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Diffusion MRI Tractography Predicts Electrophysiological Connectivity and Explains Spectral Signatures of Evoked Potentials in the Human Brain

  • S. Shailja
  • D. Lyu
  • G. Chau Loo Kung
  • L. Mortazavi
  • E. Dai
  • M. M. Zeineh
  • V. P. Buch
  • K. Deisseroth
  • J. Parvizi
  • J. A. McNab1
  1. 1Stanford University
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Cite

BibTeXRIS
BibTeX
@misc{shailja2026diffusion,
  title = {{Diffusion MRI Tractography Predicts Electrophysiological Connectivity and Explains Spectral Signatures of Evoked Potentials in the Human Brain}},
  author = {S. Shailja and D. Lyu and G. Chau Loo Kung and L. Mortazavi and E. Dai and M. M. Zeineh and V. P. Buch and K. Deisseroth and J. Parvizi and J. A. McNab},
  howpublished = {bioRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.15.751678},
  url = {https://www.biorxiv.org/content/10.64898/2026.09.15.751678v1},
}
RIS
TY  - UNPB
TI  - Diffusion MRI Tractography Predicts Electrophysiological Connectivity and Explains Spectral Signatures of Evoked Potentials in the Human Brain
AU  - S. Shailja
AU  - D. Lyu
AU  - G. Chau Loo Kung
AU  - L. Mortazavi
AU  - E. Dai
AU  - M. M. Zeineh
AU  - V. P. Buch
AU  - K. Deisseroth
AU  - J. Parvizi
AU  - J. A. McNab
PY  - 2026
DA  - 2026/09/15
PB  - bioRxiv
DO  - 10.64898/2026.09.15.751678
UR  - https://www.biorxiv.org/content/10.64898/2026.09.15.751678v1
ER  -