Linking brain networks to cognition with magnetoencephalography in paediatric autoimmune encephalitis

Charly Billaud, Amanda Wood, Daniel Griffiths-King, Klaus Kessler, Evangeline Wassmer, Elaine Foley, Sukhvir Wright*

*Corresponding author for this work

Research output: Preprint or Working paperPreprint

Abstract

Paediatric autoimmune encephalitis (e.g., acute disseminated encephalomyelitis, N-methyl-D-aspartate receptor antibody encephalitis) is an inflammatory brain disease that causes cognitive deficits, psychiatric symptoms, seizures, MRI, and EEG abnormalities. Patients can continue to experience residual cognitive difficulties months to years after the acute illness. Magnetoencephalography (MEG) can examine neural changes in the absence of frank structural abnormalities and may help identify factors predicting children at risk of long-term cognitive deficits. We predicted that theta and delta brain functional connectivity networks would be associated with processing speed and working memory in children with autoimmune encephalitis.

Participants were children diagnosed with autoimmune encephalitis at least 18 months before testing and typically developing children. All completed MEG recording (Elekta Neuromag Triux) at rest, eyes open with a fixation cross during six minutes; T1 MRI scans; and cognitive evaluation using the primary subtests of the Weschler Intelligence Scale for Children, fifth edition. Brain connectivity, specifically in delta and theta brain activity, was estimated with amplitude envelope correlation, and network efficiency was measured using graph measures (global efficiency, local efficiency, modularity). The measures were compared across the two groups with permutation correction for multiple thresholds. Finally, statistical associations with processing speed and working memory scores were tested in the autoimmune encephalitis group.

Age and sex-matched cohorts of 12 children with AE (11.2±3.5y, IQR 9y; 5M:7F) and 12 typically developing controls (10.6±3.2y, IQR 7y; 8M:4F) participated in this study. On average, children with autoimmune encephalitis did not differ from controls in working memory (t(21)= 1.449; p = .162; d = 0.605) but had a significantly lower processing speed (t(21) = 2.463; p = .023; Cohen’s d = 1.028). The groups did not differ in theta network topology measures but the autoimmune encephalitis group had a significantly lower delta local efficiency across all thresholds tested (d = −1.60 at network threshold 14%). Theta modularity was associated with lower working memory (β = -.781; t(8) = −2.588, p = .032) but this effect did not survive correction for multiple comparisons (p(corr) = .224). No other graph measure was significantly associated with psychometric scores in the autoimmune encephalitis group.

MEG was able to capture network alterations in paediatric autoimmune encephalitis patients, specifically in the topological organisation of delta brain activity. This preliminary study demonstrates that MEG is an appropriate tool for assessing children with autoimmune encephalitis; future studies should focus on confirming which functional networks can predict cognitive performance.
Original languageEnglish
DOIs
Publication statusPublished - 5 Apr 2024

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