What is the proper definition of "layerDelays" for layer recurrent networks ?

Hi,

I'm having a bit of an issue with the definition of some parameters of the layrecnet function, notably "layerDelays". The documentation of layrecnet refers this parameter as a row vector of increasing 0 or positive delays. However, my understanding of recurrent networks is that each neuron N at state (t) is fed the output the same neuron at state (t-1). Thus, a neuron at state (t+3) for example, has ben fed with its (t+2), which itself has been fed with (t+1) and so on. This creates a recurrence, which can be illustrated as the following:

However, I'm not really sure how the "tap delay" affects this processing. I suppose that, the above scheme, would be the result of using layerDelays=1. And that using a row vector like [1:2] would mean that neurons at state (t) are fed their output at state (t-1) but also (t-2) as two separate inputs, which could bei llustrated like this:

Is my understanding of this parameter correct?

Is there any detailed reference document that gives further informations regarding layer reccurent networks in matlab ?

Thank you in advance.