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Multimodal MRI cerebral correlates of verbal fluency switching and its impairment in women with depression
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In: ISSN: 2213-1582 ; Neuroimage-Clinical ; https://hal.archives-ouvertes.fr/hal-03477309 ; Neuroimage-Clinical, Elsevier, 2021, 33, pp.1-11. ⟨10.1016/j.nicl.2021.102910⟩ (2021)
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Language Impairment in Alzheimer’s Disease—Robust and Explainable Evidence for AD-Related Deterioration of Spontaneous Speech Through Multilingual Machine Learning
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In: ISSN: 1663-4365 ; Frontiers in Aging Neuroscience ; https://hal.archives-ouvertes.fr/hal-03477304 ; Frontiers in Aging Neuroscience, Frontiers, 2021, 13 (11), pp.6108. ⟨10.3389/fnagi.2021.642033⟩ (2021)
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Measuring neuropsychiatric symptoms in patients with early cognitive decline using speech analysis
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In: Eur Psychiatry (2021)
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Language Impairment in Alzheimer’s Disease—Robust and Explainable Evidence for AD-Related Deterioration of Spontaneous Speech Through Multilingual Machine Learning
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In: Front Aging Neurosci (2021)
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Abstract:
Alzheimer’s disease (AD) is a pervasive neurodegenerative disease that affects millions worldwide and is most prominently associated with broad cognitive decline, including language impairment. Picture description tasks are routinely used to monitor language impairment in AD. Due to the high amount of manual resources needed for an in-depth analysis of thereby-produced spontaneous speech, advanced natural language processing (NLP) combined with machine learning (ML) represents a promising opportunity. In this applied research field though, NLP and ML methodology do not necessarily ensure robust clinically actionable insights into cognitive language impairment in AD and additional precautions must be taken to ensure clinical-validity and generalizability of results. In this study, we add generalizability through multilingual feature statistics to computational approaches for the detection of language impairment in AD. We include 154 participants (78 healthy subjects, 76 patients with AD) from two different languages (106 English speaking and 47 French speaking). Each participant completed a picture description task, in addition to a battery of neuropsychological tests. Each response was recorded and manually transcribed. From this, task-specific, semantic, syntactic and paralinguistic features are extracted using NLP resources. Using inferential statistics, we determined language features, excluding task specific features, that are significant in both languages and therefore represent “generalizable” signs for cognitive language impairment in AD. In a second step, we evaluated all features as well as the generalizable ones for English, French and both languages in a binary discrimination ML scenario (AD vs. healthy) using a variety of classifiers. The generalizable language feature set outperforms the all language feature set in English, French and the multilingual scenarios. Semantic features are the most generalizable while paralinguistic features show no overlap between languages. The multilingual model shows an equal distribution of error in both English and French. By leveraging multilingual statistics combined with a theory-driven approach, we identify AD-related language impairment that generalizes beyond a single corpus or language to model language impairment as a clinically-relevant cognitive symptom. We find a primary impairment in semantics in addition to mild syntactic impairment, possibly confounded by additional impaired cognitive functions.
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Keyword:
Neuroscience
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URL: https://doi.org/10.3389/fnagi.2021.642033
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170097/
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Exploitation vs. exploration—computational temporal and semantic analysis explains semantic verbal fluency impairment in Alzheimer's disease
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In: ISSN: 0028-3932 ; EISSN: 1873-3514 ; Neuropsychologia ; https://hal.archives-ouvertes.fr/hal-02339134 ; Neuropsychologia, Elsevier, 2019, 131, pp.53-61. ⟨10.1016/j.neuropsychologia.2019.05.007⟩ (2019)
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Fully Automatic Speech-Based Analysis of the Semantic Verbal Fluency Task
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In: ISSN: 1420-8008 ; EISSN: 1421-9824 ; Dementia and Geriatric Cognitive Disorders ; https://hal.inria.fr/hal-01850408 ; Dementia and Geriatric Cognitive Disorders, Karger, 2018, 45 (3-4), pp.198 - 209. ⟨10.1159/000487852⟩ (2018)
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Telephone-based Dementia Screening I: Automated Semantic Verbal Fluency Assessment
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In: PervasiveHealth 2018 - 12th EAI International Conference on Pervasive Computing Technologies for Healthcare ; https://hal.inria.fr/hal-01850406 ; PervasiveHealth 2018 - 12th EAI International Conference on Pervasive Computing Technologies for Healthcare, May 2018, New York United States. ⟨10.1145/nnnnnnn.nnnnnnn⟩ (2018)
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Automatic Detection of Apathy using Acoustic Markers extracted from Free Emotional Speech
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In: 2ND WORKSHOP ON AI FOR AGING, REHABILITATION AND INDEPENDENT ASSISTED LIVING (ARIAL) @IJCAI'18 ; https://hal.inria.fr/hal-01850436 ; 2ND WORKSHOP ON AI FOR AGING, REHABILITATION AND INDEPENDENT ASSISTED LIVING (ARIAL) @IJCAI'18, Jul 2018, Stockholm Sweden (2018)
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Use of Speech Analyses within a mobile application for the Assessment of cognitive impairment in elderly people
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In: ISSN: 1567-2050 ; Current Alzheimer Research ; https://hal.inria.fr/hal-01672580 ; Current Alzheimer Research, Bentham Science Publishers, 2017, 14, pp.120 - 129. ⟨10.2174/1567205014666170829111942⟩ (2017)
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