The challenge of non-Markovian energy balance models in climate.

We first review the way in which Hasselmann's paradigm, introduced in 1976 and recently honored with the Nobel Prize, can, like many key innovations in complexity science, be understood on several different levels. It can be seen as a way to add variability into the pioneering energy balance models (EBMs) of Budyko and Sellers. On a more abstract level, however, it used the original stochastic mathematical model of Brownian motion to provide a conceptual superstructure to link slow climate variability to fast weather fluctuations, in a context broader than EBMs, and led Hasselmann to posit a need for negative feedback in climate modeling. Hasselmann's paradigm has still much to offer us, but naturally, since the 1970s, a number of newer developments have built on his pioneering ideas. One important one has been the development of a rigorous mathematical hierarchy that embeds Hasselmann-type models in the more comprehensive Mori-Zwanzig generalized Langevin equation (GLE) framework. Another has been the interest in stochastic EBMs with a memory that has slower decay and, thus, longer range than the exponential form seen in his EBMs. In this paper, we argue that the Mori-Kubo overdamped GLE, as widely used in statistical mechanics, suggests the form of a relatively simple stochastic EBM with memory for the global temperature anomaly. We also explore how this EBM relates to Lovejoy et al.'s fractional energy balance equation.

Multimodal Predictive Modeling: Scalable Imaging Informed Approaches to Predict Future Brain Health.

Background: Predicting future brain health is a complex endeavor that often requires integrating diverse data sources. The neural patterns and interactions identified through neuroimaging serve as the fundamental basis and early indicators that precede the manifestation of observable behaviors or psychological states. New Method: In this work, we introduce a multimodal predictive modeling approach that leverages an imaging-informed methodology to gain insights into future behavioral outcomes. We employed three methodologies for evaluation: an assessment-only approach using support vector regression (SVR), a neuroimaging-only approach using random forest (RF), and an image-assisted method integrating the static functional network connectivity (sFNC) matrix from resting-state functional magnetic resonance imaging (rs-fMRI) alongside assessments. The image-assisted approach utilized a partially conditional variational autoencoder (PCVAE) to predict brain health constructs in future visits from the behavioral data alone. Results: Our performance evaluation indicates that the image-assisted method excels in handling conditional information to predict brain health constructs in subsequent visits and their longitudinal changes. These results suggest that during the training stage, the PCVAE model effectively captures relevant information from neuroimaging data, thereby potentially improving accuracy in making future predictions using only assessment data. Comparison with Existing Methods: The proposed image-assisted method outperforms traditional assessment-only and neuroimaging-only approaches by effectively integrating neuroimaging data with assessment factors. Conclusion: This study underscores the potential of neuroimaging-informed predictive modeling to advance our comprehension of the complex relationships between cognitive performance and neural connectivity.

Greater physical fitness ( VO 2 max ) in healthy older adults associated with increased integrity of the locus coeruleus-noradrenergic system.

AIM: Physical activity (PA) is a key component for brain health and Reserve, and it is among the main dementia protective factors. However, the neurobiological mechanisms underpinning Reserve are not fully understood. In this regard, a noradrenergic (NA) theory of cognitive reserve (Robertson, 2013) has proposed that the upregulation of NA system might be a key factor for building reserve and resilience to neurodegeneration because of the neuroprotective role of NA across the brain. PA elicits an enhanced catecholamine response, in particular for NA. By increasing physical commitment, a greater amount of NA is synthetised in response to higher oxygen demand. More physically trained individuals show greater capabilities to carry oxygen resulting in greater Vo 2 max - a measure of oxygen uptake and physical fitness (PF). METHODS: We hypothesized that greater Vo 2 max would be related to greater Locus Coeruleus (LC) MRI signal intensity. In a sample of 41 healthy subjects, we performed Voxel-Based Morphometry analyses, then repeated for the other neuromodulators as a control procedure (Serotonin, Dopamine and Acetylcholine). RESULTS: As hypothesized, greater Vo 2 max related to greater LC signal intensity, and weaker associations emerged for the other neuromodulators. CONCLUSION: This newly established link between Vo 2 max and LC-NA system offers further understanding of the neurobiology underpinning Reserve in relationship to PA. While this study supports Robertson's theory proposing the upregulation of the NA system as a possible key factor building Reserve, it also provides ground for increasing LC-NA system resilience to neurodegeneration via Vo 2 max enhancement.

Toward precision brain health: accurate prediction of a cognitive index trajectory using neuroimaging metrics.

The goal of precision brain health is to accurately predict individuals' longitudinal patterns of brain change. We trained a machine learning model to predict changes in a cognitive index of brain health from neurophysiologic metrics. A total of 48 participants (ages 21-65) completed a sensorimotor task during 2 functional magnetic resonance imaging sessions 6 mo apart. Hemodynamic response functions (HRFs) were parameterized using traditional (amplitude, dispersion, latency) and novel (curvature, canonicality) metrics, serving as inputs to a neural network model that predicted gain on indices of brain health (cognitive factor scores) for each participant. The optimal neural network model successfully predicted substantial gain on the cognitive index of brain health with 90% accuracy (determined by 5-fold cross-validation) from 3 HRF parameters: amplitude change, dispersion change, and similarity to a canonical HRF shape at baseline. For individuals with canonical baseline HRFs, substantial gain in the index is overwhelmingly predicted by decreases in HRF amplitude. For individuals with non-canonical baseline HRFs, substantial gain in the index is predicted by congruent changes in both HRF amplitude and dispersion. Our results illustrate that neuroimaging measures can track cognitive indices in healthy states, and that machine learning approaches using novel metrics take important steps toward precision brain health.

Novel Oppositional Defiant Disorder or Conduct Disorder 24 Months After Traumatic Brain Injury in Children and Adolescents.

OBJECTIVE: The authors sought to identify predictive factors of new-onset or novel oppositional defiant disorder or conduct disorder assessed 24 months after traumatic brain injury (TBI). METHODS: Children ages 5 to 14 years who had experienced TBI were recruited from consecutive hospital admissions. Soon after injury, participants were assessed for preinjury characteristics, including psychiatric disorders, socioeconomic status (SES), psychosocial adversity, and family function, and the presence and location of lesions were documented by MRI. Psychiatric outcomes, including novel oppositional defiant disorder or conduct disorder, were assessed 24 months after injury. RESULTS: Of the children without preinjury oppositional defiant disorder, conduct disorder, or disruptive behavior disorder not otherwise specified who were recruited in this study, 165 were included in this sample; 95 of these children returned for the 24-month assessment. Multiple imputation was used to address attrition. The prevalence of novel oppositional defiant disorder or conduct disorder was 23.7 out of 165 (14%). In univariable analyses, novel oppositional defiant disorder or conduct disorder was significantly associated with psychosocial adversity (p=0.049) and frontal white matter lesions (p=0.016) and was marginally but not significantly associated with SES. In the final multipredictor model, frontal white matter lesions were significantly associated with novel oppositional defiant disorder or conduct disorder (p=0.021), and psychosocial adversity score was marginally but not significantly associated with the outcome. The odds ratio of novel oppositional defiant disorder or conduct disorder among the children with versus those without novel depressive disorder was significantly higher for girls than boys (p=0.025), and the odds ratio of novel oppositional defiant disorder or conduct disorder among the children with versus those without novel attention-deficit hyperactivity disorder (ADHD) was significantly higher for boys than girls (p=0.006). CONCLUSION: Approximately 14% of children with TBI developed oppositional defiant disorder or conduct disorder. The risk for novel oppositional defiant disorder or conduct disorder can be understood from a biopsychosocial perspective. Sex differences were evident for comorbid novel depressive disorder and comorbid novel ADHD.

Topology of turbulence within collisionless plasma reconnection.

In near-collisionless plasmas, which are ubiquitous in astrophysics, entropy production relies on fully-nonlinear processes such as turbulence and reconnection, which lead to particle acceleration. Mechanisms for turbulent reconnection include multiple magnetic flux ropes interacting to generate thin current sheets which undergo reconnection, leading to mixing and magnetic merging and growth of coherent structures, unstable reconnection current layers that fragment and turbulent reconnection outflows. All of these processes act across, and encompass, multiple reconnection sites. We use Magnetospheric Multi Scale four-point satellite observations to characterize the magnetic field line topology within a single reconnection current layer. We examine magnetopause reconnection where the spacecraft encounter the Electron Diffusion Region (EDR). We find fluctuating magnetic field with topology identical to that found for dynamically evolving vortices in hydrodynamic turbulence. The turbulence is supported by an electron-magnetohydrodynamic (EMHD) flow in which the magnetic field is effectively frozen into the electron fluid. Accelerated electrons are found in the EDR edge where we identify a departure from this turbulent topology, towards two-dimensional sheet-like structures. This is consistent with a scenario in which sub-ion scale turbulence can suppress electron acceleration within the EDR which would otherwise be possible in the electric field at the X-line.

Exploring how brain health strategy training informs the future of work.

Introduction: The workplace typically affords one of the longest periods for continued brain health growth. Brain health is defined by the World Health Organization (WHO) as the promotion of optimal brain development, cognitive health, and well-being across the life course, which we expanded to also include connectedness to people and purpose. This work was motivated by prior work showing individuals, outside of an aggregate setting, benefitted from training as measured by significant performance gains on a holistic BrainHealth Index and its factors (i.e., clarity, connectedness, emotional balance). The current research was conducted during the changing remote work practices emerging post-pandemic to test whether a capacity-building training would be associated with significant gains on measures of brain health and components of burnout. The study also tested the influence of utilization of training modules and days in office for individuals to inform workplace practices. Methods: We investigated whether 193 individuals across a firm's sites would improve on measures of brain health and burnout from micro-delivery of online tactical brain health strategies, combined with two individualized coaching sessions, and practical exercises related to work and personal life, over a six-month period. Brain health was measured using an evidenced-based measure (BrainHealth™ Index) with its components (clarity, connectedness, emotional balance) consistent with the WHO definition. Burnout was measured using the Maslach Burnout Inventory Human Services Survey. Days in office were determined by access to digital workplace applications from the firm's network. Regression analyses were used to assess relationships between change in BrainHealth factors and change in components of the Maslach Burnout Inventory. Results: Results at posttest indicated that 75% of the individuals showed gains on a composite BrainHealth Index and across all three composite factors contributing to brain health. Benefits were directly tied to training utilization such that those who completed the core modules showed the greatest gains. The current results also found an association between gains on both the connectedness and emotional balance brain health factors and reduced on burnout components of occupational exhaustion and depersonalization towards one's workplace. We found that fewer days in the office were associated with greater gains in the clarity factor, but not for connectedness and emotional balance. Discussion: These results support the value of a proactive, capacity-building training to benefit all employees to complement the more widespread limited offerings that address a smaller segment who need mental illness assistance programs. The future of work may be informed by corporate investment in focused efforts to boost collective brain capital through a human-centered, capacity-building approach. Efforts are underway to uncover the value of better brain health, i.e., Brainomics© - which includes economic, societal, and individual benefits.

Greater physical fitness (Vo2Max) in healthy older adults associated with increased integrity of the Locus Coeruleus-Noradrenergic system.

Physical activity (PA) is a key component for brain health and Reserve, and it is among the main dementia protective factors. However, the neurobiological mechanisms underpinning Reserve are not fully understood. In this regard, a noradrenergic (NA) theory of cognitive reserve (Robertson, 2013) has proposed that the upregulation of NA system might be a key factor for building reserve and resilience to neurodegeneration because of the neuroprotective role of NA across the brain. PA elicits an enhanced catecholamine response, in particular for NA. By increasing physical commitment, a greater amount of NA is synthetised in response to higher oxygen demand. More physically trained individuals show greater capabilities to carry oxygen resulting in greater Vo2max - a measure of oxygen uptake and physical fitness (PF). In the current study, we hypothesised that greater Vo2 max would be related to greater Locus Coeruleus (LC) MRI signal intensity. As hypothesised, greater Vo2max related to greater LC signal intensity across 41 healthy adults (age range 60-72). As a control procedure, in which these analyses were repeated for the other neuromodulators' seeds (for Serotonin, Dopamine and Acetylcholine), weaker associations emerged. This newly established link between Vo2max and LC-NA system offers further understanding of the neurobiology underpinning Reserve in relationship to PA. While this study supports Robertson's theory proposing the upregulation of the noradrenergic system as a possible key factor building Reserve, it also provide grounds for increasing LC-NA system resilience to neurodegeneration via Vo2max enhancement.

Ancient DNA elucidates the lost world of western Indian Ocean giant tortoises and reveals a new extinct species from Madagascar.

Before humans arrived, giant tortoises occurred on many western Indian Ocean islands. We combined ancient DNA, phylogenetic, ancestral range, and molecular clock analyses with radiocarbon and paleogeographic evidence to decipher their diversity and biogeography. Using a mitogenomic time tree, we propose that the ancestor of the extinct Mascarene tortoises spread from Africa in the Eocene to now-sunken islands northeast of Madagascar. From these islands, the Mascarenes were repeatedly colonized. Another out-of-Africa dispersal (latest Eocene/Oligocene) produced on Madagascar giant, large, and small tortoise species. Two giant and one large species disappeared c. 1000 to 600 years ago, the latter described here as new to science using nuclear and mitochondrial DNA. From Madagascar, the Granitic Seychelles were colonized (Early Pliocene) and from there, repeatedly Aldabra (Late Pleistocene). The Granitic Seychelles populations were eradicated and later reintroduced from Aldabra. Our results underline that integrating ancient DNA data into a multi-evidence framework substantially enhances the knowledge of the past diversity of island faunas.

Effects of online brain training on self-reported mental health symptoms for generally healthy adults during the Covid-19 pandemic.

BACKGROUND: The cognitive training Strategic Memory Advanced Reasoning Training (SMART) has been shown to improve symptoms of depression, anxiety, and stress when completed using in-person delivery, but mental health outcomes have not yet been studied for online delivery of SMART. METHODS: Data was analyzed from 145 generally healthy adults participating in the BrainHealth Project pilot study who had access to 12 weeks of online self-paced SMART and self-reported mental health symptoms on the Depression Anxiety Stress Scale (DASS-21) pre- and post-training. We utilized linear models to examine the change in self-reported symptoms of depression, anxiety, and stress following the 12-week training period and to explore the influence of age, gender, and education on changes in symptomatology. Data from 44 participants who completed a follow-up DASS-21 6 months after completing SMART was used to explore the lasting impact of the training. RESULTS: Improvements in depression, anxiety, and stress symptoms were observed following online SMART, evidenced by a significant decrease in self-reported symptoms on the DASS-21. Improvement in self-reported mental health symptomatology was maintained or continued to improve 6-month post-training. No significant effect of gender was observed, but findings motivate additional exploration of the effects of education and age. CONCLUSION: Online SMART should be considered a low-cost, high-impact approach for supporting public mental health for generally healthy adults.

Novel Psychiatric Disorder 6 Months After Traumatic Brain Injury in Children and Adolescents.

OBJECTIVE: To investigate the factors predictive of novel psychiatric disorders in the interval 0-6 months following traumatic brain injury (TBI). METHODS: Children ages 5-14 years consecutively hospitalized for mild to severe TBI at five hospitals were recruited. Participants were evaluated at baseline (soon after injury) for pre-injury characteristics including psychiatric disorders, socioeconomic status (SES), psychosocial adversity, family function, family psychiatric history, and adaptive function. In addition to the psychosocial variables, injury severity and lesion location detected with acquisition of a research MRI were measured to develop a biopsychosocial predictive model for development of novel psychiatric disorders. Psychiatric outcome, including occurrence of a novel psychiatric disorder, was assessed 6 months after the injury. RESULTS: The recruited sample numbered 177 children, and 141 children (80%) returned for the six-month assessment. Of the 141 children, 58 (41%) developed a novel psychiatric disorder. In univariable analyses, novel psychiatric disorder was significantly associated with lower SES, higher psychosocial adversity, and lesions in frontal lobe locations, such as frontal white matter, superior frontal gyrus, inferior frontal gyrus, and orbital gyrus. Multivariable analyses found that novel psychiatric disorder was independently and significantly associated with frontal-lobe white matter, superior frontal gyrus, and orbital gyrus lesions. CONCLUSION: The results demonstrate that occurrence of novel psychiatric disorders following pediatric TBI requiring hospitalization is common and has identifiable psychosocial and specific biological predictors. However, only the lesion predictors were independently related to this adverse psychiatric outcome.

Investing in Late-Life Brain Capital.

Within many societies and cultures around the world, older adults are too often undervalued and underappreciated. This exacerbates many key challenges that older adults may face. It also undermines the many positive aspects of late life that are of tremendous value at both an individual and societal level. We propose a new approach to elevate health and well-being in late life by optimizing late-life Brain Capital. This form of capital prioritizes brain skills and brain health in a brain economy, which the challenges and opportunities of the 21st-century demands. This approach incorporates investing in late-life Brain Capital, developing initiatives focused on building late-life Brain Capital.

Higher-Order Executive Function in Middle School: Training Teachers to Enhance Cognition in Young Adolescents.

The epoch of adolescent brain development is an ideal time to train complex thinking skills, and middle schools provide an ideal environment to train and foster this acquisition. Unfortunately, few teachers are equipped with enough knowledge of the science of learning and evidence-based methodology, to ensure all students are given sufficient opportunity to develop their cognitive capacity to the fullest. Using our evidenced-based higher-order executive function training program, we trained current teachers to provide cognitive training to their students. The results of this study demonstrate the efficacy of teacher-implemented intervention for immediate improvement in high-level executive function capacities such as gist-reasoning and interpretive statement production. More importantly, we found evidence of far transfer via students' improved academic performance in all standardized test content areas (Reading, Mathematics, Science, and Social Studies) when compared to their untrained peers. Our findings support the importance of providing intensive professional development that afford educators with a greater understanding of the brain, how we learn, and the importance of evidence-based programs to advance and instill high-level executive function in all students.

Novel Oppositional Defiant Disorder 12 Months After Traumatic Brain Injury in Children and Adolescents.

OBJECTIVE: The investigators examined the factors predictive of novel oppositional defiant disorder in the 6-12 months following traumatic brain injury (TBI). METHODS: Children ages 5-14 years old who experienced a TBI were recruited from consecutive admissions to five hospitals. Participants were evaluated soon after injury (baseline) for preinjury characteristics, including psychiatric disorders, adaptive function, family function, psychosocial adversity, family psychiatric history, socioeconomic status, and injury severity, to develop a biopsychosocial predictive model for development of novel oppositional defiant disorder. MRI analyses were conducted to examine potential brain lesions. Psychiatric outcome, including that of novel oppositional defiant disorder, was assessed 12 months after injury. RESULTS: Although 177 children were recruited for the study, 120 children without preinjury oppositional defiant disorder, conduct disorder, or disruptive behavior disorder not otherwise specified (DBD NOS) returned for the 12-month assessment. Of these 120 children, seven (5.8%) exhibited novel oppositional defiant disorder, and none developed conduct disorder or DBD NOS in the 6-12 months postinjury. Novel oppositional defiant disorder was significantly associated with lower socioeconomic status, higher psychosocial adversity, and lower preinjury adaptive functioning. CONCLUSIONS: These results demonstrate that novel oppositional defiant disorder following TBI selectively and negatively affects an identifiable group of children. Both proximal (preinjury adaptive function) and distal (socioeconomic status and psychosocial adversity) psychosocial variables significantly increase risk for this outcome.

Novel Oppositional Defiant Disorder 6 Months After Traumatic Brain Injury in Children and Adolescents.

OBJECTIVE: The investigators aimed to assess predictive factors of novel oppositional defiant disorder (ODD) among children and adolescents in the first 6 months following traumatic brain injury (TBI). METHODS: Children ages 5-14 years who experienced a TBI were recruited from consecutive admissions to five hospitals. Testing of a biopsychosocial model that may elucidate the development of novel ODD included assessment soon after injury (baseline) of preinjury characteristics, including psychiatric disorders, adaptive function, family function, psychosocial adversity, family psychiatric history, socioeconomic status, injury severity, and postinjury processing speed (which may be a proxy for brain injury). MRI analyses were also conducted to examine potential brain lesions. Psychiatric outcome, including that of novel ODD, was assessed 6 months after the injury. RESULTS: A total of 177 children and adolescents were recruited for the study, and 134 who were without preinjury ODD, conduct disorder, or disruptive behavior disorder not otherwise specified (DBD NOS) returned for the 6-month assessment. Of those who returned 6 months postinjury, 11 (8.2%) developed novel ODD, and none developed novel conduct disorder or DBD NOS. Novel ODD was significantly associated with socioeconomic status, preinjury family functioning, psychosocial adversity, and processing speed. CONCLUSIONS: These findings show that an important minority of children with TBI developed ODD. Psychosocial and injury-related variables, including socioeconomic status, lower family function, psychosocial adversity, and processing speed, significantly increase risk for this outcome.

Enhancing Patient Understanding of Medication Risks and Benefits.

OBJECTIVE: To evaluate the effectiveness of 2 interventions, including the DrugFactsBox format for presenting written medication information and the SMART (Strategic Memory Advanced Reasoning Training) program designed to enhance gist (i.e., "bottom-line" meaning) reasoning ability. METHODS: We used a 2 × 2 factorial research design. A total of 286 patients with rheumatoid arthritis were randomly assigned to 1 of 4 groups, including DrugFactsBox with the SMART program, DrugFactsBox without the SMART program, other consumer medication information (CMI) with the SMART program, and other CMI without the SMART program. Data were collected via telephone interviews and online questionnaires at 4 time points, including baseline and 6-week, 3-month, and 6-month time points following baseline. The primary outcome variable was informed decision-making, which was defined as making a value-consistent decision concerning use of disease-modifying antirheumatic drugs based on adequate knowledge. RESULTS: We found no main effects for the 2 interventions, either alone or in combination. However, there was a significant interaction between assignment to the SMART/no SMART groups and informed decision-making at baseline. Among participants in the SMART groups who did not meet the criteria for informed decision-making at baseline, 42.5% met the criteria at the 6-month follow-up, compared to 23.6% of participants in the no SMART groups (mean difference 18.9 [95% confidence interval 5.6, 32.2]; P = 0.007). This difference was driven by increased knowledge in the SMART groups. Among participants who met the criteria for informed decision-making at baseline, the difference between the SMART and no SMART groups was not statistically significant. CONCLUSION: Participation in a theory-driven program to enhance gist reasoning may have a beneficial effect on informed decision-making among patients with inadequate knowledge concerning therapeutic options.

Snoring Remediation with Oral Appliance Therapy Potentially Reverses Cognitive Impairment: An Intervention Controlled Pilot Study.

Respiration rate (RR) dynamics entrains brain neural networks. RR differences between mild cognitive impairment (MCI) and Alzheimer's disease (AD) in response to oral appliance therapy (OAT) are unknown. This pilot study investigated if RR during stable sleep shows a relationship to pathological severity in subjects with MCI and AD who snore and if RR is influenced following stabilization of the upper airway using OAT. The study cohort was as follows: cognitively normal (CN; n = 14), MCI (n = 14) and AD (n = 9); and a sub-population receiving intervention, CN (n = 5), MCI (n = 7), AD (n = 6) subjects. The intervention used was an oral appliance plus a mouth shield (Tx). RR maximum (max) rate (breaths/minute) and RR fluctuation during 2116 stable sleep periods were measured. The Montreal cognitive assessment (MoCA) was administered before and after 4 weeks with Tx. Baseline data showed significantly higher RR fluctuation in CN vs. AD (p < 0.001) but not between CN vs. MCI (p = 0.668). Linear mixed model analysis indicated Tx effect (p = 0.008) for RR max. Tx after 4 weeks lowered the RR-max in MCI (p = 0.022) and AD (p < 0.001). Compared with AD RR max, CN (p < 0.001) and MCI (p < 0.001) were higher with Tx after 4 weeks. Some MCI and AD subjects improved executive and memory function after 4 weeks of Tx.

Building brain capital.

Brains are indispensable drivers of human progress. Why not invest more heavily in them? We seek to place Brain Capital at the center of a new narrative to fuel economic and societal recovery and resilience.

Phosphate Brain Energy Metabolism and Cognition in Alzheimer's Disease: A Spectroscopy Study Using Whole-Brain Volume-Coil 31Phosphorus Magnetic Resonance Spectroscopy at 7Tesla.

INTRODUCTION: Mitochondrial dysfunction is a neurometabolic hallmark signaling abnormal brain energy metabolism (BEM) targeted as a potential early marker of Alzheimer's disease (AD). Advanced imaging technologies, such as 31phosphorus magnetic resonance spectroscopy (31P MRS) at ultra-high-field (UHF) magnetic strength 7T, provide sensitive phosphate-BEM (p-BEM) data with precision. The study's first goal was to develop a methodology to measure phosphate energy and membrane metabolites simultaneously across the whole-brain using volume-coil 31P MRS at 7T in three groups-cognitively normal (CN), amnestic mild cognitive impairment (aMCI), and AD. The second aim investigated whether p-BEM markers in the four brain regions-frontal, temporal, parietal, and occipital were significantly different across the three groups. The final goal examined correspondence between the p-BEM markers and cognition in the three groups. METHODS: Forty-one participants (CN = 15, aMCI = 15, AD = 11) were enrolled and completed cognitive assessment and scan. The cognitive domains included executive function (EF), memory, attention, visuospatial skills, and language. The p-BEM markers were measured using energy reserve index (PCr/t-ATP), energy consumption index (intracellular_Pi/t-ATP), metabolic state indicator (intracellular_Pi/PCr), and regulatory co-factors [magnesium (Mg2+) and intracellular pH]. RESULTS: Thirteen metabolites were measured simultaneously from the whole brain for all three group with high spectral resolution at UHF. In the aMCI group, a lower p-BEM was observed compared to CN group based on two markers, i.e., energy reserve (p = 0.009) and energy consumption (p = 0.05) indices; whereas in AD a significant increase was found in metabolic stress indicator (p = 0.007) and lower Mg2+ (p = 0.004) in the temporal lobes compared to aMCI using ANOVA between group analytical approach. Finally, using a linear mixed model, a significant positive correlation was found between Mg2+ and cognitive performance of memory (p = 0.013), EF (p = 0.023), and attention (p = 0.0003) in CN but not in aMCI or AD. CONCLUSION: To our knowledge, this is the first study to show that it is possible to measure p-BEM in vivo with precision at UHF across the three groups. Moreover, the findings suggest that p-BEM may be compromised in aMCI even before an AD diagnosis, which in future studies should explore to examine whether this energy crisis contributes to some of the earliest neuropathophysiologic changes in AD.

A Novel BrainHealth Index Prototype Improved by Telehealth-Delivered Training During COVID-19.

Introduction: Brain health is neglected in public health, receiving attention after something goes wrong. Neuroplasticity research illustrates that preventive steps strengthen the brain's component systems; however, this information is not widely known. Actionable steps are needed to scale proven population-level interventions. Objectives: This pilot tested two main objectives: (1) the feasibility/ease of use of an online platform to measure brain health, deliver training, and offer virtual coaching to healthy adults and (2) to develop a data driven index of brain health. Methods: 180 participants, ages 18-87, enrolled in this 12-week pilot. Participants took a BrainHealth Index™ (BHI), a composite of assessments encompassing cognition, well-being, daily-life and social, pre-post training. Participants engaged in online training with three coaching sessions. We assessed changes in BHI, effects of training utilization and demographics, contributions of sub-domain measures to the BHI and development of a factor analytic structure of latent BrainHealth constructs. Results: The results indicated that 75% of participants showed at least a 5-point gain on their BHI which did not depend on age, education, or gender. The contribution to these gains were from all sub-domains, including stress, anxiety and resilience, even though training focused largely on cognition. Some individuals improved due to increased resilience and decreased anxiety, whereas others improved due to increased innovation and social engagement. Larger gains depended on module utilization, especially strategy training. An exploratory factor analytic solution to the correlation matrix of online assessments identified three latent constructs. Discussion/Conclusion: This pilot study demonstrated the efficacy of an online platform to assess changes on a composite BrainHealth Index and efficacy in delivering training modules and coaching. We found that adults, college age to late life, were motivated to learn about their brain and engage in virtual-training with coaching to improve their brain health. This effort intends to scale up to thousands, thus the pilot data, tested by an impending imaging pilot, will be utilized in ongoing machine learning (ML) algorithms to develop a precision brain health model. This pilot is a first step in scaling evidence-based brain health protocols to reach individuals and positively affect public health globally.