  Simple memorizing tasks have been chosen such as a binary code on a matrix.
After the establishment of an appropriate protocol, the codified matrices were
individually presented to 150 university students who had to memorize them. A
computer simulation for a similar task is available which uses a perceptron on
which an algorithm was implemented allowing for some degree of globality
(technically referred to as entropic nonextensivity within a current
generalization of the usual, Boltzmann-Gibbs, statistical mechanics). Our main
observation is that, for the very specific learning task on which we focus
here, humans perform similarly to slightly nonextensive perceptrons.
