Neuron modeling may be said to have originated with the Hodgkin and Huxley action
potential model in 1952 and Rall's models of integrative activity of dendrites in 1964. Over …

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

Computational models are powerful tools for exploring the properties of complex biological
systems. In neuroscience, data-driven models of neural circuits that span multiple scales are …

With rapidly advancing multi-electrode recording technology, the local field potential (LFP)
has again become a popular measure of neuronal activity in both research and clinical …

The increasing availability of quantitative data on the human brain is opening new avenues
to study neural function and dysfunction, thus bringing us closer and closer to the …

Objective: Like all scientific research, computational neuroscience research must be
reproducible. Big data science, including simulation research, cannot depend exclusively on …

The modeling of extended microcircuits is emerging as an effective tool to simulate the
neurophysiological correlates of brain activity and to investigate brain dysfunctions …

Gamma (∼ 40-90 Hz) and beta (∼ 15-40 Hz) oscillations and their associated neuronal
assemblies are key features of neuronal sensory processing. However, the mechanisms …

The number of functional genes coding for olfactory receptors differs markedly between
species and has repeatedly been suggested to be predictive of a species' olfactory …

As researchers develop computational models of neural systems with increasing
sophistication and scale, it is often the case that fully de novo model development is …