More information: Robin Tibor Schirrmeister et al. Deep learning with convolutional neural networks for EEG decoding and visualization, Human Brain Mapping (2017). DOI: 10.1002/hbm.23730 ...

The decoder used the neural network patterns, compared them with image data from a large database, accordig to the researchers. This allowed it to identify objects with a high degree of accuracy.

Using fMRI signals and Deep Neural Network AI, researchers decode and predict what a subject is seeing or imagining. Scanning your brain to decode the contents of your mind has been a subject of ...

Neural networks? Machine learning? Here's your secret decoder for A.I. buzzwords By Luke Dormehl Updated August 4, 2021 Image used with permission by copyright holder ...

The new tool allowed the researchers to essentially roll back the tape and see, in perfect HD, which neurons, features, and circuits were active inside Claude’s neural network at any given step.

More information: Jonathan Karin et al, Interpreting single-cell and spatial omics data using deep neural network training dynamics, Nature Computational Science (2024). DOI: 10.1038/s43588-024 ...

The neural network proposed by the researchers consists of several similarly structured branches, each of which is automatically tuned to analyze the signals of a separate neural population in a ...

Facebook this week open-sourced PyTorch tools to build a deep learning model that can represent the structure of 93 different languages in a single neural network. The system is able to match up ...

Petrosyan, A., et al. (2022) Speech decoding from a small set of spatially segregated minimally invasive intracranial EEG electrodes with a compact and interpretable neural network.

Deep learning with convolutional neural networks for EEG decoding and visualization. Human Brain Mapping, 2017; DOI: 10.1002/hbm.23730 ...