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‎docs/guide/how_to_get_started_with_neuron.rst‎

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.. _how_to_get_started_with_neuron:
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How to get started with NEURON
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=============
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==============================
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To learn the basics about using NEURON:
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-------------
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What is NEURON?
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---------------
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You'll likely have questions. Ask and answer questions at the `NEURON Discussion Board <https://github.com/neuronsimulator/nrn/discussions>`_
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NEURON is a simulator for neurons and networks of neurons that runs on your local machine,
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in the cloud, or on an HPC cluster.
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Then
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It is built on biophysical models. NEURON simulates neurons using conductance-based equations
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introduced by :ref:`Hodgkin and Huxley <Hodgkin-Huxley cable equations>`, whose work
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establishes the mathematical foundation for how ion channels drive electrical activity in
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model cells.
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1.
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Read `"The NEURON Simulation Environment." <https://pubmed.ncbi.nlm.nih.gov/9248061/#:~:text=The%20NEURON%20simulation%20program%20provides,and%20membrane%20currents%20are%20complex.>`_
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You can build and simulate models using Python, HOC, and/or NEURON's graphical interface.
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2.
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Use the Programmer's Reference early and often. If you are running NEURON under MSWindows and accepted the default installation, the Programmer's Reference is already in the NEURON program group--put a shortcut to it on your desktop. If you are using MacOS or UNIX, you will have to download it separately from the `Documentation page <https://nrn.readthedocs.io/en/latest/python/index.html>`_.
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Download NEURON
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---------------
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Work through the tutorials on the `Documentation <https://nrn.readthedocs.io/en/latest/python/index.html>`_ and `Courses <https://nrn.readthedocs.io/en/latest/courses/exercises2018.html>`_ pages.
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There are two ways to get NEURON running on your system:
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4.
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Use the GUI tools as much as possible. You'll get more done, faster, and you won't have to write any code. Some of the GUI tools are described in the tutorials, and others are demonstrated in more detail in John Moore's User's Manual (see the `Documentation <https://nrn.readthedocs.io/en/latest/python/index.html>`_ page).
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:doc:`Download and run </install/install>` — the standard option for most users. Pre-built
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installers are available for Mac, Windows, and Linux.
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5.
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The GUI tools can also help you learn how to use hoc, NEURON's programming language. The CellBuilder and Network Builder can export hoc code that you can examine and reuse to do new things. You can also save the smaller GUI tools to session files, which contain reusable hoc statements.
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:doc:`Build from source </install/developer>` — for users who need a custom build, want to
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contribute to development, or need to integrate NEURON into a larger software environment.
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Examine `ModelDB <https://modeldb.science>`_ and the list of `publications about NEURON <https://nrn.readthedocs.io/en/latest/publications.html>`_ to find models of interest. Many authors have deposited their model code in ModelDB, posted it somewhere else on the WWW, or will provide code upon request.
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What can NEURON do?
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-------------------
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To learn how to use NMODL to add new mechanisms to NEURON:
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------------------------
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NEURON has been used in hundreds of published studies across computational and experimental
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neuroscience. A few examples of what it can do:
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1.
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First, consider using the ChannelBuilder instead (see the `Documentation page <https://nrn.readthedocs.io/en/latest/python/index.html>`_ for a tutorial). This is an extremely powerful GUI tool for specifying voltage- and ligand-gated ionic conductances. It's much easier to use than NMODL. Mechanisms specified with the ChannelBuilder actually execute *faster* than if they were specified with NMODL. Also, you can use it to make stochastic channel models.
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- `Mainen and Sejnowski (1996) <https://modeldb.science/2488>`_ demonstrated that the complex
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firing patterns seen in cortical neurons can be reproduced by varying the morphology of a
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single cell model built in NEURON.
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If you absolutely must use NMODL (e.g. for ion accumulation mechanisms or to add new kinds of artificial spiking cells), read chapters 9 and 10 of The NEURON Book, or at least the articles "Expanding NEURON's Repertoire of Mechanisms with NMODL" and "Discrete event simulation in the NEURON environment" (downloadable from the `publications about NEURON <https://nrn.readthedocs.io/en/latest/publications.html>`_ page).
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- `Migliore et al. (2014) <https://modeldb.science/151681>`_ used NEURON to simulate
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large-scale networks of olfactory neurons, linking network-level activity to perceptual
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phenomena.
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NEURON comes with a bunch of mod files that can serve as starting points for "programming by example." Under MSWin the default mechanisms (hh, pas, expsyn etc.) are in ``c:\nrn\src\nrnoc`` (on my Linux box this is ``/usr/local/src/nrn-x.x/src/nrnoc``). A large collection of mod files is in ``c:\nrn\examples\nrniv\nmodl`` (Linux ``/usr/local/src/nrn-x.x/share/examples/nrniv/nmodl``).
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- NEURON has also been used to simulate detailed single cell models.
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`Morse et al. (2010) <https://modeldb.science/87284>`_ investigated how early Alzheimer's
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disease affects the electrical excitability of oblique dendrites in hippocampal pyramidal
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neurons. Using a single, anatomically detailed compartmental model of one CA1 pyramidal
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cell, NEURON was used to simulate how amyloid beta blocking A-type potassium channels
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changes the way electrical signals propagate through that cell's dendritic branches.
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4.
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You may also find useful examples in `ModelDB <https://modeldb.science>`_.
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A full list of publications using NEURON is available on the
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:doc:`Publications page </publications-using-neuron>`.
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For courses about NEURON, see the :ref:`Course Exercises <exercises2018>` page and the :ref:`Training Videos <training_videos>` page.
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Learning resources
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------------------
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The resources below are organized by experience level. Within each level, two starting points
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are offered depending on your background — choose the one that fits how you think.
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Beginner
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~~~~~~~~
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**New to computational modeling?**
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If you want to understand NEURON through a biological lens, before the programming bit kicks
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in, use the following resources. These introduce NEURON through its graphical interface and
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biological concepts first.
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- :doc:`What is NEURON </guide/what_is_neuron>` — guide
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- :ref:`Basic Concepts and GUI` — 2021 course video
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- :ref:`Using NEURON's GUI to build and simulate cells` — CNS 2022 video
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- :doc:`Squid axon model </courses/interactive_modeling>` — exercise
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- :doc:`Introduction to the GUI </courses/intro_to_gui>` — exercise
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**Comfortable with Python?**
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Start here if you have a programming background and want to get something running in code first.
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- :doc:`What is NEURON </guide/what_is_neuron>` — guide
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- :doc:`Scripting NEURON basics </tutorials/scripting-neuron-basics>` — CNS 2022 video
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- :doc:`NEURON scripting exercises </courses/neuron_scripting_exercises>` — exercise
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- :doc:`Single compartment model with Hodgkin-Huxley mechanism </courses/using_nmodl_files>` — exercise
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Intermediate
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~~~~~~~~~~~~
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**New to computational modeling?**
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These resources introduce more complex cell models, morphology, and ion channel specification
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through guided examples and GUI tools.
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- :ref:`Branched cells` — 2021 course video
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- :ref:`Adding ion channels` — 2021 course video
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- :ref:`Using NMODL to add new biophysical mechanisms` — CNS 2022 video
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- :doc:`Working with morphometric data and Import3D </courses/using_morphometric_data>` — exercise
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- :ref:`How do I work with neuron morphologies?` — guide
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- :doc:`Using the CellBuilder GUI </guide/cellbuilder>` — guide
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**Comfortable with Python?**
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These resources cover networks, numerical methods, morphology in code, and scripting more
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complex models.
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- :doc:`Using NMODL files </courses/using_nmodl_files>` — exercise
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- :ref:`Networks and numerical methods` — 2021 course video
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- :ref:`Numerical Methods: accuracy, stability, speed` — CNS 2022 video
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- :doc:`Numerical methods exercises </courses/numerical-methods-exercises>` — exercise
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- :doc:`HOC exercises </courses/hoc_exercises>` — exercise
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- :doc:`Ball and Stick 1: Basic cell </tutorials/ball-and-stick-1>` — Python tutorial
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- :doc:`Ball and Stick 2: Build a ring network </tutorials/ball-and-stick-2>` — Python tutorial
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Advanced
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~~~~~~~~
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These resources assume familiarity with both the biological concepts and the scripting
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environment.
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- :ref:`Reaction-diffusion simulations` — CNS 2022 video
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- :doc:`Python RXD tutorials </rxd-tutorials/index>` — tutorial series
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- :doc:`MPI and multithreaded parallelization </courses/mpi_parallelization>` — exercise
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- :doc:`Using the Neuroscience Gateway for HPC </courses/using_nsg_portal>` — exercise
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- :doc:`Ball and Stick 3: Extensible network </tutorials/ball-and-stick-3>` — Python tutorial
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- :doc:`Ball and Stick 4: Parallel vs serial mode </tutorials/ball-and-stick-4>` — Python tutorial
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Going further
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~~~~~~~~~~~~~
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The above list covers some of the structured courses, videos, and exercises available in this
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documentation. There are additional resources worth knowing about as you go further. You can
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work through all materials on the :doc:`Documentation </tutorials/index>` and
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:doc:`Courses </courses/exercises2018>` pages.
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`ModelDB <https://modeldb.science>`_ is a publicly accessible database of published
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computational neuroscience models, many of which were built with NEURON. Once you are
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comfortable running your own simulations, ModelDB is a great resource for finding,
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downloading, and studying real models from the literature. This helps you see how others have
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approached modeling problems similar to your own.
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What's next?
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------------
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In this guide we have covered what NEURON is and what it is built on, and how to download it
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and get it running. Whether you are approaching NEURON from a biological background or a
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programming one, the learning resources above will take you from a single compartment cell all
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the way to large-scale multiscale networks. The tools are well documented, the exercises are
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hands-on, and the concepts build on each other naturally the further you go.
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Welcome to NEURON. Happy simulating.

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