Background: More effective strategies are needed to promote poststroke functional recovery.
Here, we evaluated the impact of bihemispheric transcranial direct current stimulation …

The research on robustness of brain-like models contributes to promoting its neural
information processing ability, and the understanding of bio-brain function. However, the …

Random fluctuations are inescapable feature in biological systems, but appropriate intensity
of randomness can effectively facilitate information transfer and memory encoding within the …

Neural modelling tools are increasingly employed to describe, explain, and predict the
human brain's behavior. Among them, spiking neural networks (SNNs) make possible the …

Background: Mathematical modeling and computer simulation are important methods for
understanding complex neural systems. The whole-brain network model can help people …

The essential ingredient for studying the phenomena of emergence is the ability to generate
and manipulate emergent systems that span large scales. Cellular automata are the model …

The human neuroregulator system is a complex nervous system composed of a
heterogeneous group of nerve centres distributed along the spinal cord. These centres act …

Reservoir computing is a powerful computational framework that is particularly successful in
time-series prediction tasks. It utilises a brain-inspired recurrent neural network and allows …

The human neuroregulator system is a complex nervous system composed of a
heterogeneous group of nerve centres distributed along the spinal cord. These centres act …