NEURON can be installed on a wide variety of hardware platforms. Based on your system and software environment you can choose one of the installation method described below.

Installing Binary Distribution

If you want to quickly get started with NEURON, we provide binary installers for Linux, Mac and Windows platforms.


On Windows only recommended way to install NEURON is using binary installer. You can download alpha or recent releases from below URLs:

Windows installers have name in the format of nrn-<version-id>-mingw-py-36-37-38-39-setup.exe. The py-36-37-38-39 string in the installer name indicates that the given installer is compatible with Python versions 3.6, 3.7, 3.8 and 3.9. Once the installer is downloaded, you can install it by double clicking like any other Windows application. Note that you have to install python separately if python support is required. You can find detailed step-by-step instructions in [this presentation] (

Mac OS

Since version 7.8.1 we are providing Python wheels and NEURON can be installed using pip as:

pip3 install neuron

Python wheels are provided via Note that Python2 wheels are provided for the 8.0.x release series exclusively.

Like Windows, you can also use a binary installer to install NEURON. You can download alpha or recent releases from below URLs:

Mac OS installers have name in the format of nrn-<version-id>-osx-36-37-38-39.pkg. Like windows installer, py-36-37-38-39 string in the installer name indicates that the given installer is compatible with Python versions 3.6, 3.7, 3.8 and 3.9. Note that if you double-click the installer then you might see warning like below. In this case you have to right-click on the installer and then click Open. You can then see an option to Open installer:

Installer Warning

This will install NEURON under directory /Applications/NEURON-<version>/ directory. For GUI support you have to install XQuartz separately. Once you start Terminal application, NEURON binaries (nrniv, neurondemo etc.) should be available to start.


Like Mac OS, since 7.8.1 release python wheels are provided and you can use pip to install NEURON as:

pip3 install neuron

Note that Python2 wheels are provided for the 8.0.x release series exclusively. Also, we are not providing .rpm or .deb installers for recent releases.

Installing Source Distributions

If you are running NEURON in cluster/HPC environment where you would like to have better performance (e.g. using vendor compilers like Intel, Cray, AMD, NVIDIA etc.), we advise you to build the NEURON from source. Note that to use CoreNEURON with optimised CPU/GPU support, you have to install NEURON from source.

Install Build Dependencies

In order to build NEURON from source, the following packages must be available:

  • Bison
  • Flex
  • C/C++ compiler suite
  • CMake 3.15.0

The following packages are optional (see build options):

  • Python >=3.6 (for Python interface)
  • Cython (for RXD)
  • MPI (for parallel)
  • X11 (Linux) or XQuartz (MacOS) (for GUI)

Depending on platform you can install these dependencies as follows:

Mac OS

This is for x86_64. For Apple M1 (arm64), see here

The easiest way to install dependencies on Mac OS is to use brew or conda package manager. For example, once brew is installed you can do:

brew install coreutils openmpi cmake
brew install --cask xquartz

Once these packages are installed, you can setup PATH as:

export PATH=/usr/local/bin/:$PATH

If the desired python version is not installed, you can install it using official distribution. Also, note that Xcode Command Line Tools needs to be installed for development.

Apple M1

  • Install command line tools as

    xcode-select --install
  • If desire classical NEURON GUI : from, click “Releases”, click XQuartz-2.8.0_beta3 , and follow instructions. After installing, logout and log back in.

    If you desire single click button action for X11 when entering a window then execute below command:

    defaults write org.xquartz.X11 wm_ffm -bool true

    For the new default to take effect, logout then log back in.

  • Install dependencies with HomeBrew and pip as:

    # install brew and initialize shell
    /bin/bash -c "$(curl -fsSL"
    echo 'eval $(/opt/homebrew/bin/brew shellenv)' >> $HOME/.zprofile
    eval $(/opt/homebrew/bin/brew shellenv)
    brew install cmake
    brew install open-mpi
    pip3 install --user --upgrade pip
    export PATH="$HOME/Library/Python/3.8/bin":$PATH
    pip3 install --user cython


Depending on the platform (Ubuntu, CentOS, Fedora, Debian, Red Hat etc.), there are different ways to install dependencies. For example, on Ubuntu:

sudo apt-get update
sudo apt-get install -y bison cmake flex git \
     libncurses-dev libopenmpi-dev libx11-dev \
     libxcomposite-dev openmpi-bin python3-dev
# for python dependencies
pip install scipy numpy cython

We recommend using platform specific instructions provided in nrn-build-ci repository.

Install NEURON using CMake

Starting with the 7.8.1 release, NEURON can be installed using the CMake build system. One of the primary advantages of a CMake-based build system is cross-platform support and integration with other projects like Interviews, CoreNEURON, NMODL etc. These projects are now integrated into single a CMake-based build system, and they can be installed together as shown below:

  1. Clone the latest version or specific release:
git clone           # latest development branch
git clone -b 7.8.2  # specific release version 7.8.2
cd nrn
  1. Create a build directory:
mkdir build
cd build
  1. Run cmake with the appropriate options (see below for a list of common options). A full list of options can be found in nrn/CMakeLists.txt and defaults are shown in nrn/cmake/BuildOptionDefaults.cmake. e.g. a bare-bones installation:
cmake .. \
  1. Build the code:
cmake --build . --parallel 8 --target install

Feel free to set the number of parallel jobs according to your system using the --parallel option.

  1. Set PATH and PYTHONPATH environmental variables to use the installation:
export PATH=/path/to/install/directory/bin:$PATH
export PYTHONPATH=/path/to/install/directory/lib/python:$PYTHONPATH

Particularly useful CMake options are (use ON to enable and OFF to disable feature):

  • -DNRN_ENABLE_INTERVIEWS=OFF : Disable Interviews (native GUI support)
  • -DNRN_ENABLE_PYTHON=OFF : Disable Python support
  • -DNRN_ENABLE_MPI=OFF : Disable MPI support for parallelization
  • -DNRN_ENABLE_RX3D=OFF : Disable rx3d support
  • -DNRN_ENABLE_TESTS=ON : Enable unit tests
  • -DPYTHON_EXECUTABLE=/python/binary/path : Use provided Python binary to build Python interface
  • -DCMAKE_INSTALL_PREFIX=/install/dir/path : Location for installing
  • -DCORENRN_ENABLE_NMODL=ON : Use NMODL instead of MOD2C for code generation with CoreNEURON

Please refer to docs/cmake_doc/options.rst for more information on the CMake options.

Optimized CPU and GPU Support using CoreNEURON

NEURON now integrates CoreNEURON library for improved simulation performance on modern CPU and GPU architectures. CoreNEURON is designed as a library within the NEURON simulator and can transparently handle all spiking network simulations including gap junction coupling with the fixed time step method. You can find detailed instructions here and here.

Run integrated tests

NEURON includes also some unit and integration tests. To enable you need to set the CMake flag -DNRN_ENABLE_TESTS=ON. The tests lie in the test directory and cover various aspects of NEURON:

  • CoreNEURON integration (if enabled in build step)
  • Functionality and result regression test for ringtest and testcorenrn
  • HOC interpreter tests
  • Python interpreter tests
  • Parallel Context tests
  • Rx3d tests
  • Unit tests
  • GapJunction tests

To run the tests it’s needed to:

cd nrn/build
cmake .. \
cmake --build . --parallel 8
ctest # use --parallel for speed, -R to run specific tests


  • I am getting link errors “undefined reference to ‘tgoto, tgetent, tputs’”.

This is often an issue due to missing ncurses library linking. In this case, we recommend passing your ncurses installation via CMake. For example on Mac OS with a homebrew installation: -DCMAKE_PREFIX_PATH="/usr/local/opt/ncurses" CMake option.

  • I installed NEURON via pip but while using MPI I get “could not dynamically load or”.

NEURON will try to find MPI library in the standard library paths (e.g. /usr/lib). But on some systems MPI libraries may not be in standard path. In that case you can try setting LD_LIBRARY_PATH (on linux) or DYLD_LIBRARY_PATH (on Mac OS):

export LD_LIBRARY_PATH=/path/of/mpi/installation/lib:$LD_LIBRARY_PATH

In some scenarios this may not be enough (e.g. with Anaconda installed MPI) in which case you can explicitly provide the path of MPI library using:

export MPI_LIB_NRN_PATH=/Applications/anaconda3/lib/libmpi.12.dylib
  • Can I move installation directory?

As with any other UNIX package, it is not a good idea to move NEURON around once you’ve installed it, because the directory names are coded into the files themselves. If you need to move it, put a soft link in its original location that points to the new location (so the old filenames will still work). Better yet, simply recompile neuron specifying the new installation directory.

  • How can I compile my mod files?
    • cd to the directory that contains your .mod files.
    • type “/install/dir/bin/nrnivmodl” (or, if you put that directory in your path, just type “nrnivmodl”)

This will create a subdirectory of the current directory which is your CPU name (e.g. x86_64). Inside this directory is created the program “special”, which is the neuron binary that you want to run instead of nrniv.

  • NEURON fails to launch because shared libraries cannot be found.

Make sure to LD_LIBRARY_PATH or DYLD_LIBRARY_PATH environmental variables. For example, using bash shell:

export LD_LIBRARY_PATH=/install/path/lib:$LD_LIBRARY_PATH. # on linux
export DYLD_LIBRARY_PATH=/install/path/lib:$DYLD_LIBRARY_PATH. # on Mac OS
  • NEURON is not able to find correct Python or NEURON Python library. What can I do?

NEURON tries to find correct Python based on user’s environment. If you are using NEURON via python interpreter then, as mentioned previously, setting PYTHONPATH would be sufficient. For nrniv or special binaries, you can also use -pyexe option to specify which Python should be used by NEURON:

nrniv -pyexe /python/install/path/python-3.8.3/bin/python3

If you have enabled dynamic python support using NRN_ENABLE_PYTHON_DYNAMIC CMake option or installed NEURON via pip and see error like below:

Could not load libnrnpython3

then NEURON is not able to find appropriate Python and corresponding Python library. You can verify which Python is being used by running following command:

export NRN_PYTHONHOME="/python/install/path/python-3.8.3/"
export NRN_PYLIB="/python/install/path/python-3.8.3/lib/"

If NRN_PYTHONHOME and NRN_PYLIB are inappropriate then you can set them explicitly or use -pyexe option mentioned above.

  • How to build NEURON in cluster environment where build node architecture is different than compute node?

In cluster environment, sometime we have different architecture of login/build nodes than compute nodes (similar to cross-compile environment). NEURON has tools like nocmodl, modlunit which are executed on login/build nodes. If these tools are compiled with compute node architecture then we might see error like:

[ 10%] Generating ../../../src/nrnoc/syn.c
Please verify that both the operating system and the processor support Intel(R) AVX512ER and AVX512PF instructions.

or even segmentation fault when MOD files are translated to C files.

To avoid this, we have to build nocmodl, modlunit with login/build node architecture. NEURON by default set -O0 compile flag for these tools to avoid compiler generating architecture specific instructions. But if this is not sufficient, you can set NRN_NMODL_CXX_FLAGS CMake option specifying which compiler flags should be used. For example:

cmake .. [other options] \
    -DCMAKE_CXX_FLAGS="-O3 -xMIC-AVX512" \

In the above example, we used custom build type with Intel compiler’s -xMIC-AVX512 flag for KNL architecture but used -xHost flag so that nocmodl and modlunit are compiled compatible with host architecture (i.e. node where NEURON is being built).

  • I’m getting “unrecognized command-line option” build errors on macos as python extensions are being built.

    Certain combinations of Python environment and C/C++ compiler on macos may lead to build errors of this kind:

running build_ext
building 'neuron.rxd.geometry3d.graphicsPrimitives' extension
creating build
creating build/temp.macosx-10.15-x86_64-2.7
/usr/local/bin/gcc-10 -fno-strict-aliasing -fno-common -dynamic -g -Os -pipe -fno-common -fno-strict-aliasing -fwrapv -DENABLE_DTRACE -DMACOSX -DNDEBUG -Wall -Wstrict-prototypes -Wshorten-64-to-32 -iwithsysroot /usr/local/libressl/include -DNDEBUG -g -fwrapv -Os -Wall -Wstrict-prototypes -DENABLE_DTRACE -arch x86_64 -pipe -I/Users/user/nrn/share/lib/python/neuron/rxd/geometry3d -I. -I/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/core/include -I/Applications/ -c graphicsPrimitives.cpp -o build/temp.macosx-10.15-x86_64-2.7/graphicsPrimitives.o -O0
gcc-10: error: /usr/local/libressl/include: No such file or directory
gcc-10: error: unrecognized command-line option '-Wshorten-64-to-32'
gcc-10: error: unrecognized command-line option '-iwithsysroot'; did you mean '-isysroot'?
error: command '/usr/local/bin/gcc-10' failed with exit status 1

The reason for this type of failure is that Python will provide build command-arguments for extension building based on its own build. If the compiler used to build NEURON expects different commands (eg. gcc vs. clang) then above error will be encountered.

A workaround for this issue is to set the CFLAGS environment variable providing build arguments compatible with your compiler. Here is an example for gcc/clang:

export CFLAGS="-fno-strict-aliasing -fno-common -dynamic -g -Os -pipe -DMACOSX -DNDEBUG -Wall -Wstrict-prototypes"