  In this mini-review, dedicated to the Jubilee of Professor Tadeusz Marek, we
highlight in a popular way the power of so-called free random variables
(hereafter FRV) calculus, viewed as a potential probability calculus for the
XXI century, in applications to the broad area of cognitive sciences. We
provide three examples: (i) inference of noisy signals from multivariate
correlation data from the brain; (ii) distinguished role of non-normality in
real neuronal models; (iii) applications to the field of deep learning in
artificial neural networks.
