Fig. 6: Illustration and results of RCA for source localised MEG signals.

a RCA analysis applied to ROI clusters. Feedforward effects in the source-level RCA is formalised in the same way as in the sensor-level analysis, and is based on the difference of two partial correlations. (i) The first measures the relationship between the target neural RDM and the semantic feature RDM, while controlling for other model RDMs and past RDMs from control regions. (ii) The second correlation measures the relationship between the target RDM and the semantic feature RDM, while controlling for the same other factors in addition to also removing the effects of past similarities in the source region. (iii) Example time-courses of these two partial correlations. A reduced correlation in the second partial correlation indicates the contribution of the source region to the target regions RSA effect. (iv) Subtracting the second correlation from the first is the RCA measure. b Effects between the pVTC and right ATL. Solid line shows feedforward effects (pvTC -> rATL) and line with circles shows feedback effects (rATL -> pVTC). c Feedforward (pVTC -> PFC/ATL) and Feedback (PFC/ATL-> pVTC) RCA effects between pVTC and the left PFC/ATL. d Feedforward (rATL -> PFC/ATL) and Feedback (PFC/ATL-> rATL) RCA effects between right ATL and left PFC/ATL. Shaded areas show standard error of the mean. Solid bars show time periods of significant effects.