Calcium ions generate versatile intracellular signals that control key functions in all types of
neurons. Imaging calcium in neurons is particularly important because calcium signals exert …

The brain continuously adapts its processing machinery to behavioural demands. To
achieve this, it rapidly modulates the operating mode of cortical circuits, controlling the way …

Calcium imaging with protein-based indicators, is widely used to follow neural activity in
intact nervous systems, but current protein sensors report neural activity at timescales much …

Future brain-machine interfaces, prosthetics, and intelligent soft robotics will require
integrating artificial neuromorphic devices with biological systems. Due to their poor …

The growing energy and performance costs of deep learning have driven the community to
reduce the size of neural networks by selectively pruning components. Similarly to their …

The cone photoreceptors in our eyes selectively transduce the natural light into spiking
representations, which endows the brain with high energy-efficiency color vision. However …

This paper studies the curious phenomenon for machine learning models with Transformer
architectures that their activation maps are sparse. By activation map we refer to the …

The coexistence of amyloid-β (Aβ) plaques and tau neurofibrillary tangles in the neocortex is
linked to neural system failure and cognitive decline in Alzheimer's disease. However, the …

Genetically encoded calcium indicators (GECIs) are powerful tools for systems
neuroscience. Recent efforts in protein engineering have significantly increased the …

Alzheimer's disease (AD) is characterized by a progressive dysfunction of central neurons.
Recent experimental evidence indicates that in the cortex, in addition to the silencing of a …