number of neurons for mnist dataset using mlp?
If you train long enough and have "too many" hidden layer units, then you will eventually have over-training. Usually, the goal is to find the smallest number of hidden units that can do reasonably well, as that will generally give you good generalization. In fact, there is the "bottle neck theory" that attempts to show this effect (https://openreview.net/forum?id=ry_WPG-A-)

For more on comparisons between flat hidden layer networks versus convolutional networks, see:

http://conx.readthedocs.io/en/latest/MNIST.html#A-multi-layer-perceptron-network-for-MNIST-classification