A key objective of several neuroscience studies is to understand and model how the dynamics of distinct populations of ...

The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development ...

In the first half of this course, we will explore the evolution of deep neural network language models, starting with n-gram models and proceeding through feed-forward neural networks, recurrent ...

For more than a decade, Alexander Huth from the University of Texas at Austin had been striving to build a language decoder—a tool that could extract a person’s thoughts noninvasively from brain ...