This in-person workshop will consist of interactive seminars and hands-on computational work. It will focus on teaching the skills for building and simulating complex and heterogeneous network models grounded in real biological data.

workshop topics/

• Gradient descent training of bio-realistic models of brain circuits
• Building heterogenous neural networks at different levels of resolution
• Simulating networks of biophysically detailed, multicompartmental neuronal models
• Simulating networks of point-neuron models
• Providing realistic spiking inputs to the neural networks
• Simulating perturbations
• Simulating extracellular electric field
• Using and sharing models in the SONATA format
• Visualizing network models’ structure and dynamics in 3D

applications/

Applications have closed.

‍Applicants will be notified of their status by May 1, 2026.

Preference will be given to those applicants who are actively doing research in computational neuroscience or are preparing to start a research project in this area. Note that some prior experience with Python might be useful for this workshop. Experience in modeling is not required or expected.‍

travel funding/

The Allen Institute strives to make training opportunities available on a fair and equitable basis. Some travel funding is available for participants with financial need. Please indicate on your application whether such support is needed. Applications will be evaluated on a need-blind basis.

‍There is no fee to participate in the workshop.

This work was supported by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R01EB029813 and the National Institute Of Neurological Disorders And Stroke of the National Institutes of Health under Award Numbers R01NS122742 and U24NS124001. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Attendees will learn how to use software for building, simulating, and visualizing bio-realistic models of brain circuits including:

• The SONATA file format for multiscale neuronal network models and simulation output, supporting standardized and computationally efficient storage and exchange of models.
• The Brain Modeling ToolKit (BMTK) – a Python-based software package for building and simulating large-scale neural network models at multiple levels of resolution.
• The Visual Neuronal Dynamics (VND) – a program for displaying, animating, and analyzing neural network models using 3D graphics and built-in scripting