) and comprehension. aMCI and AD presented poorer inference abilities than controls. AD subjects were more impaired than controls and aMCI regarding WB (p<0.01). ROIs DTI assessment distinguished the three groups. Mean Diffusivity (MD) in the uncinate, bilateral parahippocampal cingulate and left inferior occipitofrontal fasciculi negatively correlated with NProd. Changes in specific tracts correlated with T-tau/Aβ1-42 ratio in CSF.

CONCLUSIONS

AD and aMCI patients presented more ND impairments than controls. Those findings were associated with changes in ventral language-associated and in the inferior parahippocampal pathways. The latest were correlated with biomarkers' levels in the CSF.

METHODS

AD (N=14), aMCI (N=31) and Control (N=39) groups were compared for whole brain (WB) and regions of interest (ROI) DTI parameters, ND and AD CSF biomarkers.

Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?

Background: The discovery of early, non-invasive biomarkers for the identification of “preclinical” or “pre-symptomatic” Alzheimer's disease and other dementias is a key issue in the field, especially for research purposes, the design of preventive clinical trials, and drafting population-based health care policies. Complex behaviors are natural candidates for this. In particular, recent studies have suggested that speech alterations might be one of the earliest signs of cognitive decline, frequently noticeable years before other cognitive deficits become apparent. Traditional neuropsychological language tests provide ambiguous results in this context. In contrast, the analysis of spoken language productions by Natural Language Processing (NLP) techniques can pinpoint language modifications in potential patients. This interdisciplinary study aimed at using NLP to identify early linguistic signs of cognitive decline in a population of elderly individuals.

Methods: We enrolled 96 participants (age range 50–75): 48 healthy controls (CG) and 48 cognitively impaired participants: 16 participants with single domain amnestic Mild Cognitive Impairment (aMCI), 16 with multiple domain MCI (mdMCI) and 16 with early Dementia (eD). Each subject underwent a brief neuropsychological screening composed by MMSE, MoCA, GPCog, CDT, and verbal fluency (phonemic and semantic). The spontaneous speech during three tasks (describing a complex picture, a typical working day and recalling a last remembered dream) was then recorded, transcribed and annotated at various linguistic levels. A multidimensional parameter computation was performed by a quantitative analysis of spoken texts, computing rhythmic, acoustic, lexical, morpho-syntactic, and syntactic features.

Results: Neuropsychological tests showed significant differences between controls and mdMCI, and between controls and eD participants; GPCog, MoCA, PF, and SF also discriminated between controls and aMCI. In the linguistic experiments, a number of features regarding lexical, acoustic and syntactic aspects were significant in differentiating between mdMCI, eD, and CG (non-parametric statistical analysis). Some features, mainly in the acoustic domain also discriminated between CG and aMCI.

Conclusions: Linguistic features of spontaneous speech transcribed and analyzed by NLP techniques show significant differences between controls and pathological states (not only eD but also MCI) and seems to be a promising approach for the identification of preclinical stages of dementia. Long duration follow-up studies are needed to confirm this assumption.