High cognitive effort has been frequently related to better indices of motor learning through the study of many different paradigms. However, automaticity presumably invokes minimal cognitive processing but has often been related to high-level motor performance, which suggests a paradox. The objective of this study was to approach this paradox by examining the viability of the use of different cognitive strategies during practice and performance which promote the benefits of high cognitive effort and automaticity. Members of the university community (14 men and 15 women) divided into 3 groups practiced a discrete precision task. All participants completed four sessions totaling 320 trials and were tested on retention and transfer seven days later. Findings suggest that it is indeed possible to benefit from both effortful and minimal cognitive processing strategies and that they should be used complementarily.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.2466/pms.99.1.315-324 | DOI Listing |
Acta Psychol (Amst)
January 2025
Department of Sport Science, School of Humanities, Damghan University, Damghan, Iran.
This study aims to investigate the effect of different implicit and explicit instructions on learning a fundamental motor skill (throwing task) in autistic children with a high propensity for reinvestment. A total of 48 male volunteer students with special educational needs aged between 7 and 9 years old were conveniently selected to practice a novel throwing motor task (slingerball). The study includes a 1-week the acquisition phase with five phases of measurements involving four groups: a) analogy, b) explicit instruction, c) errorless, and d) errorful paradigms.
View Article and Find Full Text PDFCureus
December 2024
Cultural Technology and Communication, Intelligent Systems Lab, University of the Aegean, Mytilene, GRC.
Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental condition marked by movement hyperactivity, often persisting into adulthood. Understanding the movement patterns associated with ADHD is crucial for improving diagnostic precision and tailoring interventions. This study leverages the HYPERAKTIV dataset, which includes high-resolution temporal data on motor activity from people diagnosed with ADHD.
View Article and Find Full Text PDFSci Rep
January 2025
Affective Psychology Department, Institute of Psychology, Eötvös Loránd University, Budapest, Hungary.
The gut–brain axis, a bidirectional communication pathway, permits the central nervous system (CNS) to exert influence over gastrointestinal function in response to stress, while the gut microbiota regulates the CNS via immune, neuroendocrine, and vagal pathways. Current research highlights the importance of the gut microbiota in stress-related disorders and the need for further research into the mechanisms of gut–brain communication, with potential therapeutic implications for a wide range of health conditions. This is a challenge taken on in this Collection on the Gut-Brain Axis.
View Article and Find Full Text PDFJ Neural Eng
January 2025
Department of Information Engineering, Electronics and Telecommunications, University of Rome La Sapienza, Piazzale Aldo Moro 5, Rome, 00185, ITALY.
Deep learning tools applied to high-resolution neurophysiological data have significantly progressed, offering enhanced decoding, real-time processing, and readability for practical applications. However, the design of artificial neural networks to analyze neural activity in vivo remains a challenge, requiring a delicate balance between efficiency in low-data regimes and the interpretability of the results. Approach: To address this challenge, we introduce a novel specialized transformer architecture to analyze single-neuron spiking activity.
View Article and Find Full Text PDFActa Bioeng Biomech
September 2024
Faculty of Computer Science, Kazimierz Wielki University, Bydgoszcz, Poland.
Monitoring and assessing the level of lower limb motor skills using the Biodex System plays an important role in the training of football players and in post-traumatic rehabilitation. The aim of this study was to build and test an artificial intelligence-based model to assess the peak torque of the lower limb extensors and flexors. The model was based on real-world results in three groups: hearing ( = 19) and deaf football players ( = 28) and non-training deaf pupils ( = 46).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!