Objectives: To evaluate the efficacy of Cogmed Working Memory Training compared with the standard of care to improve executive function and social outcomes in adolescents with congenital heart disease (CHD) who underwent open-heart surgery in infancy and to identify factors associated with changes in outcomes following the intervention.
Study Design: In a single-center, randomized controlled trial, adolescents (13-16 years) with CHD were randomly assigned to either Cogmed (home-based 45-minutes sessions for 5-8 weeks) or to a control group. The primary outcome was working memory. Secondary outcomes included inhibitory control and cognitive flexibility as well as parent-reported executive function, symptoms of attention deficit hyperactivity disorder, and social outcomes. All measures were assessed at baseline, post-treatment (1-3 weeks post-training) and at 3-month follow-up. Data were analyzed using an intention-to-treat approach.
Results: Sixty adolescents with CHD participated (28 assigned to Cogmed). No improvement at the post-treatment or 3-month follow-up assessments was found for the primary outcome measure of working memory. Compared with the control group, participants assigned to the intervention demonstrated benefits in inhibitory control and attention at the 3-month follow-up (P = .02) and in parent-reported cognitive regulatory skills at post-treatment and 3-month follow-up (P = .02 and P = .04, respectively). Preterm birth, biventricular CHD, and history of attention deficit hyperactivity disorder diagnosis were associated with improved response to the intervention.
Conclusions: Cogmed intervention produced improvements in the self-regulatory control abilities of adolescents with CHD. The training did not enhance other areas of executive function or behavioral outcomes. Further studies are needed to evaluate the longer-term potential benefits to other domains.
Trial Registration: Clinicaltrials.gov: NCT02759263.
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http://dx.doi.org/10.1016/j.jpeds.2020.08.038 | DOI Listing |
How the prefrontal hemispheres coordinate to adapt to spatial working memory (WM) demands remains an open question. Recently, two models have been proposed: A specialized model, where each hemisphere governs contralateral behavior, and a redundant model, where both hemispheres equally guide behavior in the full visual space. To explore these alternatives, we analyzed simultaneous bilateral prefrontal cortex recordings from three macaque monkeys performing a visuo-spatial WM task.
View Article and Find Full Text PDFUnlabelled: Delay period activity in the dorso-lateral prefrontal cortex (dlPFC) has been linked to the maintenance and control of sensory information in working memory. The stability of working memory related signals found in such delay period activity is believed to support robust memory-guided behavior during sensory perturbations, such as distractors. Here, we directly probed dlPFC's delay period activity with a diverse set of activity perturbations, and measured their consequences on neural activity and behavior.
View Article and Find Full Text PDFExecutive functions, including working memory, are typically assessed clinically with neuropsychological instruments. In contrast, computerized tasks are used to test these cognitive functions in laboratory human and animal studies. Little is known of how neural activity captured by laboratory tasks relates to ability measured by clinical instruments and, by extension, clinical diagnoses of pathological conditions.
View Article and Find Full Text PDFSchizophr 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.
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