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Biological cybernetics
Apr 10, 2024
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 ...
Neural networks : the official journal of the International Neural Network Society
Apr 8, 2024
Recently, Physics-Informed Neural Networks (PINNs) have gained significant attention for their versatile interpolation capabilities in solving partial differential equations (PDEs). Despite their potential, the training can be computationally demandi...
IEEE transactions on neural networks and learning systems
Apr 4, 2024
The analysis of neuronal morphological data is essential to investigate the neuronal properties and brain mechanisms. The complex morphologies, absence of annotations, and sheer volume of these data pose significant challenges in neuronal morphologic...
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...
PLoS computational biology
Mar 28, 2024
Recent neuroimaging studies have shown that the visual cortex plays an important role in representing the affective significance of visual input. The origin of these affect-specific visual representations is debated: they are intrinsic to the visual ...
Neural networks : the official journal of the International Neural Network Society
Mar 26, 2024
To enhance resource efficiency and model deployability of neural networks, we propose a neural-layer architecture based on Householder weighting and absolute-value activating, called Householder-absolute neural layer or simply Han-layer. Compared to ...
Journal of neural engineering
Mar 20, 2024
Object recognition and making a choice regarding the recognized object is pivotal for most animals. This process in the brain contains information representation and decision making steps which both take different amount of times for different object...
Neural networks : the official journal of the International Neural Network Society
Mar 16, 2024
Various topological methods have emerged in recent years to investigate the inner workings of deep neural networks (DNNs) based on the structural and weight information. However, their effectiveness is restricted due to the stratified structure and v...
Neural networks : the official journal of the International Neural Network Society
Mar 15, 2024
Spiking Neural Networks (SNNs) have become one of the most prominent next-generation computational models owing to their biological plausibility, low power consumption, and the potential for neuromorphic hardware implementation. Among the various met...
PLoS computational biology
Mar 13, 2024
Various animals, including humans, have been suggested to perform Bayesian inferences to handle noisy, time-varying external information. In performing Bayesian inference by the brain, the prior distribution must be acquired and represented by sampli...