Simultaneous recordings from hundreds or thousands of neurons are becoming routine
because of innovations in instrumentation, molecular tools, and data processing software …

The nervous system evolved to enable navigation throughout the environment in the pursuit
of resources. Evolutionarily newer structures allowed increasingly complex adaptations but …

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 …

The medial prefrontal cortex (mPFC) has been proposed to link sensory inputs and
behavioral outputs to mediate the execution of learned behaviors. However, how such a link …

The neural population spiking activity recorded by intracortical brain-computer interfaces
(iBCIs) contain rich structure. Current models of such spiking activity are largely prepared for …

Neural dynamics can reflect intrinsic dynamics or dynamic inputs, such as sensory inputs or
inputs from other brain regions. To avoid misinterpreting temporally structured inputs as …

Artificial neural networks (ANNs) are a powerful class of computational models for
unravelling neural mechanisms of brain function. However, for neural control of movement …

Common measures of neural representational (dis) similarity are designed to be insensitive
to rotations and reflections of the neural activation space. Motivated by the premise that the …

Understanding how subjects perceive sensory stimuli in their environment and use this
information to guide appropriate actions is a major challenge in neuroscience. To study …

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 …