Targeting autonomic flexibility to enhance cognitive training outcomes in older adults with mild cognitive impairment: study protocol for a randomized controlled trial

Assessment of heart rate deceleration capacity, heart rate deceleration runs, heart rate acceleration capacity, and lipoprotein-related phospholipase A2 as predictors in individuals with dementia

Background

Autonomic dysfunction plays an essential role in dementia, however, it is not known whether electrocardiogram autonomic dysfunction-related indicators are associated with the severity of dementia. In this study, we attempted to investigate whether these indicators are correlated in patients with vascular dementia and Alzheimer's disease compared with normal health individuals. For this purpose, we measured and analyzed the predictive value of heart rate deceleration capacity (DC), heart rate deceleration runs (DRs), heart rate acceleration capacity (AC) along with the plasma levels of lipoprotein-associated phospholipase A2 (Lp-PLA2).

Methods

We compared 83 dementia cases including 41 vascular dementia (VD), 42 Alzheimer's disease (AD) patients with 42 elderly health controls. The Mini-Mental State Examination (MMSE) scores, DC, DRs, AC, and Lp-PLA2 levels were comprehensively evaluated.

Results

Our studies showed that DC and DRs in VD and AD groups were significantly lower than those in controls, while AC values were significantly higher. Furthermore, the risk stratification (high- and moderate-) of DC, DRs, and AC in VD and AD groups was increased, while the low-risk was simultaneously decreased. In addition, DC and DRs were positively while AC and Lp-PLA2 were negatively correlated with MMSE scores. Logistic regression analysis indicated that DC, DRs, AC, and Lp-PLA2 were associated with dementia. Moreover, the areas under the ROC curves showed that the combination of five variables and AC + Lp-PLA2 were 0.970 (95% CI, 0.923-0.992) and 0.940 (95% CI, 0.882-0.974) were larger than each single indicator alone.

Conclusion

Distinctive alterations in dynamic electrocardiogram-related indicators reveal a decline in autonomic nervous functions among individuals with dementia. By incorporating comprehensive analyses of DC, DRs, AC, and Lp-PLA2 values, the specificity and sensitivity of dementia diagnosis can be significantly enhanced.

Effective engagement in computerized cognitive training for older adults

Computerized cognitive training (CCT) is a frontline therapy to prevent or slow age-related cognitive decline. A prerequisite for CCT research to provide clinically relevant improvements in cognition is to understand effective engagement, i.e., the pattern of energy investment that ensures CCT effectiveness. Even though previous studies have assessed whether particular variables (e.g., gamification) predict engagement and/or CCT effectiveness, the field lacks a systematic approach to understanding effective engagement. Here, by comprehensively reviewing and evaluating engagement and adjacent literature, we propose a standardized measurement and operational framework to promote effective engagement with CCT targeting cognitive decline in older adults. We suggest that promoting effective engagement with CCT has two key steps: 1) comprehensively measuring engagement with CCT and 2) identifying which aspects of engagement are essential to achieve the pre-specified outcome of clinically relevant improvements in cognition. The proposed measurement and operational framework of effective engagement will allow future research to maximize older adults' engagement with CCT to slow/prevent age-related cognitive decline.

Vision-based estimation of fatigue and engagement in cognitive training sessions

Computerized cognitive training (CCT) is a scalable, well-tolerated intervention that has promise for slowing cognitive decline. The effectiveness of CCT is often affected by a lack of effective engagement. Mental fatigue is a the primary factor for compromising effective engagement in CCT, particularly in older adults at risk for dementia. There is a need for scalable, automated measures that can constantly monitor and reliably detect mental fatigue during CCT. Here, we develop and validate a novel Recurrent Video Transformer (RVT) method for monitoring real-time mental fatigue in older adults with mild cognitive impairment using their video-recorded facial gestures during CCT. The RVT model achieved the highest balanced accuracy (79.58%) and precision (0.82) compared to the prior models for binary and multi-class classification of mental fatigue. We also validated our model by significantly relating to reaction time across CCT tasks (Waldχ2=5.16,p=0.023). By leveraging dynamic temporal information, the RVT model demonstrates the potential to accurately measure real-time mental fatigue, laying the foundation for future CCT research aiming to enhance effective engagement by timely prevention of mental fatigue.

Autonomic nervous system flexibility for understanding brain aging

A recent call was made for autonomic nervous system (ANS) measures as digital health markers for early detection of Alzheimer's disease and related dementia (AD/ADRD). Nevertheless, contradictory or inconclusive findings exist. To help advance understanding of ANS' role in dementia, we draw upon aging and dementia-related literature, and propose a framework that centers on the role of ANS flexibility to guide future work on application of ANS function to differentiating the degree and type of dementia-related brain pathologies. We first provide a brief review of literature within the past 10 years on ANS and dementia-related brain pathologies. Next, we present an ANS flexibility model, describing how the model can be applied to understand these brain pathologies, as well as differentiate or even be leveraged to modify typical brain aging and dementia. Lastly, we briefly discuss the implication of the model for understanding resilience and vulnerability to dementia-related outcomes.

Bright Morning Lighting Enhancing Parasympathetic Activity at Night: A Pilot Study on Elderly Female Patients with Dementia without a Pacemaker

Exposure to bright morning light (BML) entrains the master circadian clock, modulates physiological circadian rhythms, and reduces sleep-wake disturbances. However, its impact on the autonomic nervous system at night remains unclear. Here, we investigated the effects of BML exposure on parasympathetic nervous system (PSNS) and sympathetic nervous system (SNS) activity at night in elderly women. This nonrandomized controlled pilot study included female participants aged ≥ 60 years who were diagnosed with a type of dementia or cognitive disorder, excluding individuals with pacemakers. The treatment group was exposed to 2500 lx of BML, whereas the control group was exposed to 200 lx of general lighting. We measured heart rate variability to quantify ANS activity. The treatment group displayed significant increases in high-frequency (HF) power (Roy's largest root = 1.62; p < 0.001) and nonsignificant decreases in normalized low-frequency (LF%) power. The corresponding nonsignificant decreases in the low-frequency/high-frequency (LF/HF) ratio and cognitive function were correlated with PSNS activity (Roy's largest root = 1.41; p < 0.001), which improved severe dementia. BML exposure reduced SNS activity and enhanced PSNS activity at night in female participants, which improved cognitive function. Thus, BML therapy may be a useful clinical tool for alleviating cognitive decline.

Utility of paced breathing tablet guidance apparatus with real-time feedback on autonomic function for individuals with mild cognitive impairment: a pilot study

BACKGROUND

Mild cognitive impairment (MCI) individuals also show significant parasympathetic deficits, while autonomic nervous system (ANS) flexibility can strengthen cognitive and brain function. Paced (or slow) breathing has significant effects on the ANS and is associated with relaxation and well-being. However, paced breathing requires considerable time and practice, a significant barrier to its widespread adoption. Feedback systems appear promising to make practice more time-efficient. A tablet guidance system providing real-time feedback on autonomic function was developed for MCI individuals and tested for efficacy.

METHODS

In this single-blind study, 14 outpatients with MCI practised with the device for 5 min twice a day for 2 weeks. The active group received feedback (FB+), whereas the placebo group (FB-) did not. Coefficient of variation of R-R intervals as the outcome indicator was measured immediately after the first intervention (T₁ ), the end of the 2-week intervention (T₂ ), and 2 weeks later (T₃ ).

RESULTS

The mean outcome of the FB- group remained unchanged during the study period, whereas the outcome value of the FB+ group increased and retained the intervention effect for an additional 2 weeks.

CONCLUSIONS

Results indicate this FB system-integrated apparatus may be useful for MCI patients for effectively learning paced breathing.

CCA identifies a neurophysiological marker of adaptation capacity that is reliably linked to internal locus of control of cognition in amnestic MCI

Locus of control (LOC) describes whether an individual thinks that they themselves (internal LOC) or external factors (external LOC) have more influence on their lives. LOC varies by domain, and a person's LOC for their intellectual capacities (LOC-Cognition) may be a marker of resilience in older adults at risk for dementia, with internal LOC-Cognition relating to better outcomes and improved treatment adherence. Vagal control, a key component of parasympathetic autonomic nervous system (ANS) regulation, may reflect a neurophysiological biomarker of internal LOC-Cognition. We used canonical correlation analysis (CCA) to identify a shared neurophysiological marker of ANS regulation from electrocardiogram (during auditory working memory) and functional connectivity (FC) data. A canonical variable from root mean square of successive differences (RMSSD) time series and between-network FC was significantly related to internal LOC-Cognition (β = 0.266, SE = 0.971, CI = [0.190, 4.073], p = 0.031) in 65 participants (mean age = 74.7, 32 female) with amnestic mild cognitive impairment (aMCI). Follow-up data from 55 of these individuals (mean age = 73.6, 22 females) was used to show reliability of this relationship (β = 0.271, SE = 0.971, CI = [0.033, 2.630], p = 0.047), and a second sample (40 participants with aMCI/healthy cognition, mean age = 72.7, 24 females) showed that the canonical vector biomarker generalized to visual working memory (β = 0.36, SE = 0.136, CI = [0.023, 0.574], p = 0.037), but not inhibition task RMSSD data (β = 0.08, SE = 1.486, CI = [- 0.354, 0.657], p = 0.685). This canonical vector may represent a biomarker of autonomic regulation that explains how some older adults maintain internal LOC-Cognition as dementia progresses. Future work should further test the causality of this relationship and the modifiability of this biomarker.

A Novel Explainability Approach for Technology-Driven Translational Research on Brain Aging

Brain aging leads to difficulties in functional independence. Mitigating these difficulties can benefit from technology that predicts, monitors, and modifies brain aging. Translational research prioritizes solutions that can be causally linked to specific pathophysiologies at the same time as demonstrating improvements in impactful real-world outcome measures. This poses a challenge for brain aging technology that needs to address the tension between mechanism-driven precision and clinical relevance. In the current opinion, by synthesizing emerging mechanistic, translational, and clinical research-related frameworks, and our own development of technology-driven brain aging research, we suggest incorporating the appreciation of four desiderata (causality, informativeness, transferability, and fairness) of explainability into early-stage research that designs and tests brain aging technology. We apply a series of work on electrocardiography-based "peripheral" neuroplasticity markers from our work as an illustration of our proposed approach. We believe this novel approach will promote the development and adoption of brain aging technology that links and addresses brain pathophysiology and functional independence in the field of translational research.