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Traditional brain connectivity analysis examines pairwise relationships between brain regions. Higher-order connectivity captures interactions among three or more regions simultaneously using mathematical tools like simplicial complexes, hypergraphs, and information-theoretic measures like O-information.

NeuroVision is currently available to academic institutions through our early access program. Contact us to request a demo and discuss licensing options. We offer free academic licenses for non-commercial research.

Yes, we actively recruit PhD students with backgrounds in mathematics, computer science, or neuroscience. Applicants should have strong programming skills (Python, JAX/PyTorch) and interest in topological data analysis or geometric deep learning.

HINEC-OI and several other tools are available on our GitHub under MIT license. They require Python 3.10+, JAX, and an NVIDIA GPU for optimal performance. Documentation and tutorials are available on our GitHub wiki.

Collaborations vary from 3-month pilot projects to multi-year research programs. We recommend starting with a pilot to establish data sharing agreements and validate the approach before committing to longer engagements.

Yes, we accept donations through Yonsei University Development Foundation. All donations are tax-deductible and directly support our research operations, student fellowships, and computational infrastructure.