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 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 …

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 …

Neurophysiology has long progressed through exploratory experiments and chance
discoveries. Anecdotes abound of researchers listening to spikes in real time and noticing …

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 …

Achieving state-of-the-art performance with deep neural population dynamics models
requires extensive hyperparameter tuning for each dataset. AutoLFADS is a model-tuning …

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 …

The existence of a multiple-demand cortical system with an adaptive, domain-general, role
in cognition has been proposed, but the underlying dynamic mechanisms and their links to …

Understanding how biological visual systems process information is challenging because of
the nonlinear relationship between visual input and neuronal responses. Artificial neural …