written by: Justin Park
Brain tractography is a neuroimaging technique that reconstructs the white matter pathways connecting different regions of the brain. Using diffusion MRI — a type of scan sensitive to the movement of water molecules along nerve fibers — tractography algorithms trace the direction and path of fiber bundles through the brain, producing 3D streamlines that represent structural connectivity. The full set of these connections forms the structural connectome: a map of how the brain is physically wired.
Tractography is used in neuroscience research to study how brain regions communicate, in clinical settings to plan neurosurgery by identifying critical pathways that must be preserved, and in educational contexts to teach neuroanatomy. It is one of the few techniques that makes the brain's internal wiring directly visible rather than inferred from functional signals alone.
The visualization problem
Tractography data is inherently three-dimensional, but standard desktop tools display it on flat screens. This creates a fundamental mismatch. When viewing a 2D projection of fiber tracts, the viewer must mentally reconstruct the 3D path of each bundle from a static image — a process that is cognitively demanding and error-prone, particularly for users without extensive neuroanatomy training.
A second problem is density. A full-brain tractography dataset can contain hundreds of thousands of streamlines. Displaying all of them simultaneously produces what researchers call the hairball problem: a dense, tangled mass of lines that is visually overwhelming and nearly impossible to interpret. Both 2D and 3D tools address this through tract isolation — displaying one named bundle at a time — but the spatial context of where that bundle sits relative to the rest of the brain is easier to preserve in 3D.
A third challenge is depth perception. Determining whether a fiber tract runs along the outer surface of the brain, deep in the center, or from top to bottom is straightforward in a 3D spatial environment but genuinely difficult from a 2D screen, where depth must be inferred from shading, occlusion, and prior anatomical knowledge.
Why AR is a natural fit
Augmented reality addresses the core visualization problem directly. When tractography data is anchored in physical space via passthrough AR, depth is perceived through natural stereo vision and head motion parallax rather than inferred from flat cues. A user can walk around the brain volume, crouch to look at structures from below, or lean in to examine a specific region — interactions that are impossible with a flat screen and qualitatively different from a fully immersive VR experience.
AR also preserves real-world context. Unlike VR, which replaces the physical environment entirely, passthrough AR keeps the room visible. This allows users to use their hands naturally, reference printed materials alongside the visualization, and collaborate with others in the same physical space without losing situational awareness.
Scaling is another advantage specific to AR. A tractography volume can be scaled from palm size — useful for getting an overview of the full connectome — up to room scale, where users can physically walk through individual fiber bundles and experience their paths through space from the inside. This range of interaction is unique to spatial computing and has no equivalent in 2D tools.
Color conventions in tractography
Most tractography tools, including DSI Studio and MRtrix, use directional color coding as the standard visualization convention. Each streamline is colored based on the local direction of the fiber at that point:
Red indicates fibers running left to right across the brain
Green indicates fibers running front to back
Blue indicates fibers running up and down
This convention is consistent across most research software, meaning that a viewer familiar with the color scheme can immediately read the orientation of any fiber bundle from its color without needing labels. In AR builds that aim to match the experience of standard desktop tools, applying this same color convention is important for comparability.
Major white matter tract systems
The corpus callosum is the largest white matter structure in the brain, forming a thick band of fibers that connects the left and right cerebral hemispheres. It allows the two sides of the brain to share information and coordinate activity. In tractography it appears as a broad, horizontally running structure in the center of the brain, typically red under directional color coding.
The corticospinal tract carries motor signals from the motor cortex at the top of the brain down through the brainstem and into the spinal cord, ultimately controlling voluntary movement throughout the body. It runs vertically through the brain and appears predominantly blue under directional color coding.
The arcuate fasciculus is a curved bundle that arcs along the outer edge of one hemisphere, connecting frontal and temporal language areas. It is strongly associated with speech production and comprehension, and damage to it is linked to certain types of aphasia. It typically appears as a mix of green and blue fibers curving around the lateral surface of the brain.
The superior longitudinal fasciculus is a set of association fibers running along the length of each hemisphere, connecting frontal, parietal, and occipital regions. It is involved in attention, spatial awareness, and language.
The uncinate fasciculus connects the frontal lobe to the temporal lobe, passing through the base of the brain. It is implicated in memory, social cognition, and emotional processing.
Existing AR and VR tractography tools
Most current tractography visualization happens on standard 2D desktop software. DSI Studio is the most widely used tool, offering interactive fiber tracking, an atlas of named tract systems, and connectivity analysis. It is optimized for 2D screen navigation and serves as the baseline against which spatial AR/VR approaches are typically compared.
On the VR and AR side, dedicated tractography tools are limited. Nanome provides VR-native molecular and structural visualization but is primarily designed for biochemistry rather than diffusion MRI data. Some academic groups have built custom Unity-based viewers for specific research purposes, and commercial surgical AR systems from companies including Stryker and Medivis overlay patient imaging data in operating rooms, though these are closed clinical tools rather than general research platforms.
The gap between what 2D desktop tools offer and what spatial computing makes possible is the motivation for research projects like Connected, which build custom AR tractography viewers and evaluate them against standard 2D tools to understand where spatial exploration genuinely improves comprehension and where it does not.