On this page you can find download links for DigiCortex. Starting from version 0.5, there are no separate AVX-optimized builds anymore (AVX/AVX2 optimizations are integrated in one executable and enabled during runtime if appropriate CPU is detected). In addition, download installation contains both 32-bit and 64-bit builds.

Latest Build: Change Log:
DigiCortex Demo Latest Version - 1.29 Change Log
DigiCortex White Paper

Please note: by downloading this software you agree with the following: Usage of DigiCortex is completely on your own risk and the author assumes no responsibility for any damage and/or loss caused by your usage of DigiCortex. DigiCortex is extremely CPU and memory intensive application, performing large amounts of calculations which can cause the CPU and memory to get very hot and to operate at their thermal limits. If you are running DigiCortex on a notebook - please ensure that it is properly ventilated / cooled and connected to AC power.


Oculus Rift visualization support:: Example how to run simulation in Oculus Rift mode can be found here (click)

CUDA support: Support for CUDA (Compute Capability 2.0 and higher) is available starting from v0.95. To enable CUDA, rename DigiCortexConfig.cuda to DigiCortexConfig.xml.

Support for more than 32 logical CPUs: Please use 64-bit build of DigiCortex if your system contains more than 32 logical CPUs. 32-bit version of DigiCortex is limited to 32 logical CPUs and will not be able to use any additional available cores.

  • For CPUs with AVX/AVX2 support, 64-bit builds are typically ~10% faster than 32-bit builds
  • 64-bit builds require 64-bit Windows™ OS to run and allow simulations that require more than 4 GB of RAM
  • AVX support requires AVX-aware OS (Windows 7 SP1, Windows Server 2008 R2 SP1 or with hotfix 2517374)
  • DigiCortex can also run on Linux using Wine adaptation layer (OpenGL compatibility might vary). AVX support requires Linux Kernels 2.6.30 or later
  • DigiCortex requires CPUs with at least SSE3 instruction set (such as Intel Pentium™ 4 or compatible CPUs)
  • OpenGL visualizations require GPU supporting OpenGL 2.0 (including shaders)


Diffusion MRI Data collection and sharing for this project was provided by the Human Connectome Project (HCP; Principal Investigators: Bruce Rosen, M.D., Ph.D., Arthur W. Toga, Ph.D., Van J. Weeden, MD). HCP funding was provided by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute of Mental Health (NIMH), and the National Institute of Neurological Disorders and Stroke (NINDS). HCP data are disseminated by the Laboratory of Neuro Imaging at the University of California, Los Angeles.