When designing a robot, such as Boston Dynamics' anthropomorphic robot Atlas, which appears exercising and sorting boxes, ...

This type of AI algorithm is not currently common since most neuroadaptive interfaces rely on opaque neural networks. 71 ...

Artificial neural networks are inspired by the early models of sensory processing by the brain. An artificial neural network can be created by simulating a network of model neurons in a computer ...

The brain's ability to track orientation and position is essential for memory, navigation, and decision-making. Traditionally ...

How can we characterize the dynamics of neural networks with recurrent connections? How do the time-varying activities of populations of neurons represent things? How are synapse strengths ...

The goal of the Journal is as a forum for the interdisciplinary field of neural engineering where neuroscientists, neurobiologists and engineers can publish their work in one periodical that ...

Researchers have developed a transfer learning-enhanced physics-informed neural network (TLE-PINN) for predicting melt pool ...

This article establishes a neural network-based technique for automatic peak picking in 2D NMR spectroscopy, demonstrating a ...

Morphological profiling allows accurate identification of cell types in dense iPSC-derived cultures, allowing its use for quality control and differentiation monitoring.

Neural network models that are able to make decisions or store memories have long captured scientists' imaginations. In these ...

AI applications like ChatGPT are based on artificial neural networks that, in many respects, imitate the nerve cells in our ...

Western researchers have developed a novel technique using math to understand exactly how neural networks make decisions—a ...