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A Causal Network Analysis of Neuromodulation in the Mood Processing Network

  • Shaoyu Qiao
  • , J. Isaac Sedillo
  • , Kevin A. Brown
  • , Breonna Ferrentino
  • , Bijan Pesaran

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Neural decoding and neuromodulation technologies hold great promise for treating mood and other brain disorders in next-generation therapies that manipulate functional brain networks. Here we perform a novel causal network analysis to decode multiregional communication in the primate mood processing network and determine how neuromodulation, short-burst tetanic microstimulation (sbTetMS), alters multiregional network communication. The causal network analysis revealed a mechanism of network excitability that regulates when a sender stimulation site communicates with receiver sites. Decoding network excitability from neural activity at modulator sites predicted sender-receiver communication, whereas sbTetMS neuromodulation temporarily disrupted sender-receiver communication. These results reveal specific network mechanisms of multiregional communication and suggest a new generation of brain therapies that combine neural decoding to predict multiregional communication with neuromodulation to disrupt multiregional communication.

Original languageEnglish
Pages (from-to)972-985.e6
JournalNeuron
Volume107
Issue number5
DOIs
StatePublished - 9 Sep 2020
Externally publishedYes

Keywords

  • causal network analysis
  • modulator decoding
  • multiregional communication
  • network edge neuromodulation
  • network excitability

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