Interventions to improve working memory, e.g. by combining task rehearsal and non-invasive brain stimulation, are gaining popularity. Many factors, however, affect the outcome of these interventions. We hypothesize that working memory capacity at baseline predicts how an individual performs on a working memory task, by setting limits on the benefit derived from tDCS when combined with strategy instructions; specifically, we hypothesize that individuals with low capacity will benefit the most. Eighty-four participants underwent two sessions of an adaptive working memory task (n-back) on two consecutive days. Participants were split into four independent groups (SHAM vs ACTIVE stimulation and STRATEGY vs no STRATEGY instructions). For the purpose of analysis, individuals were divided based on their baseline working memory capacity. Results support our prediction that the combination of tDCS and strategy instructions is particularly beneficial in low capacity individuals. Our findings contribute to a better understanding of factors affecting the outcome of tDCS when used in conjunction with cognitive training to improve working memory. Moreover, our results have implications for training regimens, e.g., by designing interventions predicated on baseline cognitive abilities, or focusing on strategy development for specific attentional skills.
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http://dx.doi.org/10.1038/s41598-021-84298-3 | DOI Listing |
Schizophr Res Cogn
June 2025
University Department of Child and Adolescent Psychiatry, Children's Hospitals of NICE CHU-Lenval, Nice, France.
Objective: To conduct a systematic review of neurocognitive dysfunctions in patients with childhood-onset schizophrenia (COS), a neuropsychiatric disorder that occurs before age 13 and is rarer and more severe than adult-onset schizophrenia.
Method: A search was made in the PubMed database. Sixty-seven studies (out of 543) which analyzed Intellectual Quotient (IQ), attentional, memory and executive functions were selected by two independent researchers.
Water Res X
May 2025
Institute for Artificial Intelligence R&D of Serbia, Fruškogorska 1, Novi Sad 21000, Serbia.
This study evaluates three Machine Learning (ML) models-Temporal Kolmogorov-Arnold Networks (TKAN), Long Short-Term Memory (LSTM), and Temporal Convolutional Networks (TCN)-focusing on their capabilities to improve prediction accuracy and efficiency in streamflow forecasting. We adopt a data-centric approach, utilizing large, validated datasets to train the models, and apply SHapley Additive exPlanations (SHAP) to enhance the interpretability and reliability of the ML models. The results show that TKAN outperforms LSTM but slightly lags behind TCN in streamflow forecasting.
View Article and Find Full Text PDFPublic Health Pract (Oxf)
June 2025
MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK.
Objectives: Disuse theory predicts that cognitive function is vulnerable to transitions that remove factors that support cognitive skills. We sought to investigate whether non-employment over the working life was associated with cognitive function and decline in later life (≥60 years old), and possible gender differences in the association.
Study Design: Longitudinal study.
Cogn Neurodyn
December 2025
Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, TamilNadu India.
Emotion recognition plays a crucial role in brain-computer interfaces (BCI) which helps to identify and classify human emotions as positive, negative, and neutral. Emotion analysis in BCI maintains a substantial perspective in distinct fields such as healthcare, education, gaming, and human-computer interaction. In healthcare, emotion analysis based on electroencephalography (EEG) signals is deployed to provide personalized support for patients with autism or mood disorders.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
CIPCE, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, North Kargar Ave., Tehran, Iran.
The term "neuroenhancement" describes the enhancement of cognitive function associated with deficiencies resulting from a specific condition. Nevertheless, there is currently no agreed-upon definition for the term "neuroenhancement", and its meaning can change based on the specific research being discussed. As humans, our continual pursuit of expanding our capabilities, encompassing both cognitive and motor skills, has led us to explore various tools.
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