Although, cognitive working memory training (CWMT) has been reported to enhance working memory functioning in youths with attention-deficit/ hyperactivity disorder (ADHD), few studies take into account the concomitant effects of medication. Sixty adolescents aged from 11 to 15 years were randomly assigned to CWMT treatment, whereas medication was either continued or not introduced (no randomization performed). Results revealed beneficial effects of CWMT on the different components of working memory (WM), namely the phonological loop, the visuospatial sketchpad and the central executive. In particular, CWMT allowed participants to obtain a level of performance similar to the typically-developing adolescents for the phonological loop (i.e., forward digit span) as well as for the visuospatial sketchpad (i.e., board span). For the central executive (i.e., backward digit span) the concomitant effects of CWMT and medication allows participants to obtain the performance level of the typically-developing adolescents. Although, no transfers were observed with respect to other cognitive functions, in medicated patients with ADHD, CWMT reduced hyperactivity / impulsivity symptoms at 2-month follow-up. The present study gives evidence of the efficacy of CWMT to enhance WM performance, as well as, to reduce symptoms. The overall results highlight the usefulness of multimodal interventions.
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http://dx.doi.org/10.1016/j.psychres.2018.07.036 | DOI Listing |
In the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for privacy protection in the Chinese clinical context. We collected and double-annotated 33,017 discharge summaries from 151 medical institutions on a municipal regional health information platform, developed a BERT-based Bidirectional Long Short-Term Memory Model (BiLSTM) and Conditional Random Field (CRF) model, and tested the performance of privacy identification on the dataset. To explore the performance of different substructures of the neural network, we created five additional baseline models and evaluated the impact of different models on performance.
View Article and Find Full Text PDFJ Integr Neurosci
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Sports, Exercise and Brain Sciences Laboratory, Sports Coaching College, Beijing Sport University, 100084 Beijing, China.
Background: Sports fatigue in soccer athletes has been shown to decrease neural activity, impairing cognitive function and negatively affecting motor performance. Transcranial direct current stimulation (tDCS) can alter cortical excitability, augment synaptic plasticity, and enhance cognitive function. However, its potential to ameliorate cognitive impairment during sports fatigue remains largely unexplored.
View Article and Find Full Text PDFNutrients
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Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), 28029 Madrid, Spain.
Decompensated cirrhosis is characterized by systemic inflammation and innate and adaptive immune dysfunction. Hepatic encephalopathy (HE) is a prevalent and debilitating condition characterized by cognitive disturbances in which ammonia and inflammation play a synergistic pathogenic role. Extraskeletal functions of vitamin D include immunomodulation, and its deficiency has been implicated in immune dysfunction and different forms of cognitive impairment.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia.
The Internet of Things (IoT) has emerged as a crucial element in everyday life. The IoT environment is currently facing significant security concerns due to the numerous problems related to its architecture and supporting technology. In order to guarantee the complete security of the IoT, it is important to deal with these challenges.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China.
Real-time and accurate traffic forecasting aids in traffic planning and design and helps to alleviate congestion. Addressing the negative impacts of partial data loss in traffic forecasting, and the challenge of simultaneously capturing short-term fluctuations and long-term trends, this paper presents a traffic forecasting model, D-MGDCN-CLSTM, based on Multi-Graph Gated Dilated Convolution and Conv-LSTM. The model uses the DTWN algorithm to fill in missing data.
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