Characterising stationary and dynamic effective connectivity changes in the motor network during and after tDCS
Name:
Publisher version
View Source
Access full-text PDFOpen Access
View Source
Check access options
Check access options
Affiliation
University of Birmingham; University Hospitals Birmingham NHS Foundation TrustPublication date
2023-02-06
Metadata
Show full item recordAbstract
The exact mechanisms behind the effects of transcranial direct current stimulation (tDCS) at a network level are still poorly understood, with most studies to date focusing on local (cortical) effects and changes in motor-evoked potentials or BOLD signal. Here, we explored stationary and dynamic effective connectivity across the motor network at rest in two experiments where we applied tDCS over the primary motor cortex (M1-tDCS) or the cerebellum (cb-tDCS) respectively. Two cohorts of healthy volunteers (n = 21 and n = 22) received anodal, cathodal, and sham tDCS sessions (counterbalanced) during 20 min of resting-state functional magnetic resonance imaging (fMRI). We used spectral Dynamic Causal Modelling (DCM) and hierarchical Parametrical Empirical Bayes (PEB) to analyze data after (compared to a pre-tDCS baseline) and during stimulation. We also implemented a novel dynamic (sliding windows) DCM/PEB approach to model the nature of network reorganisation across time. In both experiments we found widespread effects of tDCS that extended beyond the targeted area and modulated effective connectivity between cortex, thalamus, and cerebellum. These changes were characterised by unique nonlinear temporal fingerprints across connections and polarities. Our results support growing research challenging the classic notion of anodal and cathodal tDCS as excitatory and inhibitory respectively, as well as the idea of a cumulative effect of tDCS over time. Instead, they described a rich set of changes with specific spatial and temporal patterns. Our work provides a starting point for advancing our understanding of network-level tDCS effects and may guide future work to optimise its cognitive and clinical applications.Citation
Calzolari S, Jalali R, Fernández-Espejo D. Characterising stationary and dynamic effective connectivity changes in the motor network during and after tDCS. Neuroimage. 2023 Apr 1;269:119915. doi: 10.1016/j.neuroimage.2023.119915. Epub 2023 Feb 1.Type
ArticleAdditional Links
http://www.sciencedirect.com/science/journal/10538119PMID
36736717Journal
NeuroImagePublisher
Academic Pressae974a485f413a2113503eed53cd6c53
10.1016/j.neuroimage.2023.119915