The ongoing exponential rise in recording capacity calls for new approaches for analysing
and interpreting neural data. Effective dimensionality has emerged as an important property …

Human visual perception carves a scene at its physical joints, decomposing the world into
objects, which are selectively attended, tracked and predicted as we engage our …

Conventional views of brain organization suggest that regions at the top of the cortical
hierarchy processes internally oriented information using an abstract amodal neural code …

The brain plans and executes volitional movements. The underlying patterns of neural
population activity have been explored in the context of movements of the eyes, limbs …

Sensory information encoded by humans and other organisms is generally presumed to be
as accurate as their biological limitations allow. However, perhaps counterintuitively …

Humans can navigate flexibly to meet their goals. Here, we asked how the neural
representation of allocentric space is distorted by goal-directed behavior. Participants …

Humans can learn several tasks in succession with minimal mutual interference but perform
more poorly when trained on multiple tasks at once. The opposite is true for standard deep …

Deep learning (DL) has been utilized pervasively in the Internet of Things (IoT). One typical
application of DL in IoT is device identification from wireless signals, namely …

While neural plasticity has long been studied as the basis of learning, the growth of large-
scale neural recording techniques provides a unique opportunity to study how learning …

Persistently active neurons during mnemonic periods have been regarded as the
mechanism underlying working memory maintenance. Alternatively, neuronal networks …