Installation
Lead-DBS is a toolbox that works in the MATLAB environment (The Mathworks). The optimal recommended version to use is ML 2020. We try to maintain compatibility to Windows, Unix and macOS, but given our small team, not all functions are well tested on all OSs (fork us on github and join our team to improve that).
Yet, there are some required steps before you can use the toolbox:
  1. 1.
    Download Lead-DBS from https://www.lead-dbs.org/.
  2. 2.
    After downloading and extracting Lead-DBS, set the MATLAB path to include the toolbox folder. To add Lead-DBS to the MATLAB search path, do the following: Go to the File tab. Click on Set Path.... In the new window click on Add with subfolders.... Browse to the location of the Lead-DBS folder and select it. Finally click on Saveand Close.
  3. 3.
    You need SPM12 for normalization and file handling and included to your MATLAB path as well.
Once LEAD is added to your Matlab path, you can run Lead-DBS by entering the command lead dbs into the MATLAB Command Window.

Installation via Github

For more experienced users or developers who'd also wish to modify the code and potentially improve Lead-DBS, there is an alternative way of installation:
  1. 1.
    Clone the Lead-DBS repository from here.
  2. 2.
    Download the necessary datafiles using this link and unzip the downloaded folder into the cloned git repository.
  3. 3.
    We'd love to implement your improvements into Lead-DBS – please contact us for direct push access to Github or feel free to add pull-requests to the Lead-DBS repository.
This alternative way of installation can also be interesting to receive quicker (most often daily) updates on the code and helps us to assist you in a more flexible way.

Installing additional content

Several add-ons are available which can be installed manually from inside Matlab. For most cases, Lead-DBS will try to auto-install these when needed and you can take a look at the Install menu within the main Lead-DBS interface to install custom items.

Further dependencies

The FEM-based VTA model (Horn et al. 2017) needs Fortran dependencies since it uses the SimBio toolbox that is partially based on Fortran code. Please see this page for instructions to install dependencies if needed.