Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like ...

Active vision dynamically refines spatiotemporal neural representations, optimising visual processing through scanning behaviour and non-associative learning, providing insights into efficient sensory ...

This useful study presents a biologically realistic, large-scale cortical model of the rat's non-barrel somatosensory cortex, investigating synaptic plasticity of excitatory connections under varying ...

In the hippocampus, a critical brain region for learning and memory, new cells emerge in some people into late adulthood, ...

Predicting how molecular changes affect the brain's overall activity is a major challenge in neuroscience. Many deep ...

Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder marked primarily by β-amyloid (Aβ) deposition and abnormal ...

Interpreting complex neural networks is crucial for understanding their decision-making processes, particularly in applications where transparency and accountability are essential. This proposed ...

Ensuring the reliability of deep neural networks (DNNs) is paramount in safety-critical applications. Although introducing supplementary fault-tolerant mechanisms can augment the reliability of DNNs, ...