readme update

examples/vspatch/README.md

@@ -4,5 +4,5 @@ This is a test for representing graded numerical values in terms of the overall
 
 The model has opponent D1 vs D2 `VSPatch` layers that are trained to predict the amount of reward for N different "conditions", with T theta trial steps leading up to the reward.  It needs to _not_ respond for the first T-1 time steps, and then accurately predict the graded reward value at T. The opponent D1 vs. D2 dynamic within the VSPatch layer is critical for enabling this dichotomous behavior to be learned.
 
-The `CondStats` plot shows all the stats for each condition over learning, where `NR` = the non-reward trial activity, and otherwise it shows the final reward trial values.  These conditions are also plotted in the `TrainEpoch` plot.
+The `Train/Stats` plot shows all the stats for each condition after each epoch of learning, where `NR` = the non-reward trial activity, and otherwise it shows the final reward trial values.  These conditions are also plotted in the `TrainEpoch` plot, after you hit Init, after an initial epoch or more of learning.