Functional control of electrophysiological network architecture using direct neurostimulation in humans

Ankit N. Khambhati, Ari E. Kahn, Julia Costantini, Youssef Ezzyat, Ethan A. Solomon, Robert E. Gross, Barbara C. Jobst, Sameer A. Sheth, Kareem A. Zaghloul, Gregory Worrell, Sarah Seger, Bradley C. Lega, Shennan Weiss, Michael R. Sperling, Richard Gorniak, Sandhitsu R. Das, Joel M. Stein, Daniel S. Rizzuto, Michael J. Kahana, Timothy H. LucasKathryn A. Davis, Joseph I. Tracy, Danielle S. Bassett

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


Chronically implantable neurostimulation devices are becoming a clinically viable option for treating patients with neurological disease and psychiatric disorders. Neurostimulation offers the ability to probe and manipulate distributed networks of interacting brain areas in dysfunctional circuits. Here, we use tools from network control theory to examine the dynamic reconfiguration of functionally interacting neuronal ensembles during targeted neurostimulation of cortical and subcortical brain structures. By integrating multimodal intracranial recordings and diffusion-weighted imaging from patients with drug-resistant epilepsy, we test hypothesized structural and functional rules that predict altered patterns of synchronized local field potentials. We demonstrate the ability to predictably reconfigure functional interactions depending on stimulation strength and location. Stimulation of areas with structurally weak connections largely modulates the functional hubness of downstream areas and concurrently propels the brain towards more difficult-to-reach dynamical states. By using focal perturbations to bridge large-scale structure, function, and markers of behavior, our findings suggest that stimulation may be tuned to influence different scales of network interactions driving cognition.

Original languageEnglish (US)
Pages (from-to)848-877
Number of pages30
JournalNetwork Neuroscience
Issue number3
StatePublished - Jan 1 2019


  • Electrocorticography
  • Neurostimulation
  • Reconfiguration
  • Structural controllability

ASJC Scopus subject areas

  • General Neuroscience
  • Computer Science Applications
  • Artificial Intelligence
  • Applied Mathematics


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