FAST: A Novel Executive Function-Based Approach to Cognitive Enhancement

摘要

The present study introduces a novel cognitive intervention aimed at improving fluid intelligence (Gf), based on a framework we refer to as FAST: Flexible, Adaptive, Synergistic Training. FAST leverages a combination of novel game-based executive function (EF) training—designed specifically to enhance the likelihood of transfer—and transcranial electrical stimulation (tES), with aims to synergistically activate and strengthen mechanisms of cognitive control critical to Gf. To test our intervention, we collected three Gf measures from 113 participants [the advanced short Bochumer Matrizen-Test (BOMAT), Raven’s Advanced Progressive Matrices (APM), and matrices similar to Raven’s generated by Sandia labs], prior to and following one of three interventions: (1) the FAST + tRNS intervention, a combination of 30 min of daily training with our novel training game, Robot Factory, and 20 min of concurrent transcranial random noise stimulation applied to bilateral dorsolateral prefrontal cortex (DLPFC); (2) an adaptively difficult Active Control intervention comprised of visuospatial tasks that specifically do not target Gf; or (3) a no-contact control condition. Analyses of changes in a Gf factor from pre- to post-test found numerical increases for the FAST + tRNS group compared to the two control conditions, with a 0.3 SD increase relative to Active Control (p = 0.07), and a 0.19 SD increase relative to a No-contact control condition (p = 0.26). This increase was found to be largely driven by significant differences in pre- and post-test Gf as measured on the BOMAT test. Progression through the FAST training game (Robot Factory) was significantly correlated with changes in Gf. This is in contrast with progress in the Active Control condition, as well as with changes in individual EFs during FAST training, which did not significantly correlate with changes in Gf. Taken together, this research represents a useful step forward in providing new insights into, and new methods for studying, the nature of Gf and its malleability. Though our results await replication and extension, they provide preliminary evidence that the crucial characteristic of Gf may, in fact, be the ability to combine EFs rapidly and adaptively according to changing demand, and that Gf may be susceptible to targeted training.