VRNConnect: A virtual reality immersive environment for exploring brain
connectivity data
Abstract
Introduction:
A brain connectome models the clusters of neurons as inter-connected
nodes and can be obtained from different imaging techniques, including
diffusion and functional MRI, for structural and functional
connectivity, respectively. It offers us the opportunity to gain further
insights regarding neural circuitry to better understand the mechanisms
of brain functions and diseases. However, visualization, spatial
understanding, and analysis of the network’s topology are difficult due
to the neuroanatomy’s complex configuration of brain parcellation and 3D
nature. Virtual reality (VR) off ers more intuitive visualization
andinteraction for 3D data than traditional 2D displays and is a great
fi t to tackle the challenges in visualizing andanalyzing brain
connectomes. We introduce a novel immersive VR platform for connectomic
data exploration, VRNConnect, with a user-friendly interface for
quantitative network analysis and exploration. We demonstrated the
functionalities of the system with structural connectivity.
Methods:
The VRNConnect software was built using the Unity 3D game engine
(v2021.3) and Oculus integration SDKv38. An Occulus Quest2 VR headset
was used for system development. To create the structural connectome, we
used the DWI and T1w MRI of a single subject provided by the B.A.T.M.A.N
tutorial. Whole braintractography was performed using the iFOD2 and SIFT
algorithms in MRtrix3, and the connectivitymatrix was extracted with the
HCP-MMP1 atlas, resulting in 360 nodes. To allow interactive
networkanalysis, we employed the Brain Connectome Toolbox library (bctpy
v0.6) as the backends for our VR userinterface to compute graph-based
metrics, such as clustering coefficient and the shortest path
betweennodes, which can be calculated on both hop count- or
distance-based. Both controller- and hand gesture basednode and edge
selection and interaction were implemented to pick the node of interest,
and functions,including connectivity strength thresholding and brain
model scaling and zooming. Furthermore, thesoftware allows users to
import their connectomic data and/or utilize their own toolbox (with
minor codingadjustments) for analysis.