As for vision, understanding how neurons perceive and respond to rich natural visual information is a major topic of neural encoding, whereas the goal of neural decoding of visual information is ...

[Sam Greydanus] created a neural ... network on [Sam]’s GitHub page. As you can see from this article’s banner, with 96-97% accuracy it did pretty well when making predictions i.e. decoding.

Critical to the research is a type of algorithm called a convolutional neural network, which has been instrumental ... a process called cross-subject encoding and decoding. This finding is important ...

As in the case of ECoG, the neural network provided high decoding accuracy and feature interpretability. We are already using this approach to build invasive brain-computer interfaces, as well as ...

However, it has also led to confusion surrounding the related technologies, especially AI, neural networks, machine learning, and deep learning, with the terms being used interchangeably often.

The authors compared the neural activities measured during perception and imagery conditions to that predicted from neural encoding models based on the ... In this study, the authors developed ...

Every day, various types of sensory information fromthe external environment are transferred to the brainthrough different modalities and then processed to generate a series of coping behaviors.