Language Processing in Parkinson's Disease Patients Without Dementia

AbstractObjectives:The worldwide spread of Parkinson’s disease (PD) calls for sensitive and specific measures enabling its early (or, ideally, preclinical) detection. Here, we use language measures revealing deficits in PD to explore whether similar disturbances are present in asymptomatic individualsat riskfor the disease.Methods:We administered executive, semantic, verb-production, and syntactic tasks to sporadic PD patients, genetic PD patients with PARK2 (parkin) or LRRK2 (dardarin) mutation, asymptomatic first-degree relatives of the latter with similar mutations, and socio-demographically matched controls. Moreover, to detectsui generislanguage disturbances, we ran analysis of covariance tests using executive functions as covariate.Results:The two clinical groups showed impairments in all measures, most of which survived covariation with executive functions. However, the key finding concerned asymptomatic mutation carriers. While these subjects showed intact executive, semantic, and action-verb production skills, they evinced deficits in a syntactic test with minimal working memory load.Conclusions:We propose that thissui generisdisturbance may constitute a prodromal sign anticipating eventual development of PD. Moreover, our results suggest that mutations on specific genes (PARK2 and LRRK2) compromising basal ganglia functioning may be subtly related to language-processing mechanisms. (JINS, 2017,23, 150–158)

Download Full-text

Functional connectivity of spoken language processing in early-stage Parkinson’s disease: an MEG study

NeuroImage Clinical ◽

10.1016/j.nicl.2021.102718 ◽

2021 ◽

pp. 102718

Author(s):

Rasha Hyder ◽

Mads Jensen ◽

Andreas Højlund ◽

Lilli Kimppa ◽

Christopher J. Bailey ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Functional Connectivity ◽

Language Processing ◽

Early Stage ◽

Spoken Language ◽

Spoken Language Processing

Download Full-text

Predictive Value of Verbatim Parkinson’s Disease Patient-Reported Symptoms of Postural Instability and Falling

Journal of Parkinson s Disease ◽

10.3233/jpd-212636 ◽

2021 ◽

pp. 1-8

Author(s):

Monica Javidnia ◽

Lakshmi Arbatti ◽

Abhishek Hosamath ◽

Shirley W. Eberly ◽

David Oakes ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Natural Language Processing ◽

Natural Language ◽

Parkinson Disease ◽

Language Processing ◽

Rating Scale ◽

Disease Patient ◽

Postural Instability ◽

Patient Reported

Background: Postural instability is an intractable sign of Parkinson’s disease, associated with poor disease prognosis, fall risk, and decreased quality of life. Objective: 1) Characterize verbatim reports of postural instability and associated symptoms (gait disorder, balance, falling, freezing, and posture), 2) compare reports with responses to three pre-specified questions from Part II of the Movement Disorder Society Unified Parkinson Disease Rating Scale (MDS-UPDRS), and 3) examine postural instability symptoms and MDS-UPDRS responses as predictors of future falls. Methods: Fox Insight research participants reported their problems attributed to PD in their own words using the Parkinson Disease Patient Reports of Problems (PD-PROP). Natural language processing, clinical curation, and data mining techniques were applied to classify text into problem domains and clinically-curated symptoms. Baseline postural instability symptoms were mapped to MDS-UPDRS questions 2.11–2.13. T-tests and chi-square tests were used to compare postural instability reporters and non-reporters, and Cochran-Armitage trend tests were used to evaluate associations between PD-PROP and MDS-UPDRS responses; survival methods were utilized to evaluate the predictive utility of PD-PROP and MDS-UPDRS responses in time-to-fall analyses. Results: Of participants within 10 years of PD diagnosis, 9,692 (56.0%) reported postural instability symptoms referable to gait unsteadiness, balance, falling, freezing, or posture at baseline. Postural instability symptoms were significantly associated with patient-reported measures from the MDS-UPDRS questions. Balance problems reported on PD-PROP and MDS-UPDRS 2.11–2.13 measures were predictive of future falls. Conclusion: Verbatim-reported problems captured by the PD-PROP and categorized by natural language processing and clinical curation and MDS-UPDRS responses predicted falls. The PD-PROP output was more granular than, and as informative as, the categorical responses.

Download Full-text

Neural signatures of predictive language processing in parkinson’s disease with and without mild cognitive impairment

10.1101/2020.11.23.392647 ◽

2020 ◽

Author(s):

Patricia León-Cabrera ◽

Javier Pagonabarraga ◽

Joaquín Morís ◽

Saúl Martínez-Horta ◽

Juan Marín-Lahoz ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Language Processing ◽

Semantic Processing ◽

Sentence Comprehension ◽

Event Related Potentials ◽

Final Word ◽

Related Potentials

ABSTRACTCognitive deficits are common in Parkinson’s disease (PD), with some PD patients meeting criteria for mild cognitive impairment (MCI). An unaddressed question is whether linguistic prediction is preserved in PD. This ability is nowadays deemed crucial in achieving fast and efficient comprehension, and it may be negatively impacted by cognitive deterioration. To fill this gap of knowledge, we used event-related potentials (ERPs) to evaluate mechanisms of linguistic prediction in a sample of PD patients (on dopamine compensation) with and without MCI. To this end, participants read sentence contexts that were predictive or not about a sentence-final word. The final word appeared after 1 second, matching or mismatching the prediction. The introduction of the interval allowed to capture neural responses both before and after sentence-final words, reflecting semantic anticipation and processing. PD patients with normal cognition (N = 58) showed ERP responses comparable to those of matched controls. Specifically, in predictive contexts, a slow negative potential developed prior to sentence-final words, reflecting semantic anticipation. Later, expected words elicited reduced N400 responses (compared to unexpected words), indicating facilitated semantic processing. Besides, PD patients with MCI (N = 20) showed a prolongation of the N400 congruency effect (compared to matched PD patients without MCI), indicating that further cognitive decline impacts semantic processing. Finally, lower verbal fluency scores correlated with prolonged N400 congruency effects and with reduced pre-word differences in all PD patients (N = 78). This relevantly points to a role of deficits in temporal-dependent mechanisms in PD, besides prototypical frontal dysfunction, in altered semantic anticipation and semantic processing during sentence comprehension.

Download Full-text

I.P9 Effect of visuo-spatial cues on language processing in Parkinson's Disease Patients

Parkinsonism & Related Disorders ◽

10.1016/s1353-8020(07)70073-1 ◽

2006 ◽

Vol 12 ◽

pp. 23

Author(s):

E. Wattendorf ◽

A. Welge-Lüssen ◽

D. Bilecen ◽

B. Westermann ◽

M. Lotze

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Language Processing ◽

Spatial Cues

Download Full-text

STN‐DBS affects language processing differentially in Parkinson's disease: Multiple‐case MEG study

Acta Neurologica Scandinavica ◽

10.1111/ane.13423 ◽

2021 ◽

Author(s):

Rasha Hyder ◽

Andreas Højlund ◽

Mads Jensen ◽

Erik L. Johnsen ◽

Karen Østergaard ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Language Processing ◽

Multiple Case ◽

Stn Dbs

Download Full-text

Drug repurposing against Parkinson's disease by text mining the scientific literature

Library Hi Tech ◽

10.1108/lht-08-2019-0170 ◽

2020 ◽

Vol 38 (4) ◽

pp. 741-750 ◽

Cited By ~ 2

Author(s):

Yongjun Zhu ◽

Woojin Jung ◽

Fei Wang ◽

Chao Che

Keyword(s):

Machine Learning ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Natural Language Processing ◽

Knowledge Representation ◽

Natural Language ◽

Language Processing ◽

Scientific Literature ◽

Drug Repurposing ◽

Content Type

PurposeDrug repurposing involves the identification of new applications for existing drugs. Owing to the enormous rise in the costs of pharmaceutical R&D, several pharmaceutical companies are leveraging repurposing strategies. Parkinson's disease is the second most common neurodegenerative disorder worldwide, affecting approximately 1–2 percent of the human population older than 65 years. This study proposes a literature-based drug repurposing strategy in Parkinson's disease.Design/methodology/approachThe literature-based drug repurposing strategy proposed herein combined natural language processing, network science and machine learning methods for analyzing unstructured text data and producing actional knowledge for drug repurposing. The approach comprised multiple computational components, including the extraction of biomedical entities and their relationships, knowledge graph construction, knowledge representation learning and machine learning-based prediction.FindingsThe proposed strategy was used to mine information pertaining to the mechanisms of disease treatment from known treatment relationships and predict drugs for repurposing against Parkinson's disease. The F1 score of the best-performing method was 0.97, indicating the effectiveness of the proposed approach. The study also presents experimental results obtained by combining the different components of the strategy.Originality/valueThe drug repurposing strategy proposed herein for Parkinson's disease is distinct from those existing in the literature in that the drug repurposing pipeline includes components of natural language processing, knowledge representation and machine learning for analyzing the scientific literature. The results of the study provide important and valuable information to researchers studying different aspects of Parkinson's disease.

Download Full-text

How Parkinson's Disease Affects Non-verbal Communication and Language Processing

Language and Linguistics Compass ◽

10.1111/j.1749-818x.2008.00074.x ◽

2008 ◽

Vol 2 (5) ◽

pp. 739-759 ◽

Cited By ~ 22

Author(s):

Marc D. Pell ◽

Laura Monetta

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Language Processing ◽

Verbal Communication

Download Full-text

LEXICAL-SEMANTIC PROCESSING OF ACTIONS/VERBS IN PARKINSON’S DISEASE

10.5327/1980-5764.rpda095 ◽

2021 ◽

Author(s):

Dayse Souza ◽

Henrique Salmazo- Silva ◽

Roberta Baradel ◽

Reynaldo Sandrini ◽

Katerina Lukasova ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Language Processing ◽

Semantic Processing ◽

Healthy Controls ◽

Semantic Association ◽

Lexical Semantic ◽

Semantic Access ◽

Therapeutic Alternatives ◽

Action Verbs

Background: Individuals with Parkinson’s Disease present motor and cognitive impairment. In the language domain PD is a good model to study the functional contribution of the motor system to language processing. Objective: To investigate the performance of Parkinson’s disease patients on a lexical-semantic processing task of action verbs, compared to cognitively healthy controls. Methods: Parkinson’s patients performed the naming (n=25) and semantic association (n=19) tests of the Kisssing and Dancing Test - KDT, adapted by Baradel (2016). Patients were compared to cognitively healthy controls (n=44). Results: We observed a difference in performance on the naming (t[47]=-2.609, p=0.012) and semantic verb association (t[36]=-4.795, p=0.000) tasks between the groups. Parkinson’s patients had lower mean scores than healthy controls on both the naming and semantic association tasks. Conclusion: Parkinson’s patients may exhibit difficulties in lexical and semantic access of language with action content compared to healthy subjects. These results are consistent with Embodied Cognition and may support therapeutic alternatives in the field of language neuroscience.

Download Full-text