Neuromodulation confers operational flexibility on motor network output and resulting behaviour. Furthermore, neuromodulators play crucial long-term roles in the assembly and maturational shaping of the same networks as they develop. Although previous studies have identified such modulator-dependent contributions to microcircuit ontogeny, some of the underlying mechanisms are only now being elucidated. Deciphering the role of neuromodulatory systems in motor network development has potentially important implications for post-lesional regenerative strategies in adults.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.conb.2014.05.009 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Shaping the structural dynamics of motor learning through cueing during sleep.
Sleep
January 2025
UR2NF-Neuropsychology and Functional Neuroimaging Research Unit affiliated at CRCN - Centre for Research in Cognition and Neurosciences and UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium.
Enhancing the retention of recent memory traces through sleep reactivation is possible via Targeted Memory Reactivation (TMR), involving cueing learned material during post-training sleep. Evidence indicates detectable short-term microstructural changes in the brain within an hour after motor sequence learning, and post-training sleep is believed to contribute to the consolidation of these motor memories, potentially leading to enduring microstructural changes. In this study, we explored how TMR during post-training sleep affects performance gains and delayed microstructural remodeling, using both standard Diffusion Tensor Imaging (DTI) and advanced Neurite Orientation Dispersion & Density Imaging (NODDI).
View Article and Find Full Text PDFA Deep Learning-Based Framework Oriented to Pathological Gait Recognition with Inertial Sensors.
Sensors (Basel)
January 2025
Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, Via E. Orabona, 4, 70125 Bari, Italy.
Abnormal locomotor patterns may occur in case of either motor damages or neurological conditions, thus potentially jeopardizing an individual's safety. Pathological gait recognition (PGR) is a research field that aims to discriminate among different walking patterns. A PGR-oriented system may benefit from the simulation of gait disorders by healthy subjects, since the acquisition of actual pathological gaits would require either a higher experimental time or a larger sample size.
View Article and Find Full Text PDFEBR-YOLO: A Lightweight Detection Method for Non-Motorized Vehicles Based on Drone Aerial Images.
Sensors (Basel)
January 2025
College of Information Science and Technology, Donghua University, Shanghai 201620, China.
Modern city construction focuses on developing smart transportation, but the recognition of the large number of non-motorized vehicles in the city is still not sufficient. Compared to fixed recognition equipment, drones have advantages in image acquisition due to their flexibility and maneuverability. With the dataset collected from aerial images taken by drones, this study proposed a novel lightweight architecture for small objection detection based on YOLO framework, named EBR-YOLO.
View Article and Find Full Text PDFPredictive Maintenance and Fault Detection for Motor Drive Control Systems in Industrial Robots Using CNN-RNN-Based Observers.
Sensors (Basel)
December 2024
Department of Computer Science and Engineering, Intelligent Robot Research Institute, Sun Moon University, Asan 31460, Republic of Korea.
This research work presents an integrated method leveraging Convolutional Neural Networks and Recurrent Neural Networks (CNN-RNN) to enhance the accuracy of predictive maintenance and fault detection in DC motor drives of industrial robots. We propose a new hybrid deep learning framework that combines CNNs with RNNs to improve the accuracy of fault prediction that may occur on a DC motor drive during task processing. The CNN-RNN model determines the optimal maintenance strategy based on data collected from sensors, such as air temperature, process temperature, rotational speed, and so forth.
View Article and Find Full Text PDFA Deployment Method for Motor Fault Diagnosis Application Based on Edge Intelligence.
Sensors (Basel)
December 2024
Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China.
The rapid advancement of Industry 4.0 and intelligent manufacturing has elevated the demands for fault diagnosis in servo motors. Traditional diagnostic methods, which rely heavily on handcrafted features and expert knowledge, struggle to achieve efficient fault identification in complex industrial environments, particularly when faced with real-time performance and accuracy limitations.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!