ARENA is designed for researchers working with deep brain stimulation data, particularly those who need to visualize and analyze spatial 3D information, predict outcomes, or process data from commercial neuroimaging tools.

Prerequisites

• MATLAB (R2019b until R2025a)
  
  • Image Processing toolbox
  • Statistics toolbox
• Git (for cloning the repository)
• lead-dbs.org
• SuretuneSDK

Step-by-step Installation

1. Clone the ARENA repository
2. Download and install dependencies
   
   • Download and install Lead-DBS by following instructions at lead-dbs.org
   • Clone or download SuretuneSDK into a known directory.
3. Navigate to ARENA path inside MATLAB.
4. Run the setup
   >>startArena 
   During this step, you will be prompted to locate the directories of Lead-DBS and SuresuiteSDK. These locations will be stored and not asked again. (Delete config.mat to trigger the set-up procedure again)
5. Launch ARENA
   

   >>startArena 
   or to directly open a 3D viewport:
>>newScene.

Once launched, ARENA displays the 3D viewport, where different actors (data layers) can be added, manipulated, and analyzed. Each actor type supports dynamic visual options such as transparency and color.

ARENA visualizes data through actors—modular components that represent a specific object in 3D space. Actor types are highly flexible and support interaction, transformation, and analysis.

Actors are generally divided into two categories:

• Basic Actors: Represent low-level geometric or imaging data
• Composit Actors: Aggregate multiple components for higher-level interpretation

• VoxelData: 3D volumetric dataset
• VoxelDataStack: a set of VoxelData objects and their weights.
• Fibers: Tractography streamlines
• Electrode: DBS electrodes with contacts
• PointCloud, VectorCloud: Geometric data visualization
• Mesh: 3D shape often based on volumetric data
• ObjFile: 3D shape based on an imported .obj file
• DICOM: Holds original raw files and related ARENA compatible representations of the data.
• Scene: 3D viewport

All these actors can be individually manipulated, visualized, and used in spatial analysis.

ARENA also supports composite actors that integrate multiple data types into a unified structure. These are particularly valuable for advanced research workflows.

• VTA (Volume of Tissue Activated)
  TheVTA class models the region of brain tissue affected by a DBS setup. As it is often the core of a research question The VTA class will hold references to all relevant aspects related to the VTA for contextual metadata.
• Heatmap
  TheVTA class models the region of brain tissue affected by a DBS setup. As it is often the core of a research question The VTA class will hold references to all relevant aspects related to the VTA for contextual metadata.
• LOORoutine
  This composites the input data (VoxelDataStack) and analysis method (BiteAnalysis) and is able to perform leave-one-out analysis with the specified method on the provided data.
• Prediction
  PredictionModels are final products of studies. The prediction class allows to load these models and a VTA, and predict the outcome for the VTA.
• BiteAnalysis
  There are various ways how a VTA can interact with a heatmap to produce a prediction. The BiteAnalysis class provides the framework for a modular design of the tools.

• .: center the camera on the active layer
• arrow keys: move the camera or zoom
• b: invert background colo
• o: center the origin
• cmd+i / ctrl+i: import actor
• return: change layer name
• shift+1: axial view
• shift+2: sagittal view
• shift+3: coronal view
• h: hide or show the layer
• s: allow selecting layer in the 3D viewport.