degrees of freedom for two-way repeated-measures ANOVA



I had a related topic over on the R forum involving my lmer model, but now I'm more concerned with the degrees of freedom, which I thought was a more general question that would be more appropriate here.

My study had two crossed within-subjects factors. 44 subjects used an interface for 6 rounds. Each round had 3 trials, each with a different memory task condition (3 conditions in random order). So this is a 3x6 design. I've used lmer in R for the model, but I plan to compute the degrees of freedom just as I would for a two-way within-subjects ANOVA.

My lmer model is:
lmer(dist ~ condition*round + (1|id) + (1|condition:id) + (1|round:id),data=data_dist)
So I have the two factors, an error term for the subject, and an error term for the interaction between the subject and each factor. Right now I have the following for degrees of freedom:

condition: 2 (# of memory conditions - 1)
round: 5 (# of rounds - 1)
interaction: 10
subject error: 43 (# of subjects - 1)
error: 628
total: 688 (# of observations - 1)

I think I may need degrees of freedom for the extra terms from the model, but I can't find a single reference explaining how to do this. So my first question is: Do I need more terms for my degrees of freedom and, if so, how do I calculate them?

Also, once I find the degrees of freedom my second question is: Can you tell me which value is normally used for the denominator DoF in the ANOVA? (i.e., what would I use for denominator DoF when looking up the p-value for condition?)