Computational Neuroscience and Neuroinformatics

Aims and scope

Improving our understanding of brain function requires interdisciplinary collaborations between theoretical, computational, and experimental disciplines and approaches. This section fosters multidisciplinary interactions between theoretical, computational, and experimental work in the field of neuroscience.

We invite original contributions on a wide range of topics that promote theoretical modeling focused on understanding neural function at the molecular, cellular, and circuit levels via computational and model-based approaches that are experimentally testable. While the section is primarily focused on theoretical and computational research, it welcomes experimental studies that validate and test theoretical conclusions. Primarily theoretical manuscripts should be highly relevant to the neural mechanisms of the neural function, while primarily experimental manuscripts should have implications for the computational analysis of nervous system function.

Manuscripts investigating physiological mechanisms underlying neuropathologies by combining theoretical and experimental approaches are highly encouraged. Similarly, manuscripts describing novel technological advances in data analysis techniques to further insights into the function of the nervous system are also highly encouraged. Modeling approaches at all levels, from biophysically motivated realistic simulations of neurons and synapses to high-level behavioral models of inference and decision-making, are also welcome.

• Neural modeling
• Neural computation
• Neural engineering
• Neural signal processing
• Brain–computer interfaces
• Neuroinformatics
• Neural circuits
• Machine learning
• Cognitive systems
• Perception
• Neurobiologically inspired evolutionary systems