Frontiers

Neural Network Dynamics: Unraveling Spiking and Synaptic Plasticity in Learning and Memory

Neuroscience continually strives to unravel the intricate relationship between neural network morphology, spiking dynamics, and their resulting functional ...
IEEE

Saturation Function-Based Finite-Time Synchronization Control for Fractional-Order Coupled Neural Networks

Abstract: In the existing research on finite-time synchronization (FTS) control for fractional-order coupled neural networks (FOCNNs), signum function plays a crucial role in controller design. The ...
Devdiscourse

Food industry turns to machine learning to boost efficiency, cut waste and improve quality

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
Learn With Jay on MSN

Neural network cost functions: Which to use and why?

In this video, we will see what is Cost Function, what are the different types of Cost Function in Neural Network, and which ...
Learn With Jay on MSN

Activation functions in neural networks: Types and examples

In this video, we will see What is Activation Function in Neural network, types of Activation function in Neural Network, why ...
IEEE

Using Radial Basis Function Neural Network With Weight Memory Mechanism: Nonlinear System Identification

Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...
eLife

A differentiable model for optimizing the genetic drivers of synaptogenesis

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

Why some video games improve brain function – and others don't

Aaron Seitz, professor of psychology and director of the Brain Game Center for Mental Fitness and Well-being at Northeastern University, told The Washington Post that when ...
Study Finds

What Makes Brains Conscious That Computers Lack?

Research reveals why AI systems can't become conscious—and what radically different computing substrates would be needed to ...

Signature neural patterns may help predict recovery from traumatic brain injury

After traumatic brain injury (TBI), some patients may recover completely, while others retain severe disabilities. Accurately ...

Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an interpretable artificial intelligence (AI) framework named Convolutional Kolmogorov ...