@article{Li_2026_ProcNatlAcadSci_Functional,
    abstract = {The brain is organized into networks that support thought, emotion, and consciousness. While scientists have mapped these networks across the cerebral cortex for decades, connectivity of subcortical regions remains poorly understood. This gap exists because deep brain regions are difficult to image, and networks overlap there in ways that standard methods cannot untangle. We developed a computational approach that solves both problems simultaneously, producing complete and reliable maps of network organization within subcortical structures. We show that these maps can predict levels of consciousness in patients with severe brain injury, illustrating their potential clinical value, and provide a long-missing reference that can guide more precise and effective therapies for a wide range of neurological and psychiatric conditions. The human brain operates through large-scale networks whose subcortical components are critical for consciousness, emotion, and cognition. While cortical network connectivity has been mapped with increasing precision, subcortical network mapping has lagged far behind due to two fundamental barriers: the overlapping and correlated nature of brain networks, which conventional analytic methods cannot disentangle, and the inherently low signal-to-noise ratio of functional imaging data within the subcortex. As a result, no consensus or normative atlas for subcortical functional brain connectivity exists—a critical gap that has impeded both basic neuroscience and the development of targeted neuromodulatory therapies. In this work, we address these barriers using NASCAR, a tensor decomposition method explicitly designed to separate overlapping and correlated networks, applied to resting-state functional MRI data from 1,000 healthy individuals in the Human Connectome Project. This approach enabled us to fractionate four large-scale brain networks into 15 highly reproducible subnetworks spanning both cortical and subcortical structures, revealing their sites of neuroanatomic overlap and defining a normative whole-brain functional atlas grounded in subcortical connectivity. As proof of principle for the translational potential of this framework, we show that individual patterns of subnetworks predict levels of consciousness in patients with severe traumatic brain injury. By establishing a gold-standard, openly accessible reference for subcortical functional brain organization, this work expands the landscape of human brain network mapping and opens avenues for precision targeting in the treatment of a broad spectrum of neurological and psychiatric disorders.},
    author = {Li, Jian and Atalay, Alexander S. and Olchanyi, Mark D. and Cambareri, Morgan K. and Ghosh, Satrajit S. and Horn, Andreas and Lewis, Laura D. and Brown, Emery N. and Fischl, Bruce and Kinney, Hannah C. and Edlow, Brian L.},
    doi = {10.1073/pnas.2608875123},
    journal = {Proceedings of the National Academy of Sciences},
    number = {36},
    pages = {e2608875123},
    title = {Functional fractionation of large-scale brain networks in human subcortex},
    volume = {123},
    year = {2026}
}