What happens when nothing happens? An investigation of pauses as a compensatory mechanism in early Alzheimer's disease

Pistono, Aurélie; Pariente, Jérémie; Bézy, C.; Lemesle, B.; Men, J. Le; Jucla, Mélanie

doi:10.1016/j.neuropsychologia.2018.12.018

Cited by 55 publications

(71 citation statements)

References 41 publications

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“…It therefore means that disfluency can sometimes be used as a "stalling strategy" and is controlled in part by top down processes (Brown-Schmidt & Tanenhaus, 2006;Clark & Fox Tree, 2002). Although current effects do not involve filled pauses, contrary to Clark and Fox Tree's view, other authors showed that silent pauses could also reflect speaker's strategies at a discourse level rather than speech encoding processes (Pistono et al, 2016;Pistono et al, 2019). This finding also indicates that studies focusing on disfluency using this paradigm need to control the configuration of the network, as it influences the use of pauses.…”

Section: Random Structure Resultscontrasting

confidence: 71%

Eye-movements can help disentangle mechanisms underlying disfluency

Pistono

Hartsuiker

2021

Language, Cognition and Neuroscience

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To reveal the underlying cause of disfluency, several authors related the pattern of disfluencies to difficulties at specific levels of production, using a Network Task. Given that disfluencies are multifactorial, we combined this paradigm with eye-tracking to disentangle disfluency related to word preparation difficulties from others (e.g. stalling strategies). We manipulated lexical and grammatical selection difficulty. In Experiment 1, lines connecting the pictures varied in length, which led participants to use a strategy and inspect other areas than the upcoming picture when pictures were preceded by long lines. Experiment 2 only used short lines. In both experiments, lexical selection difficulty promoted self-corrections, pauses and longer fixation latency prior to naming. Multivariate Pattern Analyses demonstrated that disfluency and eyemovement data patterns can predict lexical selection difficulty. Eye-tracking could provide complementary information about network tasks, by disentangling disfluencies related to picture naming from disfluencies related to self-monitoring or stalling strategies.

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Section: Random Structure Resultscontrasting

confidence: 71%

Eye-movements can help disentangle mechanisms underlying disfluency

Pistono

Hartsuiker

2021

Language, Cognition and Neuroscience

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“…However, we revealed three qualitative differences in AD participants’ productions. First, their lexical content was lower than healthy controls, which is similar to what Pistono et al (2019) found using the same narrative task. AD participants also produced more modalizing discourse and more self-corrections while speaking.…”

Section: Discussionsupporting

confidence: 82%

“…nouns, most verbs, adjectives, numerals and adverbs of manner). Standardized indexes were calculated according to the following formula: (Open class – Closed class)/(Open class + Closed class), similarly to Pistono et al, (2019);…”

Section: Methodsmentioning

confidence: 99%

Language network connectivity increases in prodromal Alzheimer’s disease

Pistono¹,

Senoussi

Guerrier

et al. 2020

Preprint

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Language production deficits occur early in the course of Alzheimer’s disease (AD); however, only few studies have focused on language functional networks in prodromal AD. The current study aims to uncover the extent of language alteration at a prodromal stage, on a behavioral, structural and functional level, using univariate and multivariate analyses. Twenty-four AD participants and 24 matched healthy controls underwent a comprehensive language evaluation, a structural T1-3D MRI and resting-state fMRI. We performed seed-based analyses, using the left inferior frontal gyrus and left posterior temporal gyrus as seeds. Then, we analyzed connectivity between executive control networks and language network in each group. Finally, we used multivariate pattern analyses to test whether the two groups could be distinguished based on the pattern of atrophy within the language network; atrophy within the executive control networks, as well as the pattern of functional connectivity within the language network; and functional connectivity within executive control networks. AD participants had language impairment during standardized language tasks and connected-speech production. Univariate analyses were not able to discriminate participants at this stage, while multivariate pattern analyses could significantly predict the group membership of prodromal patients and healthy controls, both when classifying atrophy patterns or connectivity patterns of the language network. Language functional networks could discriminate AD participants better than executive control networks. Most notably, they revealed an increased connectivity at a prodromal stage. Multivariate analyses represent a useful tool for investigating the functional and structural (re-)organization of the neural bases of language.HighlightsLanguage network connectivity discriminates prodromal AD from healthy controlsLanguage network connectivity increases in prodromal ADAtrophy patterns in the language network do not correlate with connectivity patterns in AD

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“…These changes in the voice are explained mainly by lexical-semantic impairments and the deterioration of executive processes and attention. It is noteworthy that there are studies that use the manual extraction of parameters such as pauses (Pistono et al, 2019), which they also attribute to lexical-semantic processes, and are understood as compensatory mechanisms to improve lexical selection and memory recall. Finally, the clinical use of this tool is another major step.…”

Section: Amplitude Parametersmentioning

confidence: 99%

Ten Years of Research on Automatic Voice and Speech Analysis of People With Alzheimer's Disease and Mild Cognitive Impairment: A Systematic Review Article

et al. 2021

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Background: The field of voice and speech analysis has become increasingly popular over the last 10 years, and articles on its use in detecting neurodegenerative diseases have proliferated. Many studies have identified characteristic speech features that can be used to draw an accurate distinction between healthy aging among older people and those with mild cognitive impairment and Alzheimer's disease. Speech analysis has been singled out as a cost-effective and reliable method for detecting the presence of both conditions. In this research, a systematic review was conducted to determine these features and their diagnostic accuracy.Methods: Peer-reviewed literature was located across multiple databases, involving studies that apply new procedures of automatic speech analysis to collect behavioral evidence of linguistic impairments along with their diagnostic accuracy on Alzheimer's disease and mild cognitive impairment. The risk of bias was assessed by using JBI and QUADAS-2 checklists.Results: Thirty-five papers met the inclusion criteria; of these, 11 were descriptive studies that either identified voice features or explored their cognitive correlates, and the rest were diagnostic studies. Overall, the studies were of good quality and presented solid evidence of the usefulness of this technique. The distinctive acoustic and rhythmic features found are gathered. Most studies record a diagnostic accuracy over 88% for Alzheimer's and 80% for mild cognitive impairment.Conclusion: Automatic speech analysis is a promising tool for diagnosing mild cognitive impairment and Alzheimer's disease. The reported features seem to be indicators of the cognitive changes in older people. The specific features and the cognitive changes involved could be the subject of further research.

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What happens when nothing happens? An investigation of pauses as a compensatory mechanism in early Alzheimer's disease

Cited by 55 publications

References 41 publications

Eye-movements can help disentangle mechanisms underlying disfluency

Eye-movements can help disentangle mechanisms underlying disfluency

Language network connectivity increases in prodromal Alzheimer’s disease

Ten Years of Research on Automatic Voice and Speech Analysis of People With Alzheimer's Disease and Mild Cognitive Impairment: A Systematic Review Article

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