Helmholtz Gemeinschaft

Search
Browse
Statistics
Feeds

State-dependent signatures of anti-N-methyl-d-aspartate receptor encephalitis

[img]
Preview
PDF (Original Article) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
4MB
[img] Other (Supplementary Material)
7MB

Item Type:Article
Title:State-dependent signatures of anti-N-methyl-d-aspartate receptor encephalitis
Creators Name:von Schwanenflug, N. and Krohn, S. and Heine, J. and Paul, F. and Prüss, H. and Finke, C.
Abstract:Traditional static functional connectivity analyses have shown distinct functional network alterations in patients with anti-N-methyl-d-aspartate receptor encephalitis. Here, we use a dynamic functional connectivity approach that increases the temporal resolution of connectivity analyses from minutes to seconds. We hereby explore the spatiotemporal variability of large-scale brain network activity in anti-N-methyl-d-aspartate receptor encephalitis and assess the discriminatory power of functional brain states in a supervised classification approach. We included resting-state functional magnetic resonance imaging data from 57 patients and 61 controls to extract four discrete connectivity states and assess state-wise group differences in functional connectivity, dwell time, transition frequency, fraction time and occurrence rate. Additionally, for each state, logistic regression models with embedded feature selection were trained to predict group status in a leave-one-out cross-validation scheme. Compared to controls, patients exhibited diverging dynamic functional connectivity patterns in three out of four states mainly encompassing the default-mode network and frontal areas. This was accompanied by a characteristic shift in the dwell time pattern and higher volatility of state transitions in patients. Moreover, dynamic functional connectivity measures were associated with disease severity and positive and negative schizophrenia-like symptoms. Predictive power was highest in dynamic functional connectivity models and outperformed static analyses, reaching up to 78.6% classification accuracy. By applying time-resolved analyses, we disentangle state-specific functional connectivity impairments and characteristic changes in temporal dynamics not detected in static analyses, offering new perspectives on the functional reorganization underlying anti-N-methyl-d-aspartate receptor encephalitis. Finally, the correlation of dynamic functional connectivity measures with disease symptoms and severity demonstrates a clinical relevance of spatiotemporal connectivity dynamics in anti-N-methyl-d-aspartate receptor encephalitis.
Keywords:Autoimmune Encephalitis, NMDA Receptor, Dynamic Functional Connectivity, Supervised Classification
Source:Brain Communications
ISSN:2632-1297
Publisher:Oxford University Press
Volume:4
Number:1
Page Range:fcab298
Date:1 February 2022
Official Publication:https://doi.org/10.1093/braincomms/fcab298
PubMed:View item in PubMed
Related to:
URLURL Type
https://edoc.mdc-berlin.de/19053/Preprint version

Repository Staff Only: item control page

Downloads

Downloads per month over past year

Open Access
MDC Library