TDCS in a patient with dreadlocks: Improvements in COVID-19 related verbal fluency dysfunction.
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ABSTRACT:
SUBMITTER: Rosen AC
PROVIDER: S-EPMC8741329 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Transcranial direct current stimulation (tDCS) is a technique used to modify cognition by modulating underlying cortical excitability via weak electric current applied through the scalp. Although many studies have reported positive effects with tDCS, a number of recent studies highlight that tDCS effects can be small and difficult to reproduce. This is especially the case when attempting to modulate performance using single applications of tDCS in healthy participants. Possible reasons may be that optimal stimulation parameters have yet to be identified, and that individual variation in cortical activity and/or level of ability confound outcomes. To address these points, we carried out a series of experiments in which we attempted to modulate performance in fluency and working memory probe tasks using stimulation parameters which have been associated with positive outcomes: we targeted the left inferior frontal gyrus (LIFG) and compared performance when applying a 1.5 mA anodal current for 25 min and with sham stimulation. There is evidence that LIFG plays a role in these tasks and previous studies have found positive effects of stimulation. We also compared our experimental group (N = 19-20) with a control group receiving no stimulation (n = 24). More importantly, we also considered effects on subgroups subdivided according to memory span as well as to more direct measures of executive function abilities and motivational levels. We found no systematic effect of stimulation. Our findings are in line with a growing body of evidence that tDCS produces unreliable effects. We acknowledge that our findings speak to the conditions we investigated, and that alternative protocols (e.g., multiple sessions, clinical samples, and different stimulation polarities) may be more effective. We encourage further research to explore optimal conditions for tDCS efficacy, given the potential benefits that this technique poses for understanding and enhancing cognition.
| S-EPMC5867342 | biostudies-other
Project description: Not available
| S-BSST1269 | biostudies-other
Project description:ObjectiveThe decrease in verbal fluency in patients with Parkinson's disease (PD) undergoing subthalamic nucleus deep brain stimulation (STN-DBS) is usually assumed to reflect a frontal lobe-related cognitive dysfunction, although evidence for this is lacking.MethodsTo explore its underlying mechanisms, we combined neuropsychological, psychiatric and motor assessments with an examination of brain metabolism using F-18 fluorodeoxyglucose positron emission tomography, in 26 patients with PD, 3 months before and after surgery. We divided these patients into two groups, depending on whether or not they exhibited a postoperative deterioration in either phonemic (10 patients) or semantic (8 patients) fluency. We then compared the STN-DBS groups with and without verbal deterioration on changes in clinical measures and brain metabolism.ResultsWe did not find any neuropsychological change supporting the presence of an executive dysfunction in patients with a deficit in either phonemic or semantic fluency. Similarly, a comparison of patients with or without impaired fluency on brain metabolism failed to highlight any frontal areas involved in cognitive functions. However, greater changes in cognitive slowdown and apathy were observed in patients with a postoperative decrease in verbal fluency.ConclusionsThese results suggest that frontal lobe-related cognitive dysfunction could play only a minor role in the postoperative impairment of phonemic or semantic fluency, and that cognitive slowdown and apathy could have a more decisive influence. Furthermore, the phonemic and semantic impairments appeared to result from the disturbance of distinct mechanisms.
| S-EPMC4598145 | biostudies-literature
Project description:The coronavirus pandemic (COVID-19) is associated with secondary bacterial and fungal infections globally. In India, inappropriate use of glucocorticoids, high prevalence of diabetes mellitus and a conducive environment for fungal growth are considered as the main factors for increased incidence of COVID-19 associated mucormycosis (CAM). Few cases of CAM without steroid abuse and normal blood glucose levels were also reported during the pandemic. This study was designed to explore whether altered immune responses due to severe COVID-19 infection predisposes towards development of mucormycosis. The global transcriptome profiling of monocytes and granulocytic cells derived from CAM, Mucormycosis, COVID-19 and healthy control groups were performed to identify the differentially expressed genes (DEGs) involved in dysregulated host immune response towards respective diseased and healthy conditions.
2024-02-09 | GSE226677 | GEO
Project description:Semantic verbal fluency (sVF) tasks are commonly used in clinical diagnostic batteries as well as in a research context. When performing sVF tasks to assess executive functions (EFs) the sum of correctly produced words is the main measure. Although previous research indicates potentially better insights into EF performance by the use of finer grained sVF information, this has not yet been objectively evaluated. To investigate the potential of employing a finer grained sVF feature set to predict EF performance, healthy monolingual German speaking participants (n = 230) were tested with a comprehensive EF test battery and sVF tasks, from which features including sum scores, error types, speech breaks and semantic relatedness were extracted. A machine learning method was applied to predict EF scores from sVF features in previously unseen subjects. To investigate the predictive power of the advanced sVF feature set, we compared it to the commonly used sum score analysis. Results revealed that 8 / 14 EF tests were predicted significantly using the comprehensive sVF feature set, which outperformed sum scores particularly in predicting cognitive flexibility and inhibitory processes. These findings highlight the predictive potential of a comprehensive evaluation of sVF tasks which might be used as diagnostic screening of EFs.
| S-EPMC7994566 | biostudies-literature
Project description:IntroductionIn recent decades, researchers have defined novel methods for scoring verbal fluency tasks. In this work, we evaluate novel scores based on speed of word responses.MethodsWe transcribed verbal fluency recordings from 641 cases of incident cognitive impairment (ICI) and matched controls, all participants in a large national epidemiological study. Timing measurements of utterances were used to calculate a speed score for each recording. Traditional raw and speed scores were entered into Cox proportional hazards (CPH) regression models predicting time to ICI.ResultsConcordance of the CPH model with speed scores was 0.599, an improvement of 3.4% over a model with only raw scores and demographics. Scores with significant effects included animals raw and speed scores, and letter F speed score.DiscussionNovel verbal fluency scores based on response times could enable use of remotely administered fluency tasks for early detection of cognitive decline.Highlights The current work evaluates prognostication with verbal fluency speed scores. These speed scores improve survival models predicting cognitive decline. Cases with progressive decline have some characteristics suggestive of Alzheimer's disease. The subset of acute decliners is probably pathologically heterogeneous.
| S-EPMC9074715 | biostudies-literature
Project description:Background: Verbal fluency (VF) has been associated with several cognitive functions, but the cognitive processes underlying verbal fluency deficits in Multiple Sclerosis (MS) are controversial. Further knowledge about VF could be useful in clinical practice, because these tasks are brief, applicable, and reliable in MS patients. In this study, we aimed to evaluate the cognitive processes related to VF and to develop machine-learning algorithms to predict those patients with cognitive deficits using only VF-derived scores. Methods: Two hundred participants with MS were enrolled and examined using a comprehensive neuropsychological battery, including semantic and phonemic fluencies. Automatic linear modeling was used to identify the neuropsychological test predictors of VF scores. Furthermore, machine-learning algorithms (support vector machines, random forest) were developed to predict those patients with cognitive deficits using only VF-derived scores. Results: Neuropsychological tests associated with attention-executive functioning, memory, and language were the main predictors of the different fluency scores. However, the importance of memory was greater in semantic fluency and clustering scores, and executive functioning in phonemic fluency and switching. Machine learning algorithms predicted general cognitive impairment and executive dysfunction, with F1-scores over 67-71%. Conclusions: VF was influenced by many other cognitive processes, mainly including attention-executive functioning, episodic memory, and language. Semantic fluency and clustering were more explained by memory function, while phonemic fluency and switching were more related to executive functioning. Our study supports that the multiple cognitive components underlying VF tasks in MS could serve for screening purposes and the detection of executive dysfunction.
| S-EPMC7859643 | biostudies-literature
Project description:In this prospective observational cohort study, we found transcriptional evidence that persistent immune dysfunction was associated with 28-day mortality in both COVID-19 and non-COVID-19 septic patients. COVID-19 patients had an early antiviral response but became indistinguishable on a gene expression level from non-COVID-19 sepsis patients a week later. Early treatment of COVID-19 and non-COVID-19 sepsis ICU patients should focus on pathogen control, but both patient groups also require novel immunomodulatory treatments, particularly later during ICU hospitalization, independent of admission diagnosis. Some T1 samples were uploaded in GSE185263 and were not re-uploaded in this series.
2023-03-24 | GSE222393 | GEO
Project description:Women are thought to fare better in verbal abilities, especially in verbal-fluency and verbal-memory tasks. However, the last meta-analysis on sex/gender differences in verbal fluency dates from 1988. Although verbal memory has only recently been investigated meta-analytically, a comprehensive meta-analysis is lacking that focuses on verbal memory as it is typically assessed, for example, in neuropsychological settings. On the basis of 496 effect sizes and 355,173 participants, in the current meta-analysis, we found that women/girls outperformed men/boys in phonemic fluency (ds = 0.12-0.13) but not in semantic fluency (ds = 0.01-0.02), for which the sex/gender difference appeared to be category-dependent. Women/girls also outperformed men/boys in recall (d = 0.28) and recognition (ds = 0.12-0.17). Although effect sizes are small, the female advantage was relatively stable over the past 50 years and across lifetime. Published articles reported stronger female advantages than unpublished studies, and first authors reported better performance for members of their own sex/gender. We conclude that a small female advantage in phonemic fluency, recall, and recognition exists and is partly subject to publication bias. Considerable variance suggests further contributing factors, such as participants' language and country/region.
| S-EPMC9896545 | biostudies-literature
Project description:To investigate the role of gene expression in patients with COVID-19. Full article available at DOI: 10.1136/bmjopen-2020-044497.
2023-01-30 | GSE217948 | GEO