Why are there Topic Concentration Iterations when you disable fitting topic concentration in fitlda?

When I run fitlda with 'FitTopicConcentration' set to false, I still get `Topic Concentration Interatons'.

For example:

mdl = fitlda(bag,numTopics,'Verbose',1,'InitialTopicConcentration',50,'FitTopicConcentration',false,'LogLikelihoodTolerance',0,'IterationLimit',20);

gets:

Initial topic assignments sampled in 1.44622 seconds.
=====================================================================
| Iteration  |  Time per  |  Relative  |  Training  |     Topic     |
|            | iteration  | change in  | perplexity | concentration |
|            | (seconds)  |   log(L)   |            |   iterations  |
=====================================================================
|          0 |       0.90 |            |  6.715e+02 |             0 |
|          1 |       1.79 | 3.3759e-02 |  5.429e+02 |             0 |
|          2 |       1.70 | 1.2228e-02 |  5.031e+02 |             0 |
|          3 |       1.58 | 2.1513e-03 |  4.965e+02 |             0 |
|          4 |       1.57 | 6.2666e-04 |  4.945e+02 |             0 |
|          5 |       1.55 | 3.3881e-04 |  4.935e+02 |             0 |
|          6 |       1.60 | 2.5182e-04 |  4.927e+02 |             0 |
|          7 |       1.55 | 1.5109e-04 |  4.923e+02 |             0 |
|          8 |       1.62 | 2.2085e-04 |  4.916e+02 |             0 |
|          9 |       1.64 | 2.1745e-04 |  4.909e+02 |             0 |
|         10 |       1.66 | 1.0178e-04 |  4.906e+02 |             0 |
|         11 |       1.86 | 1.1432e-04 |  4.903e+02 |             4 |
|         12 |       1.79 | 6.5833e-04 |  4.883e+02 |             3 |
|         13 |       1.77 | 4.3774e-04 |  4.870e+02 |             3 |
|         14 |       1.70 | 4.8030e-04 |  4.855e+02 |             3 |
|         15 |       1.73 | 4.1302e-04 |  4.843e+02 |             3 |
|         16 |       1.69 | 1.9747e-04 |  4.837e+02 |             3 |
|         17 |       1.73 | 2.5513e-04 |  4.829e+02 |             3 |
|         18 |       1.83 | 2.4952e-04 |  4.822e+02 |             3 |
|         19 |       1.63 | 9.3627e-05 |  4.819e+02 |             2 |
|         20 |       1.66 | 1.0886e-04 |  4.816e+02 |             2 |
=====================================================================

Why is the rightmost column not all zeros? What does "topic concentration iterations" mean?

[Stephen Bruestle]

Note, when I run:

mdl = fitlda(bag,numTopics,'Verbose',1,'InitialTopicConcentration',50,'FitTopicConcentration',true,'LogLikelihoodTolerance',0,'IterationLimit',20);

I get:

Initial topic assignments sampled in 1.31452 seconds.
=====================================================================================
| Iteration  |  Time per  |  Relative  |  Training  |     Topic     |     Topic     |
|            | iteration  | change in  | perplexity | concentration | concentration |
|            | (seconds)  |   log(L)   |            |               |   iterations  |
=====================================================================================
|          0 |       0.59 |            |  6.715e+02 |        50.000 |             0 |
|          1 |       1.59 | 3.2014e-02 |  5.487e+02 |        50.000 |             0 |
|          2 |       1.57 | 1.1809e-02 |  5.098e+02 |        50.000 |             0 |
|          3 |       1.57 | 2.9063e-03 |  5.006e+02 |        50.000 |             0 |
|          4 |       1.68 | 7.4965e-04 |  4.983e+02 |        50.000 |             0 |
|          5 |       1.55 | 4.2984e-04 |  4.970e+02 |        50.000 |             0 |
|          6 |       1.61 | 2.2000e-04 |  4.963e+02 |        50.000 |             0 |
|          7 |       1.57 | 1.3672e-04 |  4.959e+02 |        50.000 |             0 |
|          8 |       1.55 | 3.0094e-04 |  4.950e+02 |        50.000 |             0 |
|          9 |       1.47 | 1.7135e-04 |  4.944e+02 |        50.000 |             0 |
|         10 |       1.53 | 1.9109e-04 |  4.939e+02 |        50.000 |             0 |
|         11 |       3.51 | 5.6307e-05 |  4.937e+02 |         8.503 |            47 |
|         12 |       2.40 | 4.8823e-02 |  3.699e+02 |         6.363 |            22 |
|         13 |       2.05 | 7.0746e-03 |  3.548e+02 |         6.023 |            13 |
|         14 |       2.01 | 1.7874e-03 |  3.511e+02 |         5.897 |             9 |
|         15 |       2.43 | 1.2725e-03 |  3.485e+02 |         5.775 |             9 |
|         16 |       1.89 | 1.2613e-03 |  3.460e+02 |         5.625 |            10 |
|         17 |       1.88 | 1.1882e-03 |  3.436e+02 |         5.512 |             9 |
|         18 |       1.90 | 1.2557e-03 |  3.411e+02 |         5.387 |             9 |
|         19 |       1.89 | 9.4163e-04 |  3.392e+02 |         5.307 |             7 |
|         20 |       1.94 | 8.2492e-04 |  3.376e+02 |         5.217 |             8 |
=====================================================================================