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Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy
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Altered brain function in persistent postural perceptual dizziness: A study on resting state functional connectivity.

Jin-Ok Lee1, Eek-Sung Lee2, Ji-Soo Kim1

  • 1Department of Neurology, Seoul National University of College of Medicine, Seoul National University Bundang Hospital, Republic of Korea.

Human Brain Mapping
|April 16, 2018
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Summary
This summary is machine-generated.

Persistent postural perceptual dizziness (PPPD) patients exhibit altered brain connectivity. Resting-state fMRI reveals distinct network patterns in PPPD, potentially serving as an imaging biomarker for this condition.

Keywords:
functional connectivitypersistent postural perceptual dizzinessresting state functional imagingsupport vector machinevertigo

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Area of Science:

  • Neuroimaging
  • Clinical Neuroscience
  • Medical Diagnostics

Background:

  • Persistent postural perceptual dizziness (PPPD) is a chronic condition affecting balance and spatial orientation.
  • Understanding the neural underpinnings of PPPD is crucial for developing effective diagnostic and therapeutic strategies.

Purpose of the Study:

  • To investigate whole-brain functional network alterations in patients with PPPD using resting-state functional magnetic resonance imaging (rsfMRI).
  • To identify potential neuroimaging biomarkers for PPPD classification.

Main Methods:

  • rsfMRI data from 38 PPPD patients and 38 healthy controls were analyzed using whole-brain and region-of-interest approaches.
  • Correlations between brain connectivity and clinical variables (dizziness handicap, anxiety, depression) were examined.
  • A machine learning algorithm was employed to classify subjects based on rsfMRI connectivity patterns.

Main Results:

  • PPPD patients showed increased connectivity between the subcallosal cortex and visual/frontal areas, and decreased connectivity involving the hippocampus, insula, and cerebellum.
  • These connectivity differences persisted after controlling for anxiety and depression.
  • The machine learning model achieved high accuracy (78.4% sensitivity, 76.9% specificity, AUC=0.88) in classifying PPPD patients.

Conclusions:

  • PPPD is associated with altered functional connectivity in brain networks involved in multisensory vestibular processing, spatial cognition, and emotional regulation.
  • rsfMRI connectivity patterns show promise as an objective imaging biomarker for PPPD.