Abstract
Background: Increasing efforts have focused on the establishment of novel biomarkers for the early detection of Alzheimer’s disease (AD) and prediction of Mild Cognitive Impairment (MCI)-to-AD conversion. Behavioral changes over the course of healthy ageing, at disease onset and during disease progression, have been recently put forward as promising markers for the detection of MCI and AD. The present study examines whether the temporal characteristics of speech in a collaborative referencing task are associated with cognitive function and the volumes of brain regions involved in speech production and known to be reduced in MCI and AD pathology. We then explore the discriminative ability of the temporal speech measures for the classification of MCI and AD.Method: Individuals with MCI, mild-to-moderate AD and healthy controls (HCs) underwent a structural MRI scan and a battery of neuropsychological tests. They also engaged in a collaborative referencing task with a caregiver. The associations between the conversational speech timing features, cognitive function (domain-specific) and regional brain volumes were examined by means of linear mixed-effect modeling. Genetic programming was used to explore the discriminative ability of the conversational speech features.Results: MCI and mild-to-moderate AD are characterized by a general slowness of speech, attributed to slower speech rate and slower turn-taking in conversational settings. The speech characteristics appear to be reflective of episodic, lexico-semantic, executive functioning and visuospatial deficits and underlying volume reductions in frontal, temporal and cerebellar areas.Conclusion: The implementation of conversational speech timing-based technologies in clinical and community settings may provide additional markers for the early detection of cognitive deficits and structural changes associated with MCI and AD.
Highlights
Rationale and Research GoalsProgressive loss of cognitive function and progressive cerebral atrophy are characteristic features of Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD; Dubois et al, 2007; McKhann et al, 2011; Kirova et al, 2015; König et al, 2015; Szatloczki et al, 2015)
We found that, in overt sentence reading, a higher number of pauses, shorter interpausal units and slower speech rate were associated with reduced language and working memory/attention scores and that these temporal speech characteristics were reflective of difficulties in planning longer and more syntactically complex utterances in healthy older adults and individuals with MCI and AD (De Looze et al, 2018)
We investigate whether conversational speech timing is reflective of the underlying volume of brain regions involved in speech production and known to be reduced in MCI and AD pathology
Summary
Rationale and Research GoalsProgressive loss of cognitive function and progressive cerebral atrophy are characteristic features of Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD; Dubois et al, 2007; McKhann et al, 2011; Kirova et al, 2015; König et al, 2015; Szatloczki et al, 2015). Increasing efforts have focused on the establishment of novel biomarkers for the early detection of AD and prediction of MCI-to-AD conversion, including clinical, brain, genetic, and neuropsychological data. The cognitive and structural underpinnings of these speech-based measures in classification approaches have not been systematically investigated and are not fully established. Understanding these underpinnings could add significant clinical value and further support the potential use and implementation of speech-based technologies in and outside clinical settings for the monitoring of cognitive trajectories. Increasing efforts have focused on the establishment of novel biomarkers for the early detection of Alzheimer’s disease (AD) and prediction of Mild Cognitive Impairment (MCI)-to-AD conversion.
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