S31 Structurally informed analyses of functional connectivity in stroke

Abstract

Objectives Stroke is the leading cause of disability in industrialized countries, has a big impact on quality of life, and is of high socioeconomic relevance. Despite great advances of acute therapy – like thrombolysis and mechanical thrombectomy – approximately 50% of stroke survivors suffer from permanent neurological deficits, mostly because of structural and functional neural network failure. Methods Review of own and published data on structural and functional connectivity in human stroke. Diffusion tensor imaging, MR tractography, functional and effective connectivity measures on MRI (BOLD), EEG and other electrophysiological techniques. Results Integrating structural, typically MRI-derived connectomic information into analysis of functional brain connectivity, i.e., measured by EEG, MEG or magnetic stimulation, enhances our understanding of interregional interaction after stroke (e.g., Finger et al. PLoS Comput Biol. 2016 Aug 9;12(8):e1005025; Schulz et al. Stroke. 2016 Feb;47(2):482–9). The impact of corticospinal tract damage is substantial. Enhanced connectivity between parietal and primary motor cortex appears to be related to better functional outcome. Discussion Structurally informed analyses of functional connectivity help identifying key hubs and edges that cause symptoms and subserve recovery after stroke. Limitations are discussed. Conclusions Combining MRI-based connectomics and electrophysiological measures advances our understanding of damaged neural networks and recovery in humans. Significance Whenever possible, a multimodal, combined structural and electrophysiological approach should be chosen when investigating neural networks in patients.