Source dipole modelling

In order to investigate the spatiotemporal dynamics of SPN priming, a source dipole model was constructed in BESA v. 7.0 (MEGIS GmbH, Munich, Germany) for each experiment. For the greatest accuracy of source localization, it is necessary to utilize data with a large signal-to-noise ratio. To achieve this, difference waves (symmetry–random) for each condition were averaged to produce a single grand-average waveform representing symmetry-specific responses. This was done for each experiment individually.

The protocol for producing an appropriate source dipole model required that equivalent current dipoles (ECDs) were fitted to describe the 3-dimensional source currents in the regions contributing predominantly to the data. Principle component analysis (PCA) was first used to identify an appropriate number of ECDs to fit. Since previous studies have identified bilateral extrastriate cortices as being the primary generators of symmetry specific neural activity [9–11] two ECDs were first inserted in the bilateral extrastriate regions. Following the insertion of these two ECDs, residual variance was used as a tool for indicating the sufficiency of the model. The ECD fitting procedure required waveforms with a large signal-to-noise ratio and intervals with a strong cortical response. Therefore, the weak SPN observed in Experiment 2 and 3 could not be accurately modelled. Since data across experiment 1, 4 and 5 were sufficiently explained by bilateral extrastriate ECDs, no further fitting of ECDs were required.

Classical LORETA analysis recursively applied (CLARA), which is an iterative application of the LORETA algorithm [26] was used to confirm and adjust the locations of the ECDs in the final model. Following the fitting of the ECD locations, the orientation of the ECDs then had to be determined. Since there are differences between individuals regarding gyral anatomy in the brain, ECD orientation was determined on a subject-by-subject basis, but with fixed location between subjects, based on the entire corresponding grand average difference waveform. A 4-shell ellipsoid head volume conductor model was employed using the following conductivities (S/m = Siemens per meter): Brain = .33 S/m; Scalp = 0.33 S/m; Bone = 0.0042 S/m, Cerebrospinal Fluid = 1 S/m. Source waveforms for each experiment and condition were exported and analyzed using repeated-measures ANOVAs.