Title: How we discovered Deep Neural Networks at Middlesex University in 2007.

Abstract

We represent neural networks by directed graphs and consider the
 problem of maximal connectivity with constraints.  This problem is
 motivated by some conflicting objectives in the design of biological
 neural networks.  One of the solutions of this optimisation problem
 of neural network with constrains was presented at IJCNN 2007 and
 resembles what is now called a concolutional deep-learning neural
 networks.  Inequalities and equations derived are tested on data and
 numerical estimates for parameters of a human brain.  Results support
 an intuition that human brain is maximally connected subject to
 constraints on in- and out-degrees.