The phenomenon of semantic satiation, which refers to the loss of meaning of a word or phrase after being repeated many times, is a well-known psychological phenomenon. However, the microscopic neural computational principles responsible for these me...
Neural networks : the official journal of the International Neural Network Society
Apr 20, 2024
Spiking neural networks (SNNs), as the brain-inspired neural networks, encode information in spatio-temporal dynamics. They have the potential to serve as low-power alternatives to artificial neural networks (ANNs) due to their sparse and event-drive...
International journal of neural systems
Apr 17, 2024
Deep learning technology has been successfully used in Chest X-ray (CXR) images of COVID-19 patients. However, due to the characteristics of COVID-19 pneumonia and X-ray imaging, the deep learning methods still face many challenges, such as lower ima...
International journal of neural systems
Apr 13, 2024
Most existing multi-scale object detectors depend on multi-level feature maps. The Feature Pyramid Networks (FPN) is a significant architecture for object detection that utilizes these multi-level feature maps. However, the use of FPN also increases ...
International journal of neural systems
Apr 13, 2024
Spiking Neural P Systems (SNP) are well-established computing models that take inspiration from spikes between biological neurons; these models have been widely used for both theoretical studies and practical applications. Virus machines (VMs) are an...
Neural networks : the official journal of the International Neural Network Society
Apr 12, 2024
How does the brain process natural visual stimuli to make a decision? Imagine driving through fog. An object looms ahead. What do you do? This decision requires not only identifying the object but also choosing an action based on your decision confid...
In a recent issue of Cell, Vargas and colleagues demonstrate that task-driven neural network models are superior at predicting proprioceptive activity in the primate cuneate nucleus and sensorimotor cortex compared with other models. This provides va...
Mathematical modeling of neuronal dynamics has experienced a fast growth in the last decades thanks to the biophysical formalism introduced by Hodgkin and Huxley in the 1950s. Other types of models (for instance, integrate and fire models), although ...
IEEE transactions on biomedical circuits and systems
Apr 1, 2024
The study of neuron interactions and hardware implementations are crucial research directions in neuroscience, particularly in developing large-scale biological neural networks. The FitzHugh-Nagumo (FHN) model is a popular neuron model with highly bi...
International journal of neural systems
Mar 8, 2024
A variant of membrane computing models called Spiking Neural P systems (SNP systems) closely mimics the structure and behavior of biological neurons. As third-generation neural networks, SNP systems have flexible architectures allowing the design of ...