Without a doubt, the biggest questions about dreaming are all variants on this question: Why do we dream? We began studying dreaming in the early 1990s and, between the two of us, have published over 200 scientific papers on sleep and dreams. Pulling together a variety of compelling neuroscientific ideas and state-of-the-art findings in the fields of sleep and dream research, we propose a new and innovative model of why we dream. We call this model NEXTUP. It proposes that our dreams allow us to explore the brain's neural network connections in order to understand possibilities.

In this paper we study the connection between the structure and properties of the so-called free association network of the English language, and the solution of psycholiguistical Remote Association Tests (RATs). We show that average hardness of individual RATs is largely determined by the relative positions of the test words (stimuli and response) on the free association network. We argue that solution of RATs can be interpreted as a first passage search problem on a free association network and study a variety of different search algorithms. We demonstate that in easy RATs (those solved by more than 64% subjects in 15 seconds) there are strong links directly connecting stimuli and response, and thus an efficient strategy consist in activating these direct links. In turn, the most efficient mechanism of solving medium and hard RATs consists of preferentially following what we call "moderately weak" associations.

To carry out our mathematical study, we have used the standard Decimal Code (R,G,B) to represent the 12 colours of [12], a depiction of which is in Figure 1. The relation between colours and human emotion has been studied for more than a century (e.g., see for instance [1-8]). Even longer ago, colours were commonly associated to emotions in a universal manner that allowed populations to understand quickly the given emotions. Figure 1: A depiction of the 12 colors used in [12]. For example, for centuries in many cultures it has been said that someone "had the blues" [29] or "is feeling In the last decades colours have also been studied in blue" when being down or sad. As explained in [9], the terms of emotional reactions to color hue, saturation, and phrase "feeling blue" comes from deepwater sailing ships: brightness (e.g., [14, 15]). Here, we shall put the two If a ship lost the captain or any of the officers during its approaches together to consider a novel path, where we voyage, then blue flags would be shown, and a blue band let the colour association within our neural network take would be painted along the entire hull when returning to a continuum of colours, hence considering a continuous home port. RGB analysis [30], depicted in Figure 2. Inspired by [10, 11] we consider their data base [12] to analize the correlation between colours and emotions via a deep learning approach. Whilst machine learning techniques have been used before in this direction (e.g.