Objectives

Mental fatigability refers to the failure to sustain participation in tasks requiring mental effort. Older adults with vascular risk are at particular risk for experiencing mental fatigability. The present study (1) tested a new way of measuring objective mental fatigability by examining its association with perceived mental fatigability; and (2) identified associated psychological, physiological, and situational predictors.

Methods

A cross-sectional study was conducted with 49 community-dwelling participants aged 75+ years with vascular risk. A 20-minute fatigability-manipulation task was used to induce mental fatigability and develop objective and perceived mental fatigability measures. Objective fatigability was calculated by the change of reaction time over the course of the task. Perceived fatigability was calculated by the change of fatigue self-reported before and after the task. A set of potential psychological, physiological, and situational predictors were measured.

Results

There was a significant increase in reaction time and self-reported fatigue to the fatigability manipulation task, indicating occurrence of objective and perceived mental fatigability. Reaction time and self-reported fatigue were moderately, but significantly correlated. Higher levels of executive control and having a history of more frequently engaging in mental activities were associated with lower objective mental fatigability. None of the examined factors were associated with perceived mental fatigability.

Conclusion

Objective and perceived mental fatigability were sensitive to our fatigability-manipulation task. While these two measures were correlated, they were not associated with the same factors. These findings need to be validated in studies with a more heterogeneous sample and a greater variety of fatigability-manipulation tasks.

Objectives

Adaptive physiological stress regulation is rarely studied in mild cognitive impairment (MCI). Here we targeted mental fatigability (MF) as a determinant of altered high frequency heart rate variability (HF-HRV) reactivity in individuals with MCI, and examined frontobasal ganglia circuitry as a neural basis supporting the link between MF and HF-HRV reactivity.

Methods

We measured mental fatigability and HF-HRV during a 60-minute cognitive stress protocol in 19 individuals with MCI. HF-HRV responses were modeled using a quadratic equation. Resting state functional connectivity of intra- and inter-network frontobasal ganglia circuitry was assessed using blood-oxygen-level-dependent magnetic resonance imaging among seven of the participants.

Results

Lower MF was associated with faster and greater rebound in U-shape HF-HRV reactivity, which linked to a stronger connectivity between right middle frontal gyrus and left putamen.

Conclusions

Results suggest that MF may contribute to abnormal physiological stress regulation in MCI, and fronto basal ganglia circuitry may support the link.

Objectives

To examine the cognitive and neural effects of vision-based speed-of-processing (VSOP) training in older adults with amnestic mild cognitive impairment (aMCI) and contrast those effects with an active control (mental leisure activities (MLA)).

Design

Randomized single-blind controlled pilot trial.

Setting

Academic medical center.

Participants

Individuals with aMCI (N = 21).

Intervention

Six-week computerized VSOP training.

Measurements

Multiple cognitive processing measures, instrumental activities of daily living (IADLs), and two resting state neural networks regulating cognitive processing: central executive network (CEN) and default mode network (DMN).

Results

VSOP training led to significantly greater improvements in trained (processing speed and attention: F1,19  = 6.61, partial η(2)  = 0.26, P = .02) and untrained (working memory: F1,19  = 7.33, partial η(2)  = 0.28, P = .01; IADLs: F1,19  = 5.16, partial η(2)  = 0.21, P = .03) cognitive domains than MLA and protective maintenance in DMN (F1, 9  = 14.63, partial η(2)  = 0.62, P = .004). VSOP training, but not MLA, resulted in a significant improvement in CEN connectivity (Z = -2.37, P = .02).

Conclusion

Target and transfer effects of VSOP training were identified, and links between VSOP training and two neural networks associated with aMCI were found. These findings highlight the potential of VSOP training to slow cognitive decline in individuals with aMCI. Further delineation of mechanisms underlying VSOP-induced plasticity is necessary to understand in which populations and under what conditions such training may be most effective.