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Stable Yet Destabilised: Towards Understanding Brain Network Dynamics in Psychogenic Disorders.

Mostafa Badr1, Timo Bröhl1,2, Nayrin Dissouky1

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This summary is machine-generated.

Researchers found distinct brain network patterns in psychogenic non-epileptic seizures (PNES) compared to epilepsy. These findings highlight differences in brain communication and stability, offering a potential new diagnostic tool for PNES.

Keywords:
EEGcomplex networksdestabilizationepilepsyfunctional neurological disorderspsychogenic non-epileptic seizurespsychopathologyrobustnessstabilitytime-evolving functional brain networks

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Area of Science:

  • Neuroscience
  • Clinical Neurology
  • Systems Biology

Background:

  • Psychogenic non-epileptic seizures (PNES) present with seizure-like episodes but lack the abnormal electrical activity characteristic of epilepsy.
  • Distinguishing PNES from epilepsy and normal brain function is challenging due to limited etiologic models and diagnostic methods.
  • Understanding the underlying brain dynamics of PNES is crucial for accurate diagnosis and treatment.

Purpose of the Study:

  • To investigate and compare the brain dynamics of individuals with PNES, epilepsy, and healthy controls.
  • To identify subject-specific differences in local and global functional brain network characteristics.
  • To explore the potential of network analysis as a diagnostic tool for differentiating PNES from epilepsy.

Main Methods:

  • Utilized the network ansatz to analyze time-evolving functional brain networks.
  • Examined both local (region-specific) and global (network-wide) characteristics of brain activity.
  • Compared brain dynamics in individuals with PNES, epilepsy, and a control group during interictal periods (far-off seizures).

Main Results:

  • Observed significant subject-specific differences in local network characteristics across the groups, reflecting distinct regional brain functioning.
  • Identified significant differences in global network characteristics related to brain communication, robustness, and stability.
  • Demonstrated that functional brain network analysis can reveal unique patterns associated with PNES.

Conclusions:

  • The study provides novel insights into the neurophysiological mechanisms underlying PNES.
  • Findings suggest that functional brain network analysis offers a promising avenue for developing objective diagnostic methods for PNES.
  • Differentiating PNES from epilepsy may be enhanced by assessing brain network properties.