It is exactly the same idea, but instead of a fully connected on the whole input, it is several times the same small fully-connected on different parts of the input.
For instance, if your channels are 4 consecutive black/white images with a moving ball rolling on the x axis, you will probably learn a 3D convolution (time * x * y) that will look like an edge detector projected on (x,y), and something close to an identity projected on (time*x).