The heart and brain have bi-directional influences on each other, including autonomic regulation and hemodynamic connections. Heart rate variability (HRV) measures variation in beat-to-beat intervals. New findings about disorganized sinus rhythm (erratic rhythm, quantified as heart rate fragmentation, HRF) are discussed and suggest overestimation of autonomic activities in HRV changes, especially during aging or cardiovascular events. When excluding HRF, HRV is regulated via the central autonomic network (CAN). HRV acts as a proxy of autonomic activity and is associated with executive functions, decision-making, and emotional regulation in our health and wellbeing. Abnormal changes of HRV (e.g., decreased vagal functioning) are observed in various neurological conditions including mild cognitive impairments, dementia, mild traumatic brain injury, migraine, COVID-19, stroke, epilepsy, and psychological conditions (e.g., anxiety, stress, and schizophrenia). Efforts are needed to improve the dynamic and intriguing heart-brain interactions.

IntroductionResting heart rate (HR) and heart rate variability (HRV) have been linked with cognition in the general population and in older individuals. The knowledge of this aspect of heart-brain relationship is relatively absent in older individuals with early Alzheimer's disease (AD) pathology. This study explores relationships of the HR, HRV, and cognition in cognitively healthy individuals with pathological amyloid/tau ratio (CH-PATs) in cerebral spinal fluid (CSF) compared to those with normal ratio (CH-NATs).MethodsWe examined the relationships between 1) resting HR and Mini‐Mental State Examination (MMSE); 2) resting HR and brain processing during Stroop interference; and 3) resting vagally mediated HRV (vmHRV) and task switching performance.ResultsOur studies showed that compared to CH-NATs, those CH-PATs with higher resting HR presented with lower MMSE, and less brain activation during interference processing. In addition, resting vmHRV was significantly correlated with task switching accuracy in CH-NATs, but not in CH-PATs.DiscussionThese three different tests indicate dysfunctional heart-brain connections in CH-PATs, suggesting a potential cardio-cerebral dysfunctional integration.

Early screening to determine patient risk of developing Alzheimer’s will allow better interventions and planning but necessitates accessible methods such as behavioral biomarkers. Previously, we showed that cognitively healthy older individuals whose cerebrospinal fluid amyloid / tau ratio indicates high risk of cognitive decline experienced implicit interference during a high-effort task, signaling early changes in attention. To further investigate attention’s effect on implicit interference, we analyzed two experiments completed sequentially by the same high- and low-risk individuals. We hypothesized that if attention modulates interference, practice would affect the influence of implicit distractors. Indeed, while both groups experienced a strong practice effect, the association between practice and interference effects diverged between groups: stronger practice effects correlated with more implicit interference in high-risk participants, but less interference in low-risk individuals. Furthermore, low-risk individuals showed a positive correlation between implicit interference and EEG low-range alpha event-related desynchronization when switching from high-to low-load tasks. These results demonstrate how attention impacts implicit interference and highlight early differences in cognition between high- and low-risk individuals.

BackgroundAge related atrophy occurs in Alzheimer’s disease and related dementia (ADRD). Although atrophy was reported in early stage as mild cognitive impairment (MCI), the knowledge about earlier changes is limited. To fill this knowledge, we explored the age‐related atrophy in our pilot MRI database when participants at different stages of ADRD.MethodMRI data are analyzed using NeuroQuant. We studied MRI data in cognitively healthy (CH, n=74) individuals when their cerebrospinal fluid (CSF) amyloid/tau ratios were normal (CH‐NATs, n=18) or pathological (CH‐PATs, n=41), in participants with impaired or MCI (n=9), and Alzheimer’s disease (AD, n=6), and other dementia (OD, n=6). We explored age, gender‐corrected norm percentiles for atrophy analysis in age‐related structures – (including hippocampal occupancy score (HOC, percent of hippocampi volume relative to inferior lateral ventricle volume), hippocampi, entorhinal cortex, and inferior lateral ventricles) and whole brain, cerebral white matter. We compared the data between CH, MCI, AD, and OD, compared between CH‐NATs and CH‐PATs, and compared between CH with cerebrospinal fluid (CSF) amyloid pathology (ChA+, n=15) and CH without CSF pathology (ChA‐T‐N‐, n=13) based on CSF Aβ42, phosphor‐tau (p‐tau), and total tau (t‐tau). Bonferroni correction was used for Multiple comparisons.ResultAnalysis of MRIs collected at HMRI show neuro‐quantitative data in CH participants compared to MCI, AD, or OD, and MCI to AD and OD. Compared to CH, MCI have decreased HOC and larger superior lateral ventricle (Table 1, Figure 1), AD have decreased HOC, hippocampi, whole brain, and cerebral white matter, and larger lateral ventricles, OD have similar changes except hippocampi (no change). No significant changes observed between MCI and AD or OD. No significant changes were observed between CH‐NATs and CH‐PATs, or between ChA+ and ChA‐T‐N‐.ConclusionDespite sample size limitation, these results suggest: 1) norm percentile is sensitive to age‐related atrophy at impaired stages, consistent with known changes; Whole brain volume decreases in AD and OD, only AD observed decreased hippocampal atrophy; 2) No apparent age‐related changes were observed in CH stage. Overall, MRI age‐ and gender‐corrected norm percentile for age‐related atrophy analysis is informative in individuals as early as MCI stage.

BackgroundBoth resting heart rate variability (HRV) and resting heart rate (HR) are regulated by the central autonomic network linking prefrontal cortex with cardiac regulation. To better understand the interactions between the heart and cognition we determined the relationships between resting HR/HRV and cognitive function.MethodWe compared and correlated resting HR with Mini‐Mental State Exam (MMSE) in cognitively healthy (CH, n=137) individuals when their CSF amyloid/tau ratios were normal (CH‐NATs, n=51) or pathological (CH‐PATs, n=68), in participants with mild cognitive impairment (MCI, n=54), and Alzheimer’s disease (AD, n=42). We also compared and correlated HRV with behavioral performance (accuracy and response time) or alpha event‐related desynchronization (ERD) during Stroop (interference) or task switching testing between subsets of CH‐NATs and CH‐PATs. Cognitive tasks include: 1) Stroop during low load (congruent trials) and high load (incongruent trials); 2) task switching during low load, repeat trials (color‐color or word‐word) and high load, switch trials (color‐word or word‐color). HRV was assessed from 5‐minute resting ECG recording, including: HR and root mean squared of successive differences (RMSSD) that reflect vagal activities.ResultNo differences of resting HR or HRV were observed between CH‐NATs, CH‐PATs, MCI, and AD. Interestingly, resting HR negatively correlated with MMSE only in CH‐PATs (r=‐0.57, p=0.002), but not in CH‐NATs (r=0.07, p=0.71), CH (r=‐0.09, p=0.57), MCI (r=‐0.14, p=0.41), or AD (r=‐0.11, p=0.59) (Fig 1). For Stroop interference testing, resting HR (preceding task) positively correlated with frontal alpha ERD during high load trails (r=0.78, p=0.017) in CH‐PATs, but not in CH‐NATs (Fig 2). For task switch testing, resting RMSSD positively correlated with accuracy during switch trials (r=0.64, p=0.004) in CH‐NATs, but not in CH‐PATs (Fig 3).ConclusionThese results suggest: 1) resting HR is linked with cognition in CH‐PATs; 2) resting HR is related to inhibitory control in CH‐PATs: higher HR linked with less negative alpha ERD (less activation); 3) resting HRV predicts task switching performance in CH‐NATs: higher RMSSD linked with higher accuracy. Overall, resting HR and HRV potentially reflect cognition and executive functions that differentiate CH‐NATs and CH‐PATs, suggesting different cerebral‐cardiovascular integration in these two populations.