ID 393 – Effective connectivity model for multichannel ERPs in visual oddball paradigm

Abstract

Objectives Dynamic Causal Modeling (DCM) was used to find a plausible model for the evoked brain responses (ERPs) to visual stimuli recorded in an oddball task. We aimed at the evaluation of the model reproducibility over a set of individual recordings and on the role of backward connections in the generation of ERP components. Methods 128-channel EEG was recorded in 22 healthy volunteers, the individual averaged ERPs were used for modeling. DCM is designed to assess the effective connectivity, i.e. the influence one neuronal system exerts over another. Forward cortico-cortical connections are the connections from the lower to higher hierarchical layers, and backward – from higher to lower layers. Results The best (and reproducible) model allowed the changes in strength of forward connections. The early components of ERPs can be explained by the forward connections only, but after 200 ms both forward and backward connections are required, assuming the involvement of brain endogenous activity. Conclusions Our model demonstrates the emergence of backward connections for the latencies longer than 200 ms. The forward connection modulation is sufficient to model the earlier visual ERP components for standard/deviant stimuli. These results are compatible with the DCM for auditory oddball experiment by other authors.