Spectral dynamic causal modeling identifies distinct effective connectivity patterns in anti-LGI1 encephalitis, suggesting correlations with cognitive function.
Motivation: Causal changes in effective connectivity within brain networks of patients with leucine-rich glioma inactivated 1 (LGI1) antibody encephalitis are poorly understood, limiting targeted interventions for symptom management. Goal(s): To identify effective connectivity patterns among key brain regions in patients with anti-LGI1 and examine their correlation with symptom severity and cognitive function. Approach: A spectral dynamic causal model analyzed connectivity in fMRI data of patients with anti-LGI1 encephalitis, comparing it with healthy controls. Results: Our findings revealed distinct connectivity patterns in patients with anti-LGI1, with variations correlating to symptom severity and cognitive deficits, indicating specific causal relationships in brain networks. Impact: This study enhances understanding of brain connectivity in anti-LGI1 encephalitis, potentially leading to new diagnostic biomarkers and targeted therapies. Improved insights into causal relationships may substantially enhance patient management and treatment outcomes in autoimmune encephalitis.
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Liu et al. (2025) studied this question.
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