يعرض 1 - 5 نتائج من 5 نتيجة بحث عن '"Nicklas Linz"', وقت الاستعلام: 1.07s تنقيح النتائج
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    الوصف: Objective:Semantic verbal fluency (SVF) tasks require individuals to name items from a specified category within a fixed time. An impaired SVF performance is well documented in patients with amnestic Mild Cognitive Impairment (aMCI). The two leading theoretical views suggest either loss of semantic knowledge or impaired executive control to be responsible.Method:We assessed SVF 3 times on 2 consecutive days in 29 healthy controls (HC) and 29 patients with aMCI with the aim to answer the question which of the two views holds true.Results:When doing the task for the first time, patients with aMCI produced fewer and more common words with a shorter mean response latency. When tested repeatedly, only healthy volunteers increased performance. Likewise, only the performance of HC indicated two distinct retrieval processes: a prompt retrieval of readily available items at the beginning of the task and an active search through semantic space towards the end. With repeated assessment, the pool of readily available items became larger in HC, but not patients with aMCI.Conclusion:The production of fewer and more common words in aMCI points to a smaller search set and supports the loss of semantic knowledge view. The failure to improve performance as well as the lack of distinct retrieval processes point to an additional impairment in executive control. Our data did not clearly favour one theoretical view over the other, but rather indicates that the impairment of patients with aMCI in SVF is due to a combination of both.

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    المصدر: French Journal of Psychiatry. 1:S49-S50

    الوصف: Background Major depressive disorder (MDD) is a highly disabling disease of which is related to chronic course. Currently, there is no robust prognosis biomarker. Cognitive dysfunction associated with the disease has been shown to predict treatment outcome. However, its cerebral substrate is poorly known. Verbal fluency (VF), which are broadly used neuropsychological test, assess the production of words according to a required criterion within a constrained time frame. During this task, subjects produce words within subcategories or “clusters” and occasionally “switch” to other clusters. The measurement of the cluster size and number of switches are relevant cognitive markers. Deep learning-based computational analysis method have been shown to improve the reproducibility and scalability of this measurement. The main objective of the current study was to characterize the cortical thickness (CT) surface-based morphometry (SBM) correlates of the switching and clustering scores in patients with MDD using an artificial intelligence empowered speech analysis system. The secondary objective was to compare those cognitive scores with the ones of the control group. Method The study included 26 depressed women and 25 matched in age and education level healthy females’ controls. All subjects underwent VF tests and had a structural Magnetic Resonance Imaging (MRI). The clustering and switching scores were assessed using the computational analysis method introduced by Linz et al ( https://ki-elements.deTest ). SBM was performed using SPM and CAT12 toolbox. Results In the depressed group, we observed a positive correlation between the switching score in semantic VF test and the CT, in few cortical areas. The main significant correlation was found in the left lingual gyrus (P = 0.003). The switching scores were lower in the depressed group in each VF task (P = 0.019 and P = 0.007). There was no difference between the two groups concerning the cluster size. Conclusion Our study revealed the relationship existing between the number of switches produced by depressed subjects in a semantic VF task and the CT in prefrontal regions and in more posterior areas. These results possibly suggest that switching and clustering scores assessment in VF tasks, and its cerebral correlates, may constitute potential prognosis biomarkers for depression. Although much work is still required, the establishment of such biomarkers has substantial implications for reducing the burden of the disease.

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    المصدر: Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology.

    الوصف: The Semantic Verbal Fluency (SVF) task is a classical neuropsychological assessment where persons are asked to produce words belonging to a semantic category (e.g., animals) in a given time. This paper introduces a novel method of temporal analysis for SVF tasks utilizing time intervals and applies it to a corpus of elderly Swedish subjects (mild cognitive impairment, subjective cognitive impairment and healthy controls). A general decline in word count and lexical frequency over the course of the task is revealed, as well as an increase in word transition times. Persons with subjective cognitive impairment had a higher word count during the last intervals, but produced words of the same lexical frequencies. Persons with MCI had a steeper decline in both word count and lexical frequencies during the third interval. Additional correlations with neuropsychological scores suggest these findings are linked to a person’s overall vocabulary size and processing speed, respectively. Classification results improved when adding the novel features (AUC=0.72), supporting their diagnostic value.

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