Fig. 4: Illustration and results of the MEG sensor-level Representational connectivity analysis (RCA).

a Illustration of the calculation of feedforward information flow (feedforward connectivity at each timepoint) between anterior and posterior regions at the MEG sensor-level, as introduced by Karimi-Rouzbahani et al.³². i) RDMs are created from anterior and posterior sensors. Feedforward flow at each timepoint is formalised as the contribution of the earlier posterior RDM (t-30m) to the current model-anterior RDM correlation (t). This is calculated as the difference between the anterior-model RDM correlation and the anterior-model RDM correlation where the posterior RDM is partialled out. Feedback information flow is formalised as the contribution of the earlier anterior RDM (t-30) to the current model-posterior RDM correlation (t). ii) In the partial RCA, the contribution of other model RDMs is also partialled out in the calculation of both RSA timecourses. b Feedforward RCA effects for each model RDM. c Feedback effects of the model RDMs. Shaded areas show standard error of the mean. Solid bars show time periods of significant effects. d Swarmplots showing the differences in peak RCA latency between model RDMs. Distributions display resamples of the data (31,465 resamples) which were used to generate 95% CIs for the differences in peak latencies.