Visual perceptual learning (VPL) is long-term performance improvement as a result of perceptual experience. It is unclear whether VPL is associated with refinement in representations of the trained feature (feature-based plasticity), improvement in processing of the trained task (task-based plasticity), or both. Here, we provide empirical evidence that VPL of motion detection is associated with both types of plasticity which occur predominantly in different brain areas. Before and after training on a motion detection task, subjects' neural responses to the trained motion stimuli were measured using functional magnetic resonance imaging. In V3A, significant response changes after training were observed specifically to the trained motion stimulus but independently of whether subjects performed the trained task. This suggests that the response changes in V3A represent feature-based plasticity in VPL of motion detection. In V1 and the intraparietal sulcus, significant response changes were found only when subjects performed the trained task on the trained motion stimulus. This suggests that the response changes in these areas reflect task-based plasticity. These results collectively suggest that VPL of motion detection is associated with the 2 types of plasticity, which occur in different areas and therefore have separate mechanisms at least to some degree.
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http://dx.doi.org/10.1093/cercor/bhw176 | DOI Listing |
Sci Rep
January 2025
Department of Electrical and Electronics, Faculty of Engineering, Alberoni University, Kapisa, Afghanistan.
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View Article and Find Full Text PDFJ Biomech
January 2025
Instituto Brasil de Tecnologias da Saúde, Rua Visconde de Piraja, 407 suite 905, Rio de Janeiro, RJ 22410-003, Brazil; Depto. de Diagnóstico por Imagem - Escola Paulista de Medicina, Universidade Federal de São Paulo, R. Napoleão de Barros, 800, São Paulo, SP, Brazil. Electronic address:
Anterior Shoulder Instability (ASI) is a common orthopedic condition often resulting in altered shoulder kinematics. Understanding the biomechanics of the unstable shoulder is critical to determine the most appropriate treatment. This study aims to conduct the first systematic review and meta-analysis of three-dimensional (3D) shoulder kinematic studies in ASI patients.
View Article and Find Full Text PDFPolymers (Basel)
January 2025
Department of Mechanical Engineering, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal.
Smart textiles provide a significant technological advancement, but their development must balance traditional textile properties with electronic features. To address this challenge, this study introduces a flexible, electrically conductive composite material that can be fabricated using a continuous bi-component extrusion process, making it ideal for sensor electrodes. The primary aim was to create a composite for the filament's core, combining multi-walled carbon nanotubes (MWCNTs), polypropylene (PP), and thermoplastic elastomer (TPE), optimised for conductivity and flexibility.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Beijing Aerospace Automatic Control Institute, Beijing 100854, China.
The traditional method is capable of detecting and tracking stationary and slow-moving targets in a sea surface environment. However, the signal focusing capability of such a method could be greatly reduced especially for those variable-speed targets. To solve this problem, a novel tracking algorithm combining range envelope alignment and azimuth phase filtering is proposed.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Science and Engineering, Saga University, Saga 840-8502, Japan.
Infrared array sensor-based fall detection and activity recognition systems have gained momentum as promising solutions for enhancing healthcare monitoring and safety in various environments. Unlike camera-based systems, which can be privacy-intrusive, IR array sensors offer a non-invasive, reliable approach for fall detection and activity recognition while preserving privacy. This work proposes a novel method to distinguish between normal motion and fall incidents by analyzing thermal patterns captured by infrared array sensors.
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