The brain-computer interface (BCI) connects the brain and the external world through an
information transmission channel by interpreting the physiological information of the brain …

Brain simulation, as one of the latest advances in artificial intelligence, facilitates better
understanding about how information is represented and processed in the brain. The …

Spiking Neural Networks (SNNs) are currently the most widely used computing model for
neuroscience communities. There is also an increasing research interest in exploring the …

Whole brain network models are now an established tool in scientific and clinical research,
however their use in a larger workflow still adds significant informatics complexity. We …

Inter-process communications form a performance bottleneck for large-scale brain
simulations. The sparse and imbalanced communication patterns of human brain make it …

Introduction In-silico simulations are a powerful tool in modern neuroscience for enhancing
our understanding of complex brain systems at various physiological levels. To model …

Modern neuroscience employs in silico experimentation on ever-increasing and more
detailed neural networks. The high modeling detail goes hand in hand with the need for high …

Brain simulation is one of the most important measures to understand how information is
represented and processed in the brain, which usually needs to be realized in …

Global neural dynamics emerge from multi-scale brain structures, with nodes dynamically
communicating to form transient ensembles that may represent neural information. Neural …

In modern computational modeling, neuroscientists need to reproduce long-lasting activity of
large-scale networks, where neurons are described by highly complex mathematical …