Useful resources on how to use RBM to handle attentional data:

(1) Learning to combine foveal glimpses with a third-order Boltzmann machine. Hugo Larochelle and Geoffrey Hinton,
Advances in Neural Information Processing Systems 23, 2010

this is the first implemented system for combining glimpses that jointly trains a recognition component (the RBM) with an attentional component (the fixation controller).

(2) Learning Where to Attend With Deep Architectures for Image. Misha Denil, Loris Bazzani, Hugo Larochelle and Nando de Freitas, Neural Computation, 24(8): 2151-2184, 2012

(3) Learning attentional policies for object tracking and recognition in video with deep networks. L. Bazzani, N. de Freitas, H. Larochelle, V. Murino, and J-A Ting, In International Conference on Machine Learning (ICML), 2011.

Links:

(1) http://www.lorisbazzani.info/

(2) http://www.dmi.usherb.ca/~larocheh/index_en.html

Several very new works.