Neuronal networks with strong recurrent connectivity provide the brain with a powerful
means to perform complex computational tasks. However, high-gain excitatory networks are …

Computational modelling has become increasingly common in life science research. To
provide a platform to support universal sharing, easy accessibility and model reproducibility …

Sustainable research on computational models of neuronal networks requires published
models to be understandable, reproducible, and extendable. Missing details or ambiguities …

The neurophysiology of cells and tissues are monitored electrophysiologically and optically
in diverse experiments and species, ranging from flies to humans. Understanding the brain …

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing
and disparate experimental datasets at multiple scales. The NetPyNE tool (www. netpyne …

The need for reproducible, credible, multiscale biological modeling has led to the
development of standardized simulation platforms, such as the widely-used NEURON …

Biophysically detailed neural models are a powerful technique to study neural dynamics in
health and disease with a growing number of established and openly available models. A …

Experimental studies in neuroscience are producing data at a rapidly increasing rate,
providing exciting opportunities and formidable challenges to existing theoretical and …

We developed a detailed model of macaque auditory thalamocortical circuits, including
primary auditory cortex (A1), medial geniculate body (MGB), and thalamic reticular nucleus …

The brain is not a glorified digital computer. It does not store information in registers, and it
does not mathematically transform mental representations to establish perception or …