Uncovering hidden resting state dynamics: A new perspective on auditory verbal hallucinations

Hanna Honcamp, Michael Schwartze, David E.J. Linden, Wael El-Deredy, Sonja A. Kotz*

*Corresponding author for this work

Research output: Contribution to journal(Systematic) Review article peer-review

1 Citation (Web of Science)


In the absence of sensory stimulation, the brain transits between distinct functional networks. Network dynamics such as transition patterns and the time the brain stays in each network link to cognition and behavior and are subject to much investigation. Auditory verbal hallucinations (AVH), the temporally fluctuating unprovoked experience of hearing voices, are associated with aberrant resting state network activity. However, we lack a clear understanding of how different networks contribute to aberrant activity over time. An accurate characterization of latent network dynamics and their relation to neurocognitive changes necessitates methods that capture the sub-second temporal fluctuations of the networks' functional connectivity signatures. Here, we critically evaluate the assumptions and sensitivity of several approaches commonly used to assess temporal dynamics of brain connectivity states in M/EEG and fMRI research, highlighting methodological constraints and their clinical relevance to AVH. Identifying altered brain connectivity states linked to AVH can facilitate the detection of predictive disease markers and ultimately be valuable for generating individual risk profiles, differential diagnosis, targeted intervention, and treatment strategies.

Original languageEnglish
Article number119188
Number of pages14
Early online date7 Apr 2022
Publication statusPublished - 15 Jul 2022


  • Auditory verbal hallucinations
  • Brain connectivity states
  • Dynamic functional connectivity
  • Hidden Semi Markov models
  • Resting state networks
  • Temporal dynamics

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