A Subtype Perspective on Cognitive Trajectories in Healthy Aging.

Cognitive aging is a complex and dynamic process characterized by changes due to genetics and environmental factors, including lifestyle choices and environmental exposure, which contribute to the heterogeneity observed in cognitive outcomes. This heterogeneity is particularly pronounced among older adults, with some individuals maintaining stable cognitive function while others experience complex, non-linear changes, making it difficult to identify meaningful decline accurately. Current research methods range from population-level modeling to individual-specific assessments. In this work, we review these methodologies and propose that population subtyping should be considered as a viable alternative. This approach relies on early individual-specific detection methods that can lead to an improved understanding of changes in individual cognitive trajectories. The improved understanding of cognitive trajectories through population subtyping can lead to the identification of meaningful changes and the determination of timely, effective interventions. This approach can aid in informing policy decisions and in developing targeted interventions that promote cognitive health, ultimately contributing to a more personalized understanding of the aging process within society and reducing the burden on healthcare systems.

Baseline markers of cortical excitation and inhibition predict response to theta burst stimulation treatment for youth depression.

Theta burst stimulation (TBS), a specific form of repetitive transcranial magnetic stimulation (TMS), is a promising treatment for youth with Major Depressive Disorder (MDD) who do not respond to conventional therapies. However, given the variable response to TBS, a greater understanding of how baseline features relate to clinical response is needed to identify which patients are most likely to benefit from this treatment. In the current study, we sought to determine if baseline neurophysiology, specifically cortical excitation and/or inhibition, is associated with antidepressant response to TBS. In two independent open-label clinical trials, youth (aged 16-24 years old) with MDD underwent bilateral dorsolateral prefrontal cortex (DLPFC) TBS treatment. Clinical trial one and two consisted of 10 and 20 daily sessions of bilateral DLPFC TBS, respectively. At baseline, single-pulse TMS combined with electroencephalography was used to assess the neurophysiology of 4 cortical sites: bilateral DLPFC and inferior parietal lobule. Measures of cortical excitation and inhibition were indexed by TMS-evoked potentials (i.e., P30, N45, P60, N100, and P200). Depression severity was measured before, during and after treatment completion using the Hamilton Rating Scale for Depression-17. In both clinical trials, the baseline left DLPFC N45 and P60, which are believed to reflect inhibitory and excitatory mechanisms respectively, were predictors of clinical response. Specifically, greater (i.e., more negative) N45 and smaller P60 baseline values were associated with greater treatment response to TBS. Accordingly, cortical excitation and inhibition circuitry of the left DLPFC may have value as a TBS treatment response biomarker for youth with MDD.Clinical trial 1 registration number: NCT02472470 (June 15, 2015).Clinical trial 2 registration number: NCT03708172 (October 17, 2018).

Conceptualizing healthy cognitive aging: the role of time and variability.

The interest in healthy cognitive aging (HCA) has increased substantially over the past decade. Researchers are interested in exploring how health can be promoted and cognitive decline mitigated when pathology is not present. Identifying the necessary strategies is crucial as the gradual accumulation of small declines can lead to negative effects on quality of life over time. However, the conceptualization of HCA is not agreed upon. In fact, authors often turn to the use of traditional pathology screeners in the context of HCA because of their clear threshold results and their wide use in the different fields. This leads to the assumption that individuals are either cognitively unhealthy and therefore may have some form of dementia or are dementia-free and cognitively healthy. We believe that this view is an overly simplistic approach to the understanding of the aging process. In this work, we explore how HCA has been defined and conceptualized within the different fields. We further discuss how time and variability are key concepts that are often missing when studying HCA and propose a definition that aims to unify the findings from the multidisciplinary research that studies HCA and simplify the translation of knowledge. Incorporating these two novel dimensions to the study of HCA has already been proposed methodologically but has yet been discussed at the conceptual level. We believe that the proposed new approach will allow the identification of individual factors that cause changes in cognitive health and will help build new cognitive health strategies and mitigate further declines.

Atypical Associations between Functional Connectivity during Pragmatic and Semantic Language Processing and Cognitive Abilities in Children with Autism.

Autism Spectrum Disorder (ASD) is characterized by both atypical functional brain connectivity and cognitive challenges across multiple cognitive domains. The relationship between task-dependent brain connectivity and cognitive abilities, however, remains poorly understood. In this study, children with ASD and their typically developing (TD) peers engaged in semantic and pragmatic language tasks while their task-dependent brain connectivity was mapped and compared. A multivariate statistical approach revealed associations between connectivity and psychometric assessments of relevant cognitive abilities. While both groups exhibited brain-behavior correlations, the nature of these associations diverged, particularly in the directionality of overall correlations across various psychometric categories. Specifically, greater disparities in functional connectivity between the groups were linked to larger differences in Autism Questionnaire, BRIEF, MSCS, and SRS-2 scores but smaller differences in WASI, pragmatic language, and Theory of Mind scores. Our findings suggest that children with ASD utilize distinct neural communication patterns for language processing. Although networks recruited by children with ASD may appear less efficient than those typically engaged, they could serve as compensatory mechanisms for potential disruptions in conventional brain networks.

Neuroimaging and machine learning for studying the pathways from mild cognitive impairment to alzheimer's disease: a systematic review.

BACKGROUND: This systematic review synthesizes the most recent neuroimaging procedures and machine learning approaches for the prediction of conversion from mild cognitive impairment to Alzheimer's disease dementia. METHODS: We systematically searched PubMed, SCOPUS, and Web of Science databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) systematic review guidelines. RESULTS: Our search returned 2572 articles, 56 of which met the criteria for inclusion in the final selection. The multimodality framework and deep learning techniques showed potential for predicting the conversion of MCI to AD dementia. CONCLUSION: Findings of this systematic review identified that the possibility of using neuroimaging data processed by advanced learning algorithms is promising for the prediction of AD progression. We also provided a detailed description of the challenges that researchers are faced along with future research directions. The protocol has been registered in the International Prospective Register of Systematic Reviews- CRD42019133402 and published in the Systematic Reviews journal.

A new acquisition protocol for conducting studies with children: The science camp research experience.

In the last 50 years, the study of brain development has brought major discoveries to education and medicine, changing the lives of millions of children and families. However, collecting behavioral and neurophysiological data from children has specific challenges, such as high rates of data loss and participant dropout. We have developed a science camp method to collect data from children using the benefits of positive peer interactions and interactive and engaging activities, to allow researchers to better collect data repeatedly and reliably from groups of children. A key advantage of this approach is that by increasing participant engagement, attention is also increased, thereby increasing data quality, reducing data loss, and lowering attrition rates. This protocol describes the step-by-step procedure for facilitation of a science camp, including behavioral, electrophysiological, and participatory engagement activities. As this method is robust but also flexible, we anticipate that it can also be applied to different demographics and research needs.

The frontoparietal multiple demand network interacts with the dual pathways in auditory working memory.

The frontoparietal multiple demand (MD) network has been proposed as a control network that regulates processing demands while enabling goal-directed actions. This study tested the MD network account in auditory working memory (AWM) and identified its functional role and relationship with the dual pathways model in AWM, where segregation of function was based on the sound domain. Forty-one healthy young adults performed an n-back task consisting of an orthogonal combination of the sound domain (spatial versus nonspatial) and cognitive operation (low load versus high load). Functional connectivity and correlation analyses were performed to assess the connectivity of the MD network and the dual pathways. Our results confirmed the contribution of the MD network to AWM and identified its interactions with the dual pathways in both sound domains and during high and low load levels. At high loads, the strength of connectivity with the MD network correlated with task accuracy, indicating the key role of the MD network in supporting successful performance as cognitive load increases. This study contributed to the auditory literature by showing that both the MD network and dual pathways collaborate with each other to support AWM, and neither of them alone is adequate to explain auditory cognition.

Does cognitive aging follow an orchid and dandelion phenomenon?

Cognitive reserve reflects the brain's intrinsic adaptive capacity against the neurodegenerative effects of aging. The maintenance or enhancement of the brain's cognitive reserve plays a crucial role in mitigating the severity of pathologies associated with aging. A new movement, social prescribing, which focuses on prescribing lifestyle activities as a treatment for patients, is growing in popularity as a solution against aging pathologies. However, few studies have demonstrated a clear impact of lifestyle activities on individual cognitive health, outside of floor and ceiling effects. Understanding who benefits from which lifestyle factors remains unclear. Here, we investigated the potential effects of lifestyle activities on individuals' cognitive health from more than 3,530 older adults using a stratification method and advanced analysis technique. Our stratification methods allowed us to observe a new result: older adults who had relatively average cognitive scores were not impacted by lifestyle factors. By comparison, older adults with very high or very low cognitive scores were highly impacted by lifestyle factors. These findings expand the orchid and dandelion theory to the aging field, regarding the biological sensitivity of individuals to harmful and protective environmental effects. Our discoveries demonstrate the role of individual differences in the aging process and its importance for social prescribing programs.

Music and Visual Art Training Increase Auditory-Evoked Theta Oscillations in Older Adults.

Music training was shown to induce changes in auditory processing in older adults. However, most findings stem from correlational studies and fewer examine long-term sustainable benefits. Moreover, research shows small and variable changes in auditory event-related potential (ERP) amplitudes and/or latencies in older adults. Conventional time domain analysis methods, however, are susceptible to latency jitter in evoked responses and may miss important information of brain processing. Here, we used time-frequency analyses to examine training-related changes in auditory-evoked oscillatory activity in healthy older adults (N = 50) assigned to a music training (n = 16), visual art training (n = 17), or a no-treatment control (n = 17) group. All three groups were presented with oddball auditory paradigms with synthesized piano tones or vowels during the acquisition of high-density EEG. Neurophysiological measures were collected at three-time points: pre-training, post-training, and at a three-month follow-up. Training programs were administered for 12-weeks. Increased theta power was found pre and post- training for the music (p = 0.010) and visual art group (p = 0.010) as compared to controls (p = 0.776) and maintained at the three-month follow-up. Results showed training-related plasticity on auditory processing in aging adults. Neuroplastic changes were maintained three months post-training, suggesting music and visual art programs yield lasting benefits that might facilitate encoding, retention, and memory retrieval.

Digital interventions for depression and anxiety in older adults: a systematic review of randomised controlled trials.

One in five older adults experience symptoms of depression and anxiety. Digital mental health interventions are promising in their ability to provide researchers, mental health professionals, clinicians, and patients with personalised tools for assessing their behaviour and seeking consultation, treatment, and peer support. This systematic review looks at existing randomised controlled trial studies on digital mental health interventions for older adults. Four factors have been found that contributed to the success of digital mental health interventions: (1) ease of use; (2) opportunities for social interactions; (3) having human support; and (4) having the digital mental health interventions tailored to the participants' needs. The findings also resulted in methodological considerations for future randomised controlled trials on digital mental health interventions: (1) having a healthy control group and an intervention group with clinical diagnoses of mental illness; (2) collecting data on the support given throughout the duration of the interventions; (3) obtaining qualitative and quantitative data to measure the success of the interventions; and (4) conducting follow-up interviews and surveys up to 1 year post-intervention to determine the long-term outcomes. The factors that were identified in this systematic review can provide future digital mental health interventions researchers, health professionals, clinicians, and patients with the tools to design, develop, and use successful interventions for older users.

The Challenges Toward Real-world Implementation of Digital Health Design Approaches: Narrative Review.

BACKGROUND: Digital health represents an important strategy in the future of health care delivery. Over the past decade, mobile health has accelerated the agency of health care users. Despite prevailing excitement about the potential of digital health, questions remain on efficacy, uptake, usability, and patient outcome. This challenge is confounded by 2 industries, digital and health, which have vastly different approaches to research, design, testing, and implementation. In this regard, there is a need to examine prevailing design approaches, weigh their benefits and challenges toward implementation, and recommend a path forward that synthesizes the needs of this complex stakeholder group. OBJECTIVE: In this review, we aimed to study prominent digital health intervention design approaches that mediate the digital health space. In doing so, we sought to examine the origins, perceived benefits, contrasting nuances, challenges, and typical use-case scenarios of each methodology. METHODS: A narrative review of digital health design approaches was performed between September 2020 and April 2021 by referencing keywords such as "digital health design," "mHealth design," "e-Health design," "agile health," and "agile healthcare." The studies selected after screening were those that discussed the design and implementation of digital health design approaches. A total of 120 studies were selected for full-text review, of which 62 (51.6%) were selected for inclusion in this review. RESULTS: A review identifying the 5 overarching digital health design approaches was compiled: user-centered design, person-based design, human-centered design, patient-centered design, and patient-led design. The findings were synthesized in a narrative structure discussing the origins, advantages, disadvantages, challenges, and potential use-case scenarios. CONCLUSIONS: Digital health is experiencing the growing pains of rapid expansion. Currently, numerous design approaches are being implemented to harmonize the needs of a complex stakeholder group. Whether the end user is positioned as a person, patient, or user, the challenge to synthesize the constraints and affordances of both digital design and health care, built equally around user satisfaction and clinical efficacy, remains paramount. Further research that works toward a transdisciplinarity in digital health may help break down friction in this field. Until digital health is viewed as a hybridized industry with unique requirements rather than one with competing interests, the nuances that each design approach posits will be difficult to realize in a real-world context. We encourage the collaboration of digital and health experts within hybrid design teams, through all stages of intervention design, to create a better digital health culture and design ethos.

Music training modulates theta brain oscillations associated with response suppression.

There is growing interest in developing training programs to mitigate cognitive decline associated with normal aging. Here, we assessed the effect of 3-month music and visual art training programs on the oscillatory brain activity of older adults using a partially randomized intervention design. High-density electroencephalography (EEG) was measured during the pre- and post-training sessions while participants completed a visual GoNoGo task. Time-frequency representations were calculated in regions of interest encompassing the visual, parietal, and prefrontal cortices. Before training, NoGo trials generated greater theta power than Go trials from 300 to 500 ms post-stimulus in mid-central and frontal brain areas. Theta power indexing response suppression was significantly reduced after music training. There was no significant difference between pre- and post-test for the visual art or the control group. The effect of music training on theta power indexing response suppression was associated with reduced functional connectivity between prefrontal, visual, and auditory regions. These results suggest that theta power indexes executive control mechanisms in older adults. Music training affects theta power and functional connectivity associated with response suppression. These findings contribute to a better understanding of inhibitory control ability in older adults and the neuroplastic effects of music interventions.

Children with autism spectrum disorder show atypical electroencephalographic response to processing contextual incongruencies.

Children with autism spectrum disorder (ASD) experience difficulties with social communication, making it challenging to interpret contextual information that aids in accurately interpreting language. To investigate how the brain processes the contextual information and how this is different in ASD, we compared event-related potentials (ERPs) in response to processing visual and auditory congruent and incongruent information. Two groups of children participated in the study: 37 typically developing children and 15 children with ASD (age range = 6 to 12). We applied a language task involving auditory sentences describing congruent or incongruent images. We investigated two ERP components associated with language processing: the N400 and P600. Our results showed how children with ASD present significant differences in their neural responses in comparison with the TD group, even when their reaction times and correct trials are not significantly different from the TD group.

Healthy memory aging - the benefits of regular daily activities increase with age.

As the number of older adults increases, so does the pressure on health care systems due to age-related disorders. Attempts to reduce cognitive decline have focused on individual interventions such as exercise or diet, with limited success. This study adopted a different approach by investigating the impact of combined daily activities on memory decline. We used data from the National Institute of Aging's Health and Retirement Study to explore two new questions: does combining activities affect memory decline, and if yes, does this impact change across the lifespan? We created a new machine learning model using 33 daily activities and involving 3210 participants. Our results showed that the effect of combined activities on memory decline was stronger than any individual activity's impact. Moreover, this effect increased with age, whereas the importance of historical factors such as education, and baseline memory decreased. The present findings point out the importance of selecting multiple, diverse activities for older adults as they age. These results could have a significant impact on aging health policies promoting new programs such as social prescribing.

Moderate-Intensity Physical Activity, Music and Art Activities Preserved Cognitive Health in Older Adults: An Argument for Social Prescribing Solution.

Introduction: Rates of dementia are projected to increase over the coming years as global populations age. Without a treatment to slow the progression of dementia, many health policies are focusing on preventing dementia by slowing the rate of cognitive decline with age. However, it is unclear which lifestyle changes in old age meaningfully reduce the rate of cognitive decline associated with aging. Objectives: Use existing, multi-year longitudinal health data to determine if engagement in a variety of different lifestyle activities can slow the rate of cognitive decline as older adults age. Method: Data from the English Longitudinal Study of Aging was analyzed using a quasi-experimental, efficient matched-pair design inspired by the clinical trial methodology. Changes in short-term memory scores were assessed over a multi-year interval for groups who undertook one of 11 different lifestyle activities, compared to control groups matched across confounding socioeconomic and lifestyle factors. Results: Two factors, moderate-intensity physical activity and learning activities, resulted in significant positive impact on cognitive function. Conclusion: Our analysis brings cognitive benefit arguments in favor of two lifestyle activities, moderate-intensity physical activity and learning activities, while rejecting other factors advanced by the literature such as vigorous-intensity physical activity. Those findings justify and encourage the development of new lifestyle health programs by health authorities and bring forward the new health system solution, social prescribing.

Examining Challenges to the Incorporation of End Users in the Design of Digital Health Interventions: Protocol for a Systematic Review.

BACKGROUND: The process of designing a digital health intervention (DHI)-also referred to as mobile health or eHealth-spans needs assessments, technical functionality and feasibility, user satisfaction, effectiveness, impact, and value. These interventions are causing a rapid evolution in the landscape of health care. Multiple studies have shown their propensity to extend both the quality and reach of interventions. However, failure to improve DHI design is linked to failed uptake and health outcomes. This dilemma is further conflicted by the colliding backdrops of the digital and health industries, both of which approach, understand, and involve end users differently in the framing of a DHI. OBJECTIVE: The objective of this systematic review is to assess the challenges to incorporating end users in the design stage of digital health interventions, to identify key pain points, and to identify limitations and gaps for areas of future investigation. METHODS: The PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols) checklist will be used to structure this protocol. A systematic search of the PsycINFO, PubMed (MEDLINE), Web of Science, CINAHL, Scopus, and IEEE Xplore databases will be conducted. Additionally, the PerSPEcTiF guidelines for complex interventions will be consulted. Two reviewers will independently screen the titles and abstracts of the identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. Two reviewers will independently extract and validate data from the included studies into a standardized form and conduct quality appraisal. RESULTS: As of February 2021, we have completed a preliminary literature search examining challenges to the incorporation of end users in the design stage of DHIs. Systematic searches, data extraction and analysis, and writing of the systematic review are expected to be completed by December 2021. CONCLUSIONS: This systematic review aims to provide an effective summary of key pain points toward incorporating end users in DHIs. Results from this review will provide an evidence base for a better approach to end user involvement in the interest of improving efficacy and uptake of DHIs. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42021238164; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=238164. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/28083.

A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT.

This project aimed to develop and evaluate a fast and fully-automated deep-learning method applying convolutional neural networks with deep supervision (CNN-DS) for accurate hematoma segmentation and volume quantification in computed tomography (CT) scans. Non-contrast whole-head CT scans of 55 patients with hemorrhagic stroke were used. Individual scans were standardized to 64 axial slices of 128 × 128 voxels. Each voxel was annotated independently by experienced raters, generating a binary label of hematoma versus normal brain tissue based on majority voting. The dataset was split randomly into training (n = 45) and testing (n = 10) subsets. A CNN-DS model was built applying the training data and examined using the testing data. Performance of the CNN-DS solution was compared with three previously established methods. The CNN-DS achieved a Dice coefficient score of 0.84 ± 0.06 and recall of 0.83 ± 0.07, higher than patch-wise U-Net (< 0.76). CNN-DS average running time of 0.74 ± 0.07 s was faster than PItcHPERFeCT (> 1412 s) and slice-based U-Net (> 12 s). Comparable interrater agreement rates were observed between "method-human" vs. "human-human" (Cohen's kappa coefficients > 0.82). The fully automated CNN-DS approach demonstrated expert-level accuracy in fast segmentation and quantification of hematoma, substantially improving over previous methods. Further research is warranted to test the CNN-DS solution as a software tool in clinical settings for effective stroke management.

Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer's disease: protocol for a rapid systematic review.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder commonly associated with deficits of cognition and changes in behavior. Mild cognitive impairment (MCI) is the prodromal stage of AD that is defined by slight cognitive decline. Not all with MCI progress to AD dementia. Thus, the accurate prediction of progression to Alzheimer's, particularly in the stage of MCI could potentially offer developing treatments to delay or prevent the transition process. The objective of the present study is to investigate the most recent neuroimaging procedures in the domain of prediction of transition from MCI to AD dementia for clinical applications and to systematically discuss the machine learning techniques used for the prediction of MCI conversion. METHODS: Electronic databases including PubMed, SCOPUS, and Web of Science will be searched from January 1, 2017, to the date of search commencement to provide a rapid review of the most recent studies that have investigated the prediction of conversion from MCI to Alzheimer's using neuroimaging modalities in randomized trial or observational studies. Two reviewers will screen full texts of included papers using predefined eligibility criteria. Studies will be included if addressed research on AD dementia and MCI, explained the results in a way that would be able to report the performance measures such as the accuracy, sensitivity, and specificity. Only studies addressed Alzheimer's type of dementia and its early-stage MCI using neuroimaging modalities will be included. We will exclude other forms of dementia such as vascular dementia, frontotemporal dementia, and Parkinson's disease. The risk of bias in individual studies will be appraised using an appropriate tool. If feasible, we will conduct a random effects meta-analysis. Sensitivity analyses will be conducted to explore the potential sources of heterogeneity. DISCUSSION: The information gathered in our study will establish the extent of the evidence underlying the prediction of conversion to AD dementia from its early stage and will provide a rigorous and updated synthesis of neuroimaging modalities allied with the data analysis techniques used to measure the brain changes during the conversion process. SYSTEMATIC REVIEW REGISTRATION: PROSPERO,CRD42019133402.

Increased Intra-Subject Variability of Reaction Times and Single-Trial Event-Related Potential Components in Children With Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is an increasingly common neurodevelopmental disorder that affects 1 in 59 children. The cognitive profiles of individuals with ASD are varied, and the neurophysiological underpinnings of these developmental difficulties are unclear. While many studies have focused on overall group differences in the amplitude or latency of event related potential (ERP) responses, recent research suggests that increased intra-subject neural variability may also be a reliable indicator of atypical brain function in ASD. This study aimed to identify behavioral and neural variability responses during an emotional inhibitory control task in children with ASD compared to typically developing (TD) children. Children with ASD showed increased variability in response to both inhibitory and emotional stimuli, evidenced by greater reaction time variability and single-trial ERP variability of N200 and N170 amplitudes and/or latencies compared to TD children. These results suggest that the physiological basis of ASD may be more accurately explained by increased intra-subject variability, in addition to characteristic increases or decreases in the amplitude or latency of neural responses. Autism Res 2020, 13:221-229. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The cognitive functions including memory, attention, executive functions, and perception, of individuals with ASD are varied, and the physiological underpinnings of these profiles are unclear. In this study, children with ASD showed increased intra-subject neural and behavioral variability in response to an emotional inhibitory control task compared to typically developing children. These results suggest that the physiological basis of ASD may also be explained by increased behavioral and neural variability in people with ASD, rather than simply characteristic increases or decreases in averaged brain responses.