Kullback–Leibler Divergence of Sleep-Wake Patterns Related with Depressive Severity in Patients with Epilepsy

Author:

Liu Mingsu1,Jiang Jian2,Feng Yu1,Cai Yang1,Ding Jing13,Wang Xin14

Affiliation:

1. Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai 200032, China

2. Institute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200050, China

3. CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai 200031, China

4. Department of the State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai 200032, China

Abstract

(1) Objective: Whether abnormal sleep-wake rhythms were associated with depressive symptoms in patents with epilepsy had remained unclear. Our study aimed to establish relative entropy for the assessment of sleep-wake patterns and to explore the relationship between this index and the severity of depressive symptoms in patients with epilepsy. (2) Methods: We recorded long-term scalp electroencephalograms (EEGs) and Hamilton Depression Rating Scale-17 (HAMD-17) questionnaire scores from 64 patients with epilepsy. Patients with HAMD-17 scores of 0–7 points were defined as the non-depressive group, while patients with scores of 8 or higher were defined as the depression group. Sleep stages were firstly classified based on EEG data. We then quantified sleep-wake rhythm variations in brain activity using the Kullback–Leibler divergence (KLD) of daytime wakefulness and nighttime sleep. The KLD at different frequency bands in each brain region was analyzed between the depression and non-depression groups. (3) Results: Of the 64 patients with epilepsy included in our study, 32 had depressive symptoms. It was found that patients with depression had significantly decreased KLD for high-frequency oscillations in most brain areas, especially the frontal lobe. A detailed analysis was conducted in the right frontal region (F4) because of the significant difference in the high-frequency band. We found that the KLDs at the gamma bands were significantly decreased in the depression groups compared to the non-depression group (KLDD = 0.35 ± 0.05, KLDND = 0.57 ± 0.05, p = 0.009). A negative correlation was displayed between the KLD of gamma band oscillation and HAMD-17 score (r = −0.29, p = 0.02). (4) Conclusions: Sleep-wake rhythms can be assessed using the KLD index calculated from long-term scalp EEGs. Moreover, the KLD of high-frequency bands had a negative correlation with HAMD-17 scores in patients with epilepsy, which indicates a close relationship between abnormal sleep-wake patterns and depressive symptoms in patients with epilepsy.

Funder

Clinical Research Plan of SHDC

Lingang Laboratory

Publisher

MDPI AG

Subject

General Neuroscience

Reference44 articles.

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2. Rhythms of life: Circadian disruption and brain disorders across the lifespan. Nature reviews;Logan;Neuroscience,2019

3. The relationship between sleep and epilepsy: Evidence from clinical trials and animal models;Matos;J. Neurol. Sci.,2010

4. Sleep architecture in patients with Juvenile Myoclonic Epilepsy;Mekky;Sleep Med.,2017

5. Individual brain metabolic connectome indicator based on Kullback-Leibler Divergence Similarity Estimation predicts progression from mild cognitive impairment to Alzheimer’s dementia;Wang;Eur. J. Nucl. Med. Mol. Imaging,2020

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