A Comparative Investigation of Functional Connectivity Utilizing Electroencephalography in Insomnia Patients With and Without Restless Leg Syndrome
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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.
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.
참고문헌 (32)
- Trenkwalder C, "Restless legs syndrome : pathophysiology, clinical presentation and management", Nat Rev Neurol, 6, pp.337~346 (2010)
- Guo S, "Restless legs syndrome : from pathophysiology to clinical diagnosis and management", Front Aging Neurosci, 9, pp.171~ (2017)
- Lee BY, "Involvement of the central somatosensory system in restless legs syndrome : a neuroimaging study", Neurology, 90, pp.e1834~e1841 (2018)
- Rizzo G, "Brain imaging and networks in restless legs syndrome", Sleep Med, 31, pp.39~48 (2017)
- Park KM, "Alterations of functional connectivity in patients with restless legs syndrome", J Clin Neurol, 18, pp.290~297 (2022)
- Kocar TD, "Differential functional connectivity in thalamic and dopaminergic pathways in restless legs syndrome : a meta-analysis", Ther Adv Neurol Disord, 13, pp.1756286420941670~ (2020)
- Li Z, "Disrupted brain network topology in chronic insomnia disorder : a resting-state fMRI study", Neuroimage Clin, 18, pp.178~185 (2018)
- Wang L, "Altered default mode and sensorimotor network connectivity with striatal subregions in primary insomnia : a resting-state multi-band fMRI study", Front Neurosci, 12, pp.917~ (2018)
- Heo IS, "Electrophysiological changes related to childhood trauma in patients with major depressive disorder : an event-related potential study", Clin Psychopharmacol Neurosci, 20, pp.167~179 (2022)
- Lee I, "Comparison of quantitative electroencephalography between tic disorder and attention-deficit", hyperactivity disorder in children, 2021, pp.19, 739~750
- Saletu M, "EEG mapping in patients with restless legs syndrome as compared with normal controls", Psychiatry Res, 115, pp.49~61 (2002)
- Allen RP, "Restless legs syndrome : diagnostic criteria, special considerations, and epidemiology : a report from the restless legs syndrome diagnosis and epidemiology workshop at the National Institutes of Health", Sleep Med, 4, pp.101~119 (2003)
- Dale AM, "Dynamic statistical parametric mapping : combining fMRI and MEG for high-resolution imaging of cortical activity", Neuron, 26, pp.55~67 (2000)
- Tass P, "Detection of n : m phase locking from noisy data : application to magnetoencephalography", Phys Rev Lett, 81, pp.3291~3294 (1998)
- Bruña R, "Phase locking value revisited : teaching new tricks to an old dog", J Neural Eng, 15, pp.056011~ (2018)
- Sevim S, "Correlation of anxiety and depression symptoms in patients with restless legs syndrome : a population based survey", J Neurol Neurosurg Psychiatry, 75, pp.226~230 (2004)
- Becker PM, "The biopsychosocial effects of restless legs syndrome(RLS)", Neuropsychiatr Dis Treat, 2, pp.505~512 (2006)
- Walters AS, "Ropinirole is effective in the treatment of restless legs syndrome. TREAT RLS 2 : a 12-week, double-blind, randomized, parallel-group, placebo-controlled study", Mov Disord, 19, pp.1414~1423 (2004)
- Auvinen P, "A longitudinal study of restless legs symptoms among patients with depression", Nord J Psychiatry, 76, pp.584~590 (2022)
- Unrath A, "Cortical grey matter alterations in idiopathic restless legs syndrome : an optimized voxel-based morphometry study", Mov Disord, 22, pp.1751~1756 (2007)
- Li Z, "Reduced regional activity and functional connectivity within sensorimotor network in Parkinson’s patients with restless legs syndrome", Mol Pain, 15, pp.1744806919882272~ (2019)
- Wik G, "Retrosplenial cortical activation in the fibromyalgia syndrome", Neuroreport, 14, pp.619~621 (2003)
- Ku J, "Diurnal variation of default mode network in patients with restless legs syndrome", Sleep Med, 41, pp.1~8 (2018)
- Tuovinen N, "Functional connectivity and topology in patients with restless legs syndrome : a case-control resting-state functional magnetic resonance imaging study", Eur J Neurol, 28, pp.448~458 (2021)
- Colzato LS, "Cognitive profile in restless legs syndrome : a signal-to-noise ratio account", Curr Res Neurobiol, 2, pp.100021~ (2021)
- Choi JW, "Reduced neural synchrony in patients with restless legs syndrome during a visual oddball task", PLoS One, 7, pp.e42312~ (2012)
- Jung KY, "Cognition in restless legs syndrome", J Sleep Med, 12, pp.1~6 (2015)
- Ku J, "Default mode network disturbances in restless legs syndrome", Willis-Ekbom disease, 2016, pp.23, 6~11
- Ji B, "Functional connectivity density in the sensorimotor area is associated with sleep latency in patients with primary insomnia", Neuropsychiatr Dis Treat, 18, pp.1~10 (2022)
- Lee YS, "Resting-state connectivity and the effects of treatment in restless legs syndrome", Sleep Med, 67, pp.33~38 (2020)
- Wang L, "Altered cortical gray matter volume and functional connectivity after transcutaneous spinal cord direct current stimulation in idiopathic restless legs syndrome", Sleep Med, 74, pp.254~261 (2020)
- Liu C, "Mapping intrinsic functional brain changes and repetitive transcranial magnetic stimulation neuromodulation in idiopathic restless legs syndrome : A resting-state functional magnetic resonance imaging study", Sleep Med, 16, pp.785~791 (2015)