Neural prostheses translate neural activity from the brain into control signals for guiding
prosthetic devices, such as computer cursors and robotic limbs, and thus offer individuals with …

Neuroscience is experiencing a revolution in which simultaneous recording of thousands of
neurons is revealing population dynamics that are not apparent from single-neuron …

Recurrent neural networks (RNNs) are useful tools for learning nonlinear relationships in time
series data with complex temporal dependences. In this paper, we explore the ability of a …

Increasing evidence suggests that neural population responses have their own internal drive,
or dynamics, that describe how the neural population evolves through time. An important …

A major hurdle to clinical translation of brain–machine interfaces (BMIs) is that current decoders,
which are trained from a small quantity of recent data, become ineffective when neural …

The large power requirement of current brain–machine interfaces is a major hindrance to
their clinical translation. In basic behavioural tasks, the downsampled magnitude of the 300–…

Objective. Brain–machine interfaces (BMIs) seek to enable people with movement disabilities
to directly control prosthetic systems with their neural activity. Current high performance …

In the 1960s, Evarts first recorded the activity of single neurons in motor cortex of behaving
monkeys ( Evarts, 1968 ). In the 50 years since, great effort has been devoted to …

Neural circuits must transform new inputs into outputs without prematurely affecting
downstream circuits while still maintaining other ongoing communication with these targets. We …

In dynamic environments, subjects often integrate multiple samples of a signal and combine
them to reach a categorical judgment 1 . The process of deliberation can be described by a …