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Altered effective connectivity of the default mode network in juvenile myoclonic epilepsy

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Abstract

Juvenile myoclonic epilepsy (JME) is associated with brain dysconnectivity in the default mode network (DMN). Most previous studies of patients with JME have assessed static functional connectivity in terms of the temporal correlation of signal intensity among different brain regions. However, more recent studies have shown that the directionality of brain information flow has a more significant regional impact on patients’ brains than previously assumed in the present study. Here, we introduced an empirical approach incorporating independent component analysis (ICA) and spectral dynamic causal modeling (spDCM) analysis to study the variation in effective connectivity in DMN in JME patients. We began by collecting resting-state functional magnetic resonance imaging (rs-fMRI) data from 37 patients and 37 matched controls. Then, we selected 8 key nodes within the DMN using ICA; finally, the key nodes were analyzed for effective connectivity using spDCM to explore the information flow and detect patient abnormalities. This study found that compared with normal subjects, patients with JME showed significant changes in the effective connectivity among the precuneus, hippocampus, and lingual gyrus (p < 0.05 with false discovery rate (FDR) correction) with most of the effective connections being strengthened. In addition, previous studies have found that the self-connection of normal subjects’ nodes showed strong inhibition, but the self-connection inhibition of the anterior cingulate cortex and lingual gyrus of the patient was decreased in this experiment (p < 0.05 with FDR correction); as the activity in these areas decreased, the nodes connected to them all appeared abnormal. We believe that the changes in the effective connectivity of nodes within the DMN are accompanied by changes in information transmission that lead to changes in brain function and impaired cognitive and executive function in patients with JME. Overall, our findings extended the dysconnectivity hypothesis in JME from static to dynamic causal and demonstrated that aberrant effective connectivity may underlie abnormal brain function in JME patients at early phase of illness, contributing to the understanding of the pathogenesis of JME.

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Data availability

The datasets analyzed in the current study are available from the corresponding author upon reasonable request.

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Acknowledgements

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Funding

This work was supported by a grant from the National Natural Science Foundation of China [Grant numbers 61966023 and 82160326].

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Authors and Affiliations

  1. School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China

    Ming Ke & Feng Wang

  2. Department of Nuclear Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, 730030, China

    Guangyao Liu

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  1. Ming Ke
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  2. Feng Wang
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  3. Guangyao Liu
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Contributions

MK, FW, and GY designed the experiment and revised the manuscript. MK and FW wrote the manuscript. GY recorded and collected the data. FW performed the data analysis. All authors contributed to this article and approved the version submitted.

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Correspondence to Ming Ke or Guangyao Liu.

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This study was approved by the Medical Research Ethics Committee of the Lanzhou University Second Hospital (No. 2019A-102). All individuals understood the purpose and latent risks and signed informed consent.

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Ke, M., Wang, F. & Liu, G. Altered effective connectivity of the default mode network in juvenile myoclonic epilepsy. Cogn Neurodyn (2023). https://doi.org/10.1007/s11571-023-09994-4

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