You have one p-values for each ROI timecourse (for the largest cluster) indicating whether your conditions are exchangeable. If you want to correct for the 4 ROIs you could use any adequate multiple comparison correction, from classical Bonferroni (which might be too conservative as the tests are likely not completly independent) to Benjamini-Hochberg style FDR correction (but applied to the cluster permutation test p-values).
This leaves us with the question which p-values count, one per ROI (the largest cluster, i.e. smallest p-value) or the p-values for all supra cluster-threshold clusters. I would think the former is more appropriate, as you already corrected for the multiple clusters.
That is, for the Bonferroni correction you would multiply your p-values by 4, (or identically, divide your critical alpha by 4).
This solution is incomplete, as I do not know how to get corrected p-values for the second largest cluster with FDR or Holm-Bonferroni.