Recent advances in understanding the brain’s dynamic functioning have been achieved through a wide range of experiments conducted across multiple levels of ...

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...

During each of these phases, our brains show markedly different characteristics in their architecture, according to the new ...

Biological neural networks are immensely complex systems underlying all aspects of cognition and behavior. Despite significant advances in neuroscience, a ...

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...

Physicists have spent decades trying to explain puzzling radio bursts and other odd signals that seem to arrive from deep ...

Abstract: The nonlinear behavior of loudspeakers is of great interest in a number of audio processing algorithms, as it may have a detrimental effect on their performance. These algorithms may be ...

This valuable study uses mathematical modeling and analysis to address the question of how neural circuits generate distinct low-dimensional, sequential neural dynamics that can change on fast, ...

A new study published in Advanced Science suggests that the brain uses two distinct, large-scale networks to recognize ...

A collaboration between SISSA's Physics and Neuroscience groups has taken a step forward in understanding how memories are stored and retrieved in the ...

Artificial intelligence (AI) is set to transform the care of women with cancer. From early detection via digital phenotyping ...