Automated Indices of Clustering and Switching of Semantic Verbal Fluency in Parkinson’s Disease

Farzanfar, Delaram; Statucka, Marta; Cohn, Mélanie

doi:10.1017/s1355617718000759

Cited by 9 publications

(13 citation statements)

References 43 publications

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“…The Troyer method relies heavily on experimenters' subjective judgment of semantic relatedness and cluster segmentation. Farzanfar et al compared an automated computational assessment with the traditional experimenter-based assessment of semantic fluency data from patients with PD [ 8 ]. In the computational assessment, each word was represented as a vector in a semantic space derived from corpora.…”

Section: Introductionmentioning

confidence: 99%

Graph Theoretical Analysis of Semantic Fluency in Patients with Parkinson’s Disease

Zhang

Chan

et al. 2022

Behavioural Neurology

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Semantic fluency is the ability to name items from a given category within a limited time, which relies on semantic memory, working memory, and executive function. Semantic disfluency is a common problem in Parkinson’s disease (PD) and Alzheimer’s disease (AD). We demonstrated a graph theoretical analysis of semantic fluency in patients with PD ( N = 86 ), patients with AD ( N = 40 ), and healthy controls (HC, N = 88 ). All participants completed a standard animal fluency test. Their verbal responses were recorded, transcripted, and transformed into directed speech graphs. Patients with PD generated fewer correct words than HC and more correct words than patients with AD. Patients with PD showed higher density, shorter diameter, and shorter average shortest path length than HC, but lower density, longer diameter, and longer average shortest path length than patients with AD. It suggests that patients with PD produced relatively smaller and denser speech graphs. Moreover, in PD, the densities of speech graphs correlated with the severity of non-motor symptoms, but not the severity of motor symptoms. The graph theoretical analysis revealed new features of semantic disfluency in patients with PD.

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Section: Introductionmentioning

confidence: 99%

Graph Theoretical Analysis of Semantic Fluency in Patients with Parkinson’s Disease

Zhang

Chan

et al. 2022

Behavioural Neurology

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“…After the identification of word clusters, characteristics such as the mean cluster size and number of switches between clusters are calculated. Several studies suggested that the size of clusters is associated with language functions [10,14,16], whereas the number of switches is more strongly associated with executive functions [10,17]. Other authors, however, obtained conflicting results [12,17,18], and some studies found the cluster size and number of clusters to be highly correlated, which means that they might not represent independent parameters at all [7,17,19].…”

Section: Clusters In the Verbal Fluency Task Transcriptmentioning

confidence: 99%

A Semantic Relatedness Model for the Automatic Cluster Analysis of Phonematic and Semantic Verbal Fluency Tasks Performed by People With Parkinson Disease: Prospective Multicenter Study

Hähnel¹,

Feige²,

Kunze³

et al. 2023

JMIR Neurotech

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Background Phonematic and semantic verbal fluency tasks (VFTs) are widely used to capture cognitive deficits in people with neurodegenerative diseases. Counting the total number of words produced within a given time frame constitutes the most commonly used analysis for VFTs. The analysis of semantic and phonematic word clusters can provide additional information about frontal and temporal cognitive functions. Traditionally, clusters in the semantic VFT are identified using fixed word lists, which need to be created manually, lack standardization, and are language specific. Furthermore, it is not possible to identify semantic clusters in the phonematic VFT using this technique. Objective The objective of this study was to develop a method for the automated analysis of semantically related word clusters for semantic and phonematic VFTs. Furthermore, we aimed to explore the cognitive domains captured by this analysis for people with Parkinson disease (PD). Methods People with PD performed tablet-based semantic (51/85, 60%) and phonematic (69/85, 81%) VFTs. For both tasks, semantic word clusters were determined using a semantic relatedness model based on a neural network trained on the Wikipedia (Wikimedia Foundation) text corpus. The cluster characteristics derived from this model were compared with those derived from traditional evaluation methods of VFTs and a set of neuropsychological parameters. Results For the semantic VFT, the cluster characteristics obtained through automated analyses showed good correlations with the cluster characteristics obtained through the traditional method. Cluster characteristics from automated analyses of phonematic and semantic VFTs correlated with the overall cognitive function reported by the Montreal Cognitive Assessment, executive function reported by the Frontal Assessment Battery and the Trail Making Test, and language function reported by the Boston Naming Test. Conclusions Our study demonstrated the feasibility of standardized automated cluster analyses of VFTs using semantic relatedness models. These models do not require manually creating and updating categorized word lists and, therefore, can be easily and objectively implemented in different languages, potentially allowing comparison of results across different languages. Furthermore, this method provides information about semantic clusters in phonematic VFTs, which cannot be obtained from traditional methods. Hence, this method could provide easily accessible digital biomarkers for executive and language functions in people with PD.

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“…Technology may provide opportunity for clarification on the subtle components of performance in verbal fluency tasks and on the value of switching and clustering as reliable indices of differential performance between normal and pathological aging conditions. For example, Farzanfar et al (2018) used an automated computational approach to yield switching, mean cluster size and cumulative relatedness indices in individuals with cognitive decline in Parkinson's disease. These researchers found that automated switching indices showed evidence of concurrent and construct validity, characterized individual difference in advanced PD, and outperformed the experimenter-dependent index in predicting MCI associated to PD.…”

Section: Verbal Fluency Tasksmentioning

confidence: 99%

Marrying Past and Present Neuropsychology: Is the Future of the Process-Based Approach Technology-Based?

et al. 2020

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A cognitive assessment strategy that is not limited to examining a set of summary test scores may be more helpful for early detection of emergent illness such as Alzheimer's disease (AD) and may permit a better understanding of cognitive functions and dysfunctions in those with AD and other dementia disorders. A revisit of the work already undertaken by Kaplan and colleagues using the Boston Process-Approach provides a solid basis for identifying new opportunities to capture data on neurocognitive processes, test-taking strategies and response styles. Thus, this critical review will combine traditional process-based assessment strategies with support provided or offered by newer technologies that have the potential to add value to data collection and interpretation. There is now considerable interest in neuropsychological test administration using computer/digital technology, both in research and in clinical settings. To add value, any computerized version of an existing cognitive test should respect the administration procedure for which normative data were obtained, should be time-saving in terms of scoring and interpretation, and should, we argue, facilitate gathering information about the processes and strategies followed in test completion. This article will offer an overview of the steps needed when implementing computerization of neuropsychological tests using a Process-Based Approach (PBA) to these technology-based adaptations and will discuss further developments in this area by linking it to future technological developments that may be possible in the area of neuropsychological assessment. Additionally, an overview of neuropsychological tests that may benefit from computerization will be presented, together with suggestions on the specific processes, strategies and features that may be captured with the aid of such computerization. Finally, hypotheses on how virtual reality could be an asset for the future of the PBA to neuropsychological assessment will also be discussed.

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Automated Indices of Clustering and Switching of Semantic Verbal Fluency in Parkinson’s Disease

Cited by 9 publications

References 43 publications

Graph Theoretical Analysis of Semantic Fluency in Patients with Parkinson’s Disease

Graph Theoretical Analysis of Semantic Fluency in Patients with Parkinson’s Disease

A Semantic Relatedness Model for the Automatic Cluster Analysis of Phonematic and Semantic Verbal Fluency Tasks Performed by People With Parkinson Disease: Prospective Multicenter Study

Marrying Past and Present Neuropsychology: Is the Future of the Process-Based Approach Technology-Based?

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