We present a methodology based on complex networks and maximal information methods that, using data from surveys on urban perception at two spatial levels, reveals the connectivity between human needs. Questions, linked to needs by their satisfiers, are represented by nodes, and correlation between them by edges, weighted by the information strength of every pair of questions. Graph theory is applied to reveal the structure of the network. Our results show that different spatial levels present different and non-trivial patterns of need emergence. A simple numerical model suggests a dependency on the probability distribution of weights. This way of visualising the connectivity of human needs can be used to devise new strategies to cope with the complexity of urban-making processes.