How to build better memory training games

Abstract

Can we create engaging training programs that improve working memory (WM) skills? While there are numerous procedures that attempt to do so, there is a great deal of controversy regarding their efficacy. Nonetheless, recent meta-analytic evidence shows consistent improvements across studies on lab-based tasks generalizing beyond the specific training effects (Au et al., 2014; Karbach and Verhaeghen, 2014), however, there is little research into how WM training aids participants in their daily life. Here we propose that incorporating design principles from the fields of Perceptual Learning (PL) and Computer Science might augment the efficacy of WM training, and ultimately lead to greater learning and transfer. In particular, the field of PL has identified numerous mechanisms (including attention, reinforcement, multisensory facilitation and multi-stimulus training) that promote brain plasticity. Also, computer science has made great progress in the scientific approach to game design that can be used to create engaging environments for learning. We suggest that approaches integrating knowledge across these fields may lead to a more effective WM interventions and better reflect real world conditions.

Keywords: brain training; game design; perceptual learning; video games; working memory.

Figure 1

(A) Diagram of an n-back task presented as a 2-back task (Jaeggi et al., 2008, 2010). Here, visual and auditory stimuli are presented simultaneously and participants have to respond to both modality streams independently. (B) Diagram of a complex span training task (Buschkuehl et al., ; Loosli et al., 2012). Animal pictures are presented sequentially, and participants respond to the orientation of each picture, and then reproduce the sequence in which the animals were presented. (C) Schematic of gamified n-back training task.

Figure 2

Interference of learning by gamification. Motivational features such as scores, prizes, and scene-changes seem to interfere with learning. Specifically, training with all these features led to a lesser degree of learning compared to training without motivational features over the course of three sessions of n-back training (adapted from Katz et al., 2014).