Abstract: “Cognitive training” (CT) is a label used to describe paper-and-pen or computerized exercises designed to engage a desired set of mental skills for the purpose of enhancing neurocognitive functioning. Although the literature on the topic is considerably rich (on PubMed, for the sole 2018, the use of “cognitive training” as title keyword returns 123 results), very few studies pose the fundamental question: “How does CT work?”, or, more precisely, “Based on which computational mechanisms would engaging in CT result into meaningful changes in outcome measures?”.  The overwhelming majority of the studies focus on treatment efficacy by modelling outcome measure(s) as a function of CT (e.g., an active CT condition versus an active control condition), but do not describe in detail the exact mechanistic reason why CT should have an effect in the first place (De Marco et al., 2014). Biological frameworks have been proposed [i.e., the hypothetical role played by neurotrophic factors, synaptic connections and neuroplasticity (Castells-Sánchez et al., 2019)] but these have been introduced as an a posteriori interpretation, not as a driving principle for the design of the exercises.