Learners are able to use 2 different types of knowledge to perform a skill. One type is a conscious mental model, and the other is based on memories of instances. The authors conducted 3 experiments that manipulated training conditions designed to affect the availability of 1 or both types of knowledge about an artificial grammar. Participants were tested for both speed and accuracy of their ability to generate letter sequences. Results indicate that model-based training leads to slow accurate responding. Memory-based training leads to fast, less accurate responding and highest achievement when perfect accuracy was not required. Evidence supports participants' preference for using the memory-based mode when exposed to both types of training. Finally, the accuracy contributed by model-based training declined over a retention interval.
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http://dx.doi.org/10.1037/0278-7393.30.5.1002 | DOI Listing |
Alzheimers Dement
December 2024
Johns Hopkins University, Baltimore, MD, USA.
Background: Phenotyping Alzheimer's Disease (AD) can be crucial to providing personalized treatment. Several studies have analyzed the use of digital biomarkers to characterize a subject's behavior, usually obtained from a single modality, such as speech. However, combining several modalities in a single study has not been deeply studied.
View Article and Find Full Text PDFFront Neurorobot
December 2024
Department of Fine Arts, Bozhou University, Bozhou, Anhui, China.
Introduction: Segmentation tasks in computer vision play a crucial role in various applications, ranging from object detection to medical imaging and cultural heritage preservation. Traditional approaches, including convolutional neural networks (CNNs) and standard transformer-based models, have achieved significant success; however, they often face challenges in capturing fine-grained details and maintaining efficiency across diverse datasets. These methods struggle with balancing precision and computational efficiency, especially when dealing with complex patterns and high-resolution images.
View Article and Find Full Text PDFBiomed Eng Lett
January 2025
School of Chemistry and Chemical Engineering, Tianjin University of Technology, Tianjin, 300384 People's Republic of China.
Brain-computer interface (BCI) has been widely used in human-computer interaction. The introduction of artificial intelligence has further improved the performance of BCI system. In recent years, the development of BCI has gradually shifted from personal computers to embedded devices, which boasts lower power consumption and smaller size, but at the cost of limited device resources and computing speed, thus can hardly improve the support of complex algorithms.
View Article and Find Full Text PDFJ Phys Chem Lett
January 2025
School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, People's Republic of China.
Efficient capture of single-stranded DNA (ssDNA) is crucial for high-throughput sequencing, which influences the speed and accuracy of genetic analysis. Electrophoresis (EP) and electro-osmotic flow (EOF) have a significant impact on the translocation behavior of ssDNA through the nanopore. Experimentally, dynamically tracking these two effects remains challenging, and conventional numerical methods also struggle to capture their dynamic properties in the presence of DNA.
View Article and Find Full Text PDFJ Neuroeng Rehabil
January 2025
Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
Background: Motion complexity is necessary for adapting to external changes, but little is known about trunk motion complexity during seated perturbation in individuals with spinal cord injury (SCI). We aimed to investigate changes following SCI in trunk segmental motion complexity across different perturbation directions and how they affect postural control ability in individuals with SCI.
Methods: A total of 17 individuals with SCI and 18 healthy controls participated in challenging sagittal-seated perturbations with hand protection.
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