‘Language of the past’ - Exploring past tense disruption during autobiographical narration in neurodegenerative disorders

Episodic Thinking in Alzheimer's Disease Through the Lens of Language: Linguistic Analysis and Transformer-Based Classification

PURPOSE

Episodic memory decline is a hallmark of Alzheimer's disease (AD) and linked to deficits in episodic thinking directed to the future. We addressed the question whether a deficit in episodic thinking can be picked up directly from connected speech and its detection can be automatized.

METHOD

We linguistically classified 2,809 utterances (including embedded clauses in the utterances) from picture descriptions from 70 healthy older controls, 82 people with mild probable AD (pAD), and 46 people with moderate pAD for whether they were episodic, nonepisodic, or "other" (e.g., off-task). Generalized linear regression models were used to investigate how ratios of these categories change in AD, controlling for age, gender, and education. Finally, we applied deep learning technique to explore the feasibility of automating the episodicity analysis.

RESULTS

Decline in episodicity significantly distinguished controls from both mild pAD and moderate pAD. Correlation analysis suggested this decline not to be an effect of age, gender, and education but of cognitive ability. The decline was not compensated by an increase of nonepisodic utterances but mainly of off-task expressions. A transformer-based classifier to explore the possibility of automatizing the classification of episodicity achieved a macro F1 score of 0.913 in the ternary classification.

CONCLUSION

These results show that a loss of episodicity is an early effect in AD that is manifested in spontaneous speech and can be reliably measured by both humans and machines.

Mental Time Travel and Time Reference Difficulties in Alzheimer's Disease: Are They Related? A Systematic Review

Mental time travel and language enable us to go back and forth in time and to organize and express our personal experiences through time reference. People with Alzheimer's disease have both mental time travel and time reference impairments, which can greatly impact their daily communication. Currently, little is known about the potential relationship between time conceptualization (i.e., mental time travel) and time reference difficulties in this disease. A systematic review of the literature was performed to determine if this link had already been investigated. Only three articles integrated both time conceptualization and time reference measures. However, the link between the two was not systematically analyzed and interpreted. This review highlights the lack of research addressing the question of the influence of time conceptualization impairments in Alzheimer's disease on other cognitive domains, and especially language.

Cognitive and Neural Mechanisms of Social Communication Dysfunction in Primary Progressive Aphasia

Mounting evidence suggests that, in parallel with well-defined changes in language, primary progressive aphasia (PPA) syndromes display co-occurring social cognitive impairments. Here, we explored multidimensional profiles of carer-rated social communication using the La Trobe Communication Questionnaire (LCQ) in 11 semantic dementia (SD), 12 logopenic progressive aphasia (LPA) and 9 progressive non-fluent aphasia (PNFA) cases and contrasted their performance with 19 Alzheimer’s disease (AD) cases, 26 behavioural variant frontotemporal dementia (bvFTD) cases and 31 healthy older controls. Relative to the controls, the majority of patient groups displayed significant overall social communication difficulties, with common and unique profiles of impairment evident on the LCQ subscales. Correlation analyses revealed a differential impact of social communication disturbances on functional outcomes in patient and carer well-being, most pronounced for SD and bvFTD. Finally, voxel-based morphometry analyses based on a structural brain MRI pointed to the degradation of a distributed brain network in mediating social communication dysfunction in dementia. Our findings suggest that social communication difficulties are an important feature of PPA, with significant implications for patient function and carer well-being. The origins of these changes are likely to be multifactorial, reflecting the breakdown of fronto-thalamic brain circuits specialised in the integration of complex information.

Subjective Time in Dementia: A Critical Review

The capacity for subjective time in humans encompasses the perception of time's unfolding from moment to moment, as well as the ability to traverse larger temporal expanses of past- and future-oriented thought via mental time travel. Disruption in time perception can result in maladaptive outcomes-from the innocuous lapse in timing that leads to a burnt piece of toast, to the grievous miscalculation that produces a traffic accident-while disruption to mental time travel can impact core functions from planning appointments to making long-term decisions. Mounting evidence suggests that disturbances to both time perception and mental time travel are prominent in dementia syndromes. Given that such disruptions can have severe consequences for independent functioning in everyday life, here we aim to provide a comprehensive exposition of subjective timing dysfunction in dementia, with a view to informing the management of such disturbances. We consider the neurocognitive mechanisms underpinning changes to both time perception and mental time travel across different dementia disorders. Moreover, we explicate the functional implications of altered subjective timing by reference to two key and representative adaptive capacities: prospective memory and intertemporal decision-making. Overall, our review sheds light on the transdiagnostic implications of subjective timing disturbances in dementia and highlights the high variability in performance across clinical syndromes and functional domains.

"More than words" - Longitudinal linguistic changes in the works of a writer diagnosed with semantic dementia

Leveraging recent advances in automated language analysis and anovel statistical approach utilizing an independent control group, we explored changes in lexical output across two published works of a man diagnosed with semantic dementia. We found significant increase in adverb usage and decline in familiarity, meaningfulness, age of acquisition and co-occurrence probability over 2 years. Collectively, these indices suggest that WR's narrative structure became progressively simpler, lexically less sophisticated, and that words commonly associated together no longer appeared in close proximity. Our study illustrates how degeneration of the semantic knowledge base impacts the production, content, and quality of literary works.

"All is not lost"-Rethinking the nature of memory and the self in dementia

Memory and the self have long been considered intertwined, leading to the assumption that without memory, there can be no self. This line of reasoning has led to the misconception that a loss of memory in dementia necessarily results in a diminished sense of self. Here, we challenge this assumption by considering discrete facets of self-referential memory, and their relative profiles of loss and sparing, across three neurodegenerative disorders: Alzheimer's disease, semantic dementia, and frontotemporal dementia. By exploring canonical expressions of the self across past, present, and future contexts in dementia, relative to healthy ageing, we reconcile previous accounts of loss of self in dementia, and propose a new framework for understanding and managing everyday functioning and behaviour. Notably, our approach highlights the multifaceted and dynamic nature in which the temporally-extended self is likely to change in healthy and pathological ageing, with important ramifications for development of person-centred care. Collectively, we aim to promote a cohesive sense of self in dementia across past, present, and future contexts, by demonstrating how, ultimately, 'All is not lost'.

Language in Amnestic Mild Cognitive Impairment and Dementia of Alzheimer’s Type: Quantitatively or Qualitatively Different?

Background/Aims: The purpose of this study was to explore language differences between individuals diagnosed with amnestic mild cognitive impairment multiple domain (aMCIm) and those with probable Alzheimer’s disease, with a goal of (i) characterizing the language profile of aMCIm and (ii) determining whether the profiles of dementia of Alzheimer’s type (DAT) and aMCIm individuals are on a continuum of one diagnostic entity or represent two distinct ­cognitive disorders. Methods: Language data from 28 patients with consensus diagnosis of aMCIm and DAT derived from a retrospective chart review were compared to that of healthy controls. Results: A non-parametric statistic established that there was no significant difference between groups in age, years of education or duration of symptoms and that expressive language was found to be relatively intact in both patient groups. In contrast, both groups exhibited significant impairments on receptive language tests and on linguistically complex tasks that rely on episodic memory and executive functions. Individuals with aMCIm and DAT present with configurations of language features that are largely in parallel to each other and reflect predominantly quantitative differences. Conclusion: Language tests provide an important contribution to the diagnostic process in their capacity to identify language impairments at an early stage. Understanding the nature of language decline is critically important to the intervention process as this information would inform cognitive intervention approaches aimed at promoting quality of life in people living with MCI and dementia.

Connected Language in Late Middle-Aged Adults at Risk for Alzheimer's Disease

Connected language is often impaired among people with Alzheimer's disease (AD), yet little is known about when language difficulties first emerge on the path to a clinical diagnosis. The objective of this study was to determine whether individuals with psychometric (preclinical) evidence of amnestic mild cognitive impairment (pMCI) showed deficits in connected language measures. Participants were 39 pMCI and 39 cognitively healthy (CH) adults drawn from the Wisconsin Registry for Alzheimer's Prevention, who were matched for age, literacy, and sex. Participants completed a connected language task in which they described the Cookie Theft picture from the Boston Diagnostic Aphasia Examination. Language samples were analyzed across three language domains: content, syntactic complexity, and speech fluency. Paired t-tests were used to compare CH and pMCI groups on all variables, and Cohen's d effect sizes were calculated for each comparison. The CH and pMCI groups differed significantly on measures of content (e.g., CH group produced more semantic units, more unique words and had larger idea density, on average, than the pMCI group). The picture description findings are consistent with previous retrospective studies showing semantic language differences in adults with autopsy-confirmed AD. Given that these comparisons are between cognitively healthy and pMCI individuals (before a clinical MCI diagnosis), these findings may represent subtle language difficulty in spontaneous speech, and may be predictive of larger language changes over time.

Quantitative text feature analysis of autobiographical interview data: prediction of episodic details, semantic details and temporal discounting

Autobiographical memory and episodic future thinking (i.e. the capacity to project oneself into an imaginary future) are typically assessed using the Autobiographical Interview (AI). In the AI, subjects are provided with verbal cues (e.g. “your wedding day”) and are asked to freely recall (or imagine) the cued past (or future) event. Narratives are recorded, transcribed and analyzed using an established manual scoring procedure (Levine et al., 2002). Here we applied automatic text feature extraction methods to a relatively large (n = 86) set of AI data. In a first proof-of-concept approach, we used regression models to predict internal (episodic) and semantic detail sum scores from low-level linguistic features. Across a range of different regression methods, prediction accuracy averaged at about 0.5 standard deviations. Given the known association of episodic future thinking with temporal discounting behavior, i.e. the preference for smaller-sooner over larger-later rewards, we also ran models predicting temporal discounting directly from linguistic features of AI narratives. Here, prediction accuracy was much lower, but involved the same text feature components as prediction of internal (episodic) details. Our findings highlight the potential feasibility of using tools from quantitative text analysis to analyze AI datasets, and we discuss potential future applications of this approach.

[Are language disorders in Alzheimer's disease simply aphasia?]

Alzheimer's disease is accompanied by gradual aphasia, becoming more severe when the cognitive disorders are more marked. However, the quality of care provided to the patient can modulate the evolution of these language difficulties. Aphasia is linked to a human communication deficiency and can be limited by taking into account the phatic function of language to keep the channels of communication open.