Learning and Memory

Aging is a complex natural phenomenon that is manifested by degenerative changes in the structure and function of cells and tissues. D-Galactose-induced aging mice are an artificial accelerated aging model that causes memory and learning impairment, oxidative stress, and neuroinflammation. In this study, we examined the underlying mechanism of an aging mouse model induced by D-galactose. Our behavioral Morris water maze results revealed that D-galactose administration for 2 months significantly induced memory and learning impairment in C57BL/6J mice. High performance liquid chromatography (HPLC) results showed elevated levels of the metabolite methylglyoxal (MG) in D-galactose-induced aging mice. Whether and how D-galactose induces senescence by elevated levels of reactive metabolite MG remain unclear. In our study, MG mainly accumulated through the following two aspects: to increase its source, namely, the triose phosphate produced by the glycolysis pathway, and to reduce its detoxification system, namely, the glyoxalase system. Therefore, elevated MG levels may be one of the causes of brain senescence in D-galactose-induced mice. However, the molecular mechanism of the increased level of the reaction metabolite methylglyoxal requires further exploration.

Background: Cognitive decline is a significant public health concern in older adults. Identifying new ways to maintain cognitive and brain health throughout the lifespan is of utmost importance. Simultaneous exercise and cognitive engagement has been shown to enhance brain function in animal and human studies. Virtual reality (VR) may be a promising approach for conducting simultaneous exercise and cognitive studies. In this study, we evaluated the feasibility of cycling in a cognitively enriched and immersive spatial navigation VR environment in younger and older adults.

Methods: A total of 20 younger (25.9 ± 3.7 years) and 20 older (63.6 ± 5.6 years) adults participated in this study. Participants completed four trials (2 learning and 2 recall) of cycling while wearing a head-mounted device (HMD) and navigating a VR park environment. Questionnaires were administered to assess adverse effects, mood, presence, and physical exertion levels associated with cycling in the VR environment.

Results: A total of 4 subjects withdrew from the study due to adverse effects, yielding a 90% completion rate. Simulator sickness levels were enhanced in both age groups with exposure to the VR environment but were within an acceptable range. Exposure to the virtual environment was associated with high arousal and low stress levels, suggesting a state of excitement, and most participants reported enjoyment of the spatial navigation task and VR environment. No association was found between physical exertion levels and simulator sickness levels.

Conclusion: This study demonstrates that spatial navigation while cycling is feasible and that older adults report similar experiences to younger adults. VR may be a powerful tool for engaging physical and cognitive activity in older adults with acceptable adverse effects and with reports of enjoyment. Future studies are needed to assess the efficacy of a combined exercise and cognitive VR program as an intervention for promoting healthy brain aging, especially in older adults with increased risk of age-related cognitive decline.

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.