Computational models in neuroscience usually take the form of systems of differential
equations. The behaviour of such systems is the subject of dynamical systems theory …

Loss of speech after paralysis is devastating, but circumventing motor-pathway injury by
directly decoding speech from intact cortical activity has the potential to restore natural …

Map** behavioural actions to neural activity is a fundamental goal of neuroscience. As our
ability to record large neural and behavioural data increases, there is growing interest in …

Our ability to use deep learning approaches to decipher neural activity would likely benefit
from greater scale, in terms of both the model size and the datasets. However, the …

Recent work has argued that large-scale neural recordings are often well described by
patterns of coactivation across neurons. Yet the view that neural variability is constrained to …

The past decade has witnessed remarkable advances in the simultaneous measurement of
neuronal activity across many brain regions, enabling fundamentally new explorations of the …

A central principle in neuroscience is that neurons within the brain act in concert to produce
perception, cognition, and adaptive behavior. Neurons are organized into specialized brain …

Advances in neural recording present increasing opportunities to study neural activity in
unprecedented detail. Latent variable models (LVMs) are promising tools for analyzing this …

Advances in our understanding of brain function, along with the development of neural
interfaces that allow for the monitoring and activation of neurons, have paved the way for …

Modelling the spatiotemporal dynamics in the activity of neural populations while also
enabling their flexible inference is hindered by the complexity and noisiness of neural …