Question: I have two dropdowns DD1 & DD2 , I want that if user selects option HELLO (value="100") in DD1 and presses a key , then the same value option in DD2 is removed, DD1 will have that option,
it would only be removed from DD2

```
var selectedItems = $('#DD1').val();

 for ( var i = 0 ; i < selectedItems.length; i++) 
        {
           $("#DD2 option[value='"+selectedItems[i]+']"').remove();
        }                                                                       

```

Answer: 
From what I understand of HTM's, the structure of layers and columns mimics the structure of the neocortex. See appendix B here: <http://www.numenta.com/htm-overview/education/HTM_CorticalLearningAlgorithms.pdf>

So the short answer would be that since the brain can understand non-linear phenomenon with this structure, so can an HTM.

Initial, instantaneous sensory input is indeed mapped to 2D regions within an HTM. This does not limit HTM's to dealing with 2D representations any more than a one dimensional string of bits is limited to representing only one dimensional things. It's just a way of encoding stuff so that sparse distributed representations can be formed and their efficiencies can be taken advantage of.

To answer your question about Project Gutenberg, I don't think an HTM will really understand language without first understanding the physical world on which language is based and creates symbols for. That said, this is a very interesting sequence for an HTM, since predictions are only made in one direction, and in a way the understanding of what's happening to the fruit goes backwards. i.e. I see the pattern 'flies like a' and assume the phrase applies to the fruit the same way it did to time. HTM's do group subsequent input (words in this case) together at higher levels, so if you used Fuzzy Grouping (perhaps) as Davide Maltoni has shown to be effective, the two halves of the sentence could be grouped together into the same high level representation and feedback could be sent down linking the two specific sentences. Numenta, to my knowledge has not done too much with feedback messages yet, but it's definitely part of the theory.
Yes, It can do non-linear. Basically it is multilayer. And all multilayer neural networks can infer non linear relationships. And I think the neighborship is calculated locally. If it is calcualted locally then globally it can be piece wise non linear for example look at Local Linear Embedding.