Clin Psychopharmacol Neurosci.  2024 May;22(2):314-321. 10.9758/cpn.23.1117.

A Comparative Investigation of Functional Connectivity Utilizing Electroencephalography in Insomnia Patients with and without Restless Leg Syndrome

Affiliations
  • 1Department of Psychiatry, Inje University College of Medicine, Goyang, Korea
  • 2Psychiatric Clinic in Your Brain and Mind, Goyang, Korea
  • 3Kim’s Hue Neuropsychiatric Clinic, Bucheon, Korea

Abstract


Objective
The current study aimed to identify distinctive functional brain connectivity characteristics that differentiate patients with restless legs syndrome (RLS) from those with primary insomnia.
Methods
Quantitative electroencephalography (QEEG) was employed to analyze connectivity matrices using the phaselocking value technique. A total of 107 patients with RLS (RLS group) and 17 patients with insomnia without RLS (primary insomnia group) were included in the study. Demographic variables were compared using t tests and chi-square tests, while differences in connectivity were examined through multiple analyses of covariance. Correlation analysis was conducted to explore the relationship between connectivity and the severity of RLS.
Results
The results indicated significant differences in the primary somatosensory cortex (F = 4.377, r = 0.039), primary visual cortex (F = 4.215, r = 0.042), and anterior prefrontal cortex (F = 5.439, r = 0.021) between the RLS and primary insomnia groups. Furthermore, the connectivity of the sensory cortex, including the primary somatosensory cortex (r = −0.247, p = 0.014), sensory association cortex (r = −0.238, p = 0.028), retrosplenial region (r = −0.302, p = 0.002), angular gyrus (r = −0.258, p = 0.008), supramarginal gyrus (r = −0.230, p = 0.020), primary visual cortex (r = −0.275, p = 0.005) and secondary visual cortex (r = −0.226, p = 0.025) exhibited an inverse association with RLS symptom severity.
Conclusion
The prefrontal cortex, primary somatosensory cortex, and visual cortex showed potential as diagnostic biomarkers for distinguishing RLS from primary insomnia. These findings indicate that QEEG-based functional connectivity analysis shows promise as a valuable diagnostic tool for RLS and provides insights into its underlying mechanisms. Further research is needed to explore this aspect further.

Keyword

Restless legs syndrome; EEG; Phase locking value; Brain; Connectivity; Sensory cortex
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