Evidence map›Paper›PMID 40670863›Full record

ArticleBrain imaging and behavior2025

Investigation of the effective connectivity between the anti-NMDAR encephalitis default mode network and the medial temporal lobe network using spectral dynamic causal modelling.

Zijun Liu, Muzi Li, Jingwen Li, Guang Xu, Junzhang Tian, Xiaofen Ma

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Article in Brain imaging and behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Zijun Liu *Guangdong Medical University, Zhanjiang, P. R. China.
Muzi Li *Department of Nuclear Medicine, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, No.466 Road XinGang, Guangzhou, 510317, P. R. China.
Jingwen LiDepartment of Nuclear Medicine, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, No.466 Road XinGang, Guangzhou, 510317, P. R. China.
Guang XuDepartment of Neurology, The Affiliated Guangdong Second Provincial, General Hospital of Jinan University, Guangzhou, P. R. China.
Junzhang TianDepartment of Nuclear Medicine, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, No.466 Road XinGang, Guangzhou, 510317, P. R. China. tianjunzhang2015@163.com.
Xiaofen MaGuangdong Medical University, Zhanjiang, P. R. China. xiaofenma12@163.com.

Funding

the National Science Foundation of China 82472035the Science and Technology Program of Guangzhou 202201020385
6 · The paper itself

Abstract

backgroundResearch has indicated that anti-N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis involves global network dysfunction, linking memory deficits to connectivity in the hippocampus, default mode network (DMN), and medial temporal lobe network (MTL). Most relevant cognitive studies have focused on functional connectivity (FC) rather than effective connectivity (EC), meaning that the directed interactions and causal relationships between the DMN and MTL remain unexplored.

methodsHerein, we collected resting-state functional MRI (fMRI) data from 23 patients with anti-NMDAR encephalitis (mean age 30.04 ± 12.67 years) and 23 matched controls (mean age 28.87 ± 9.36 years). Spectral dynamic causal modelling (spDCM) was applied to assess the effective connectivity among the 12 predefined regions of interest in the DMN and MTL.

resultsEffective connectivity (EC) within and between the DMN and MTL networks significantly differed in the NMDAR-resistant encephalitis group compared to controls; the positive EC within the DMN and from the MTL to the DMN was enhanced, while the negative EC from the DMN to the MTL increased, and the positive EC within the MTL decreased. The mean DMN connectivity values in the anti-NMDAR group were negatively correlated with California Verbal Learning Test (CVLT) and Modified Mental State Examination (MMSE) scores, an effect which remained significant after adjusting for age, sex, and body mass index.

conclusionThis study identified differences in the connectivity between the DMN and MTL networks in patients with post-acute anti-NMDAR encephalitis, suggesting a possible disconnection. The parahippocampal gyrus (PHG) mediates connections between the hippocampus and the posterior cingulate cortex (PCC). Structural or functional loss of the PHG may affect the integration between the MTL memory system and DMN nodes, correlating with cognitive deficits. This study provides crucial results to improve our understanding of the directed integration between the DMN and MTL networks, providing new evidence.

Indexed as

Anti-N-Methyl-D-Aspartate Receptor EncephalitisDefault Mode NetworkNerve NetTemporal LobeAdultBrain MappingFemaleHippocampusHumansMagnetic Resonance ImagingMaleNeural PathwaysYoung AdultAnti-NMDAR encephalitisCognitionDefault mode networkEffective connectivityMedial Temporal lobe netwark

Identifiers

PMID40670863

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.