Cognitive and Structural Correlates of Conversational Speech Timing in Mild Cognitive Impairment and Mild-to-Moderate Alzheimer's Disease: Relevance for Early Detection Approaches

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.

Keywords: Alzheimer; brain volumes; cognitive function; conversation; speech timing.

Figure 1

General diagram of the classification process in Evolutionary Algorithms (EAs). In order to find the optimal model (or candidate), a set of working models are randomly generated (Step 1: initialize population). The models (or candidates) are then evaluated to assess their accuracy rate (Step 2: evaluate). In order to achieve the maximum accuracy rate, certain models (or candidates) are selected for use in the subsequent generation of models (Step 3: select) via recombination (also known as sexual reproduction or crossover) and/or mutation. Recombination is an operator that is applied to two or more selected models (the so-called parents or genotype or chromosomes), by mixing their genetic material (genes), to create one or more new models (the children or new chromosomes or offspring). Mutation is applied to one model (asexual reproduction) or two models (sexual reproduction) and results in one new model. This procedure is repeated for many iterations and the resulting model is evaluated each time (Step 4: evaluate) or until the desired accuracy rate is achieved at which stage a final optimal model is selected and the process is terminated (Step 5: termination). Adapted from Figure 4.5 of Dehsarvi (2018).

Figure 2

Example of a generation of classification with the optimal model (best fitted chromosome) selected (in black). This model has used a certain number/set of inputs or speech features (inputs 0, 13, 6, 16, 11, 3, and 1) and a combination of different functions to form the best model (or fittest chromosome). Other models with lower accuracy rates are depicted in light gray in the figure. The selected model (or chromosome) is the fittest one of a certain run and is stored as an output, along with all the other runs, upon completion of 5-fold cross-validation.

Figure 3

Marginal estimates of Interpausal Unit (IPU) duration (log-transformed) as a function of Working Memory/Attention scores (log-transformed) in the Describe, Match, and Describe and Match trials. Describe-Trial: individuals with AD/MCI and HC are the directors, i.e., they describe the shapes and instruct where to place them; Match-Trial: individuals with AD/MCI and HC are the matchers, i.e., they place the pictures on their board following the caregiver’s instructions; Describe and Match-Trial: both interlocutors describe the shapes and agree on where to place them.

Figure 4

Marginal estimates of Interpausal Unit (IPU) duration (log-transformed) as a function of the Left Fusiform Gyrus (L FFG) in the Describe, Match, and Describe and Match trials. Describe-Trial: individuals with AD/MCI and HC are the directors, i.e., they describe the shapes and instruct where to place them; Match-Trial: individuals with AD/MCI and HC are the matchers, i.e., they place the pictures on their board following the caregiver’s instructions; Describe and Match-Trial: both interlocutors describe the shapes and agree on where to place them.