Pictures for memory game for adults7/29/2023 ![]() ![]() Simple span tasks present sequences of stimuli that vary in set-size with participants typically reporting the items in (reverse) order of presentation. Span training targets WM capacity (Klingberg et al., 2002, 2005) typically relying on two types of tasks, simple and complex. ![]() We propose that integrating knowledge from psychology and neuroscience along with the science of video game design could critically inform the development of engaging, cognitively immersive challenges that will more optimally train WM memory processes. Off-the-shelf computer games and standard cognitive approaches each contain component properties that can benefit WM. Here we review recent WM training approaches discussing their strengths and limitations and suggest methods that are based on the principles of perceptual learning (PL) and game design to make them more effective. Au et al., 2014 Karbach and Verhaeghen, 2014 for recent meta-analyses). Recent approaches targeting skills related to WM (Klingberg et al., 2002, 2005 Jaeggi et al., 2008, 2010 Anguera et al., 2013 Goldin et al., 2014) have shown generalizing benefits to a wide number of non-trained cognitive tasks that are thought to rely on WM, including executive control and fluid reasoning (c.f. WM underlies performance in virtually all complex cognitive tasks (Shah and Miyake, 1999). Here, we focus on working memory (WM), a limited-capacity system for storing and manipulating information in a given moment. ![]() Recent research on “brain training” renews promise for improving memory and other cognitive skills. However, despite evidence these techniques improve memory performance, they do not target underlying memory processes, and while they do have some influence on memory systems in the brain (Maguire et al., 2003), they typically fail to broadly generalize to untrained activities (Verhaeghen et al., 1992 Maguire et al., 2003 St Clair-Thompson et al., 2010). Most approaches to improve memory implement strategies, such as creating mnemonic devices (for example, the method of loci). We suggest that approaches integrating knowledge across these fields may lead to a more effective WM interventions and better reflect real world conditions.Īs long as scientists have explored memory, they have strived, and often failed, to improve it. Also, computer science has made great progress in the scientific approach to game design that can be used to create engaging environments for learning. In particular, the field of PL has identified numerous mechanisms (including attention, reinforcement, multisensory facilitation and multi-stimulus training) that promote brain plasticity. 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. 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. 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.
0 Comments
Leave a Reply.AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |