Multilingual Learning for Mild Cognitive Impairment Screening from a Clinical Speech Task

The Semantic Verbal Fluency Task (SVF) is an efficient and minimally invasive speech-based screening tool for Mild Cognitive Impairment (MCI). In the SVF, testees have to produce as many words for a given semantic category as possible within 60 seconds. State-of-the-art approaches for automatic evaluation of the SVF employ word embeddings to analyze semantic similarities in these word sequences. While these approaches have proven promising in a variety of test languages, the small amount of data available for any given language limits the performance. In this paper, we for the first time investigate multilingual learning approaches for MCI classification from the SVF in order to combat data scarcity. To allow for cross-language generalisation, these approaches either rely on translation to a shared language, or make use of several distinct word embeddings. In evaluations on a multilingual corpus of older French, Dutch, and German participants (Controls=66, MCI=66), we show that our multilingual approaches clearly improve over single-language baselines

Small vessel disease burden and functional brain connectivity in mild cognitive impairment

Background: The role of small vessel disease in the development of dementia is not yet completely understood. Functional brain connectivity has been shown to differ between individuals with and without cerebral small vessel disease. However, a comprehensive measure of small vessel disease quantifying the overall damage on the brain is not consistently used and studies using such measure in mild cognitive impairment individuals are missing.Method: Functional brain connectivity differences were analyzed between mild cognitive impairment individuals with absent or low (n = 34) and high (n = 34) small vessel disease burden using data from the Parelsnoer Institute, a Dutch multicenter study. Small vessel disease was characterized using an ordinal scale considering: lacunes, microbleeds, perivascular spaces in the basal ganglia, and white matter hyperintensities. Resting state functional MRI data using 3 Tesla scanners was analyzed with group-independent component analysis using the CONN toolbox.Results: Functional connectivity between areas of the cerebellum and between the cerebellum and the thalamus and caudate nucleus was higher in the absent or low small vessel disease group compared to the high small vessel disease group.Conclusion: These findings might suggest that functional connectivity of mild cognitive impairment individuals with low or absent small vessel disease burden is more intact than in mild cognitive impairment individuals with high small vessel disease. These brain areas are mainly responsible for motor, attentional and executive functions, domains which in previous studies were found to be mostly associated with small vessel disease markers. Our results support findings on the involvement of the cerebellum in cognitive functioning

Small vessel disease burden and functional brain connectivity in mild cognitive impairment

Background: The role of small vessel disease in the development of dementia is not yet completely understood. Functional brain connectivity has been shown to differ between individuals with and without cerebral small vessel disease. However, a comprehensive measure of small vessel disease quantifying the overall damage on the brain is not consistently used and studies using such measure in mild cognitive impairment individuals are missing. Method: Functional brain connectivity differences were analyzed between mild cognitive impairment individuals with absent or low (n = 34) and high (n = 34) small vessel disease burden using data from the Parelsnoer Institute, a Dutch multicenter study. Small vessel disease was characterized using an ordinal scale considering: lacunes, microbleeds, perivascular spaces in the basal ganglia, and white matter hyperintensities. Resting state functional MRI data using 3 Tesla scanners was analyzed with group-independent component analysis using the CONN toolbox. Results: Functional connectivity between areas of the cerebellum and between the cerebellum and the thalamus and caudate nucleus was higher in the absent or low small vessel disease group compared to the high small vessel disease group. Conclusion: These findings might suggest that functional connectivity of mild cognitive impairment individuals with low or absent small vessel disease burden is more intact than in mild cognitive impairment individuals with high small vessel disease. These brain areas are mainly responsible for motor, attentional and executive functions, domains which in previous studies were found to be mostly associated with small vessel disease markers. Our results support findings on the involvement of the cerebellum in cognitive functioning.</p

Small vessel disease burden and functional brain connectivity in mild cognitive impairment

Background: The role of small vessel disease in the development of dementia is not yet completely understood. Functional brain connectivity has been shown to differ between individuals with and without cerebral small vessel disease. However, a comprehensive measure of small vessel disease quantifying the overall damage on the brain is not consistently used and studies using such measure in mild cognitive impairment individuals are missing. Method: Functional brain connectivity differences were analyzed between mild cognitive impairment individuals with absent or low (n = 34) and high (n = 34) small vessel disease burden using data from the Parelsnoer Institute, a Dutch multicenter study. Small vessel disease was characterized using an ordinal scale considering: lacunes, microbleeds, perivascular spaces in the basal ganglia, and white matter hyperintensities. Resting state functional MRI data using 3 Tesla scanners was analyzed with group-independent component analysis using the CONN toolbox. Results: Functional connectivity between areas of the cerebellum and between the cerebellum and the thalamus and caudate nucleus was higher in the absent or low small vessel disease group compared to the high small vessel disease group. Conclusion: These findings might suggest that functional connectivity of mild cognitive impairment individuals with low or absent small vessel disease burden is more intact than in mild cognitive impairment individuals with high small vessel disease. These brain areas are mainly responsible for motor, attentional and executive functions, domains which in previous studies were found to be mostly associated with small vessel disease markers. Our results support findings on the involvement of the cerebellum in cognitive functioning.</p

The Dutch Parelsnoer Institute - Neurodegenerative diseases; methods, design and baseline results

Background: The is a collaboration between 8 Dutch University Medical Centers in which clinical data and biomaterials from patients suffering from chronic diseases (so called "Pearls") are collected according to harmonized protocols. The Pearl Neurodegenerative Diseases focuses on the role of biomarkers in the early diagnosis, differential diagnosis and in monitoring the course of neurodegenerative diseases, in particular Alzheimer's disease. Methods: The Pearl Neurodegenerative Diseases is a 3-year follow-up study of patients referred to a memory clinic with cognitive complaints. At baseline, all patients are subjected to a standardized examination, including clinical data and biobank materials, e.g. blood samples, MRI and cerebrospinal fluid. At present, in total more than 1000 patients have been included, of which cerebrospinal fluid and DNA samples are available of 211 and 661 patients, respectively. First descriptives of a subsample of the data (n = 665) shows that patients are diagnosed with dementia (45%), mild cognitive impairment (31%), and subjective memory complaints (24%). Discussion: The Pearl Neurodegenerative Diseases is an ongoing large network collecting clinical data and biomaterials of more than 1000 patients with cognitive impairments. The project has started with data analyses of the baseline characteristics and biomarkers, which will be the starting point of future specific research questions that can be answered by this unique dataset

The use of artificial intelligence and automatic speech and image analysis for remote cognitive testing

International audienc