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.

Age-associated proteins explain the role of medial temporal lobe networks in Alzheimer's disease.

The structural connectivity (SC) of the medial temporal lobe and its associated cortical anterior temporal and posterior medial networks (MTL-AT-PM) is linked to pathologies and memory decline in Alzheimer's disease (AD). However, neuroimaging analyses cannot tell us how SC changes occur in AD at the molecular level and do not provide a means of intervening to slow/prevent pathology-related changes in MTL-AT-PM SC. The current study aimed to understand how and where AD-related changes occur within MTL-AT-PM using proteomics. We used a 4-step approach in 101 older adults from a local sample, aiming to understand how proteins and SC in combination at the multivariate level predict AD pathology, and to identify specific proteins related to SC and AD pathology. Separately, we validated the discovered proteins in relation to SC and AD pathology using ADNI sample. We identified 12 latent factors linking proteins and SC; five showed significant relationships with AD pathology and/or episodic memory. Insulin-like growth factor binding proteins and tumor necrosis factor receptors, and hippocampal/parahippocampal edges contributed most to AD-related latent factors. Fast causal inference found protein-protein, protein-SC, and protein-pathology pathways, with seven proteins showing directional links to SC and AD-related neurodegeneration. We validated these results by identifying significant relationships between six available proteins with SC and amyloid-beta and phosphorylated tau in ADNI. We identified multivariate relationships between proteins and MTL-AT-PM networks that add to our understanding of AD pathology and suggest specific non-pathological proteins that warrant further study in relation to brain networks and AD pathology as possible therapeutic targets.

Risk-Taking Behavior Differs Between Older Adults with and without Mild Cognitive Impairment.

Background: Adequately evaluating risk and making decisions is vital but understudied for older adults living independently but with compromised cognition, as seen in those with mild cognitive impairment (MCI), specifically those with amnestic MCI (aMCI) which is associated with higher risk of conversion to Alzheimer's disease. Objective: We propose to comprehensively evaluate risk-taking behaviors across domains important for everyday activities between an aMCI group and their cognitively healthy counterparts (HC). Methods: A case-control study design. Data on risk-taking behaviors via the Domain-Specific Risk-Taking Scale (DOSPERT), and candidate confounding mental health factors (i.e., neurodegeneration, depression, and fatigue) were collected. Analyses on group difference and interaction between group and confounding factors on risk-taking behaviors were conducted. Results: The aMCI group showed a higher likelihood of risk-taking than HC (t = 4.38, df = 73, p < 0.001). Moderation analysis showed fatigue (F = 5.91, p = 0.018) and presence of depression (F = 4.52, p = 0.037), but not neurodegeneration, as significant moderators for group and DOSPERT total score, controlling for sex. In post-hoc analyses, there was a significant relationship between both fatigue (B = -7.83, SE = 3.65, t = -2.14, p = 0.036), and presence of depression (B = -20.80, SE = 9.97, t = -2.09, p = 0.041), with DOSPERT total score for HC but not for aMCI. There were no significant relationships between neurodegeneration, fatigue, or depression with any specific risk-taking domains after correction for multiple comparisons. Conclusions: Our results show differences in risk-taking behavior between older adults with and without intact cognition, and overall decision-making is affected by fatigue and depression in HC but not aMCI, together suggesting the importance of cognition in the ability to adjust risk-taking behaviors.

Positive affect disrupts neurodegeneration effects on cognitive training plasticity in older adults.

Cognitive training for older adults varies in efficacy, but it is unclear why some older adults benefit more than others. Positive affective experience (PAE), referring to high positive valence and/or stable arousal states across everyday scenarios, and associated functional networks can protect plasticity mechanisms against Alzheimer's disease neurodegeneration, which may contribute to training outcome variability. The objective of this study is to investigate whether PAE explains variability in cognitive training outcomes by disrupting the adverse effect of neurodegeneration on plasticity. The study's design is a secondary analysis of a randomized control trial of cognitive training with concurrent real or sham brain stimulation (39 older adults with mild cognitive impairment; mean age, 71). Moderation analyses, with change in episodic memory or executive function as the outcome, PAE or baseline resting-state connectivity as the moderator and baseline neurodegeneration as the predictor are the methods used in the study. The result of the study is that PAE stability and baseline default mode network (DMN) connectivity disrupted the effect of neurodegeneration on plasticity in executive function but not episodic memory. The study concludes that PAE stability and degree of DMN integrity both explained cognitive training outcome variability, by reducing the adverse effect of neurodegeneration on cognitive plasticity. We highlight the need to account for PAE, brain aging factors and their interactions with plasticity in cognitive training.

Experience sampling reveals the role that covert goal states play in task-relevant behavior.

Cognitive neuroscience has gained insight into covert states using experience sampling. Traditionally, this approach has focused on off-task states. However, task-relevant states are also maintained via covert processes. Our study examined whether experience sampling can also provide insights into covert goal-relevant states that support task performance. To address this question, we developed a neural state space, using dimensions of brain function variation, that allows neural correlates of overt and covert states to be examined in a common analytic space. We use this to describe brain activity during task performance, its relation to covert states identified via experience sampling, and links between individual variation in overt and covert states and task performance. Our study established deliberate task focus was linked to faster target detection, and brain states underlying this experience-and target detection-were associated with activity patterns emphasizing the fronto-parietal network. In contrast, brain states underlying off-task experiences-and vigilance periods-were linked to activity patterns emphasizing the default mode network. Our study shows experience sampling can not only describe covert states that are unrelated to the task at hand, but can also be used to highlight the role fronto-parietal regions play in the maintenance of covert task-relevant states.

Improving comparability across cognitive training trials for brain aging: A focus on interoperability.

Cognitive training may promote healthy brain aging and prevent dementia, but results from individual studies are inconsistent. There are disagreements on how to evaluate cognitive training interventions between clinical and basic scientists. Individual labs typically create their own assessment and training materials, leading to difficulties reproducing methods. Here, we advocate for improved interoperability: the exchange and cooperative development of a consensus for cognitive training design, analysis, and result interpretation. We outline five guiding principles for improving interoperability: (i) design interoperability, developing standard design and analysis models; (ii) material interoperability, promoting sharing of materials; (iii) interoperability incentives; (iv) privacy and security norms, ensuring adherence to accepted ethical standards; and (v) interpretability prioritization, encouraging a shared focus on neurobiological mechanisms to improve clinical relevance. Improving interoperability will allow us to develop scientifically optimized, clinically useful cognitive training programs to slow/prevent brain aging. HIGHLIGHTS: Interoperability facilitates progress via resource sharing and comparability.Better interoperability is needed in cognitive training for brain aging research.We adapt an interoperability framework to cognitive training research.We suggest five guiding principles for improved interoperability.We propose an open-source pipeline to facilitate interoperability.

Patterns of ongoing thought in the real world.

Health and well-being are impacted by our thoughts and the things we do. In the laboratory, studies suggest specific task contexts impact thought processes. More broadly, this suggests the people we are with, the places we are in, and the activities we perform may influence our thought patterns. In our study, participants completed experience sampling surveys for five days in daily life. Principal component analysis decomposed this data to identify common "patterns of thought," and linear mixed modelling related these patterns to the participants' activities. Our study replicated the influence of socializing on patterns of thought and established that this is part of a broader set of relationships linking activities to how thoughts are organized in daily life. Our study suggests sampling thinking in the real world may help map thoughts to activities, and these "thought-activity" mappings could be useful to researchers and health care professionals interested in health and well-being.

Influence of affective states on informant impression of neuropsychiatric symptoms in people living with MCI.

Objectives: Alzheimer's disease (AD) and mild cognitive impairment (MCI) are often accompanied by neuropsychiatric symptoms (NPS; e.g. depression/apathy/irritability) causing challenges for people living with dementia/caregivers and predicting worse disease progression. Accurately assessing NPS is critical to research on AD/MCI. However, there are limitations to both self-reports and clinician evaluations; the field often relies on informants to assess NPS. Informants' perception of NPS are influenced by disease and caregiver factors that may lead to biased assessments. We aimed to assess the relationship between participants self-reported affective states (valence/arousal) and informant-reported NPS.Methods: Data from a double-blinded intervention design (primarily testing neurostimulation's effect on NPS) were used to examine the relationship between participant-reported affective states and informant-reported NPS over 1 month. Forty participants (24 females) with MCI and NPS (mean age = 71.7, SD = 7) were enrolled along with informants (primarily spouses/partners) who regularly interact with participants. NPS assessment occurred weekly and at pre- and post-intervention, and participant-reported affective states were assessed at 14 timepoints.Results: Generalized Estimating Equations showed that participant levels of arousal, but not valence, were significantly related to corresponding informant-reported NPS at weekly (arousal: B= -0.59, SE = 0.27, Wald's χ2 = 4.61, p=.032; valence: B = 0.17, SE = 0.19, Wald's χ2 = 0.80, p=.37) and pre-/post- (arousal: B= -4.00, SE = 1.58, Wald's χ2 = 6.42, p=.011; valence: B= -3.34, SE = 1.80, Wald's χ2 = 3.43, p=.06) assessments.Conclusion: The findings indicate that informant-reported NPS may be more strongly influenced by arousal, and informants may be less attuned to valence in people living with MCI.

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 (ß = 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 (ß = 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 (ß = 0.36, SE = 0.136, CI = [0.023, 0.574], p = 0.037), but not inhibition task RMSSD data (ß = 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.

Effect of online tDCS to left somatomotor cortex on neuropsychiatric symptoms among older adults at risk for dementia.

BACKGROUND: Neuropsychiatric symptoms (NPS) in mild cognitive impairment (MCI) cause distress to patients and caregivers, and accelerate progression to dementia. Transcranial direct current stimulation (tDCS) is a promising non-invasive treatment for NPS. OBJECTIVE/HYPOTHESIS: This pilot study assessed behavioral and neural effects of a 4-week anodal tDCS intervention targeting left sensorimotor cortex (LSMC: left precentral/postcentral gyri) during visual attention (compared to online sham tDCS), in 40 older adults (24 females, mean age = 71) with MCI. METHODS: A phase 0 double-blinded randomized control trial was conducted. NPS (patient-reported mood symptoms plus a caregiver-reported questionnaire) and fMRI were measured at baseline and immediately post-intervention. RESULTS: Generalized Estimating Equations found no significant group by time interactions for either NPS measure. However, there was evidence of decreased patient-reported NPS (Wald's χ2 = 3.80, p = .051), decreased LSMC activation during visual attention (Wald's χ2 = 2.93, p = .087), and increased LSMC-amygdala resting-state functional connectivity (rsFC; Wald's χ2 = 3.13, p = .077) in intervention group from pre-to post-intervention. Decrease in LSMC activation (Wald's χ2 = 9.20, p = .002) and increase in LSMC-amygdala rsFC (Wald's χ2 = 4.72, p = .030) related to decreased patient-reported NPS. Increased positive valence across sessions was significantly associated with intervention-related NPS improvement (Wald's χ2 = 22.92, p < .001). There were no findings for caregiver-reported NPS. Effects were stronger for left postcentral compared to left precentral gyrus. CONCLUSION: We found tentative evidence that tDCS applied to LSMC during visual attention in older adults with MCI improved NPS via changes in LSMC activation and LSMC-amygdala rsFC, suggesting improved emotion regulation. Patient-reported NPS was more sensitive to these changes than caregiver-reports, and effects were strongest for left postcentral gyrus. Follow-up studies should perform precise mechanistic investigation and efficacy testing.

Brain imaging studies of emotional well-being: a scoping review.

This scoping review provides an overview of previous empirical studies that used brain imaging techniques to investigate the neural correlates of emotional well-being (EWB). We compiled evidence on this topic into one accessible and usable document as a foundation for future research into the relationship between EWB and the brain. PRISMA 2020 guidelines were followed. We located relevant articles by searching five electronic databases with 95 studies meeting our inclusion criteria. We explored EWB measures, brain imaging modalities, research designs, populations studied, and approaches that are currently in use to characterize and understand EWB across the literature. Of the key concepts related to EWB, the vast majority of studies investigated positive affect and life satisfaction, followed by sense of meaning, goal pursuit, and quality of life. The majority of studies used functional MRI, followed by EEG and event-related potential-based EEG to study the neural basis of EWB (predominantly experienced affect, affective perception, reward, and emotion regulation). It is notable that positive affect and life satisfaction have been studied significantly more often than the other three aspects of EWB (i.e., sense of meaning, goal pursuit, and quality of life). Our findings suggest that future studies should investigate EWB in more diverse samples, especially in children, individuals with clinical disorders, and individuals from various geographic locations. Future directions and theoretical implications are discussed, including the need for more longitudinal studies with ecologically valid measures that incorporate multi-level approaches allowing researchers to better investigate and evaluate the relationships among behavioral, environmental, and neural factors. Systematic review registration: https://osf.io/t9cf6/.

Unifying framework for cognitive training interventions in brain aging.

Cognitive training is a promising tool for slowing or preventing cognitive decline in older adults at-risk for dementia. Its success, however, has been limited by a lack of evidence showing that it reliably causes broad training effects: improvements in cognition across a range of domains that lead to real-world benefits. Here, we propose a framework for enhancing the effect of cognitive training interventions in brain aging. The focus is on (A) developing cognitive training task paradigms that are informed by population-level cognitive characteristics and pathophysiology, and (B) personalizing how these sets are presented to participants during training via feedback loops that aim to optimize "mismatch" between participant capacity and training demands using both adaptation and random variability. In this way, cognitive training can better alter whole-brain topology in a manner that supports broad training effects in the context of brain aging.

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.

Enhancing cortical network-level participation coefficient as a potential mechanism for transfer in cognitive training in aMCI.

Effective cognitive training must improve cognition beyond the trained domain (show a transfer effect) and be applicable to dementia-risk populations, e.g., amnesic mild cognitive impairment (aMCI). Theories suggest training should target processes that 1) show robust engagement, 2) are domain-general, and 3) reflect long-lasting changes in brain organization. Brain regions that connect to many different networks (i.e., show high participation coefficient; PC) are known to support integration. This capacity is 1) relatively preserved in aMCI, 2) required across a wide range of cognitive domains, and 3) trait-like. In 49 individuals with aMCI that completed a 6-week visual speed of processing training (VSOP) and 28 active controls, enhancement in PC was significantly more related to transfer to working memory at global and network levels in VSOP compared to controls, particularly in networks with many high-PC nodes. This suggests that enhancing brain integration may provide a target for developing effective cognitive training.

Brain Small-Worldness Properties and Perceived Fatigue in Mild Cognitive Impairment.

BACKGROUND: Perceived fatigue is among the most common complaints in older adults and is substantially influenced by diminished resources or impaired structure of widespread cortical and subcortical regions. Alzheimer's disease and its preclinical stage-mild cognitive impairment (MCI)-are considered a brain network disease. It is unknown, however, whether those with MCI will therefore perceive worse fatigue, and whether an impaired global brain network will worsen their experience of fatigue. METHODS: In this pilot case-control study of age-, sex-, and education-matched MCI and their cognitively healthy counterparts (HCs), perceived fatigue was measured using Multidimensional Fatigue Inventory, and diffusion tensor imaging tractography data were analyzed using graph theory methods to explore small-worldness properties: segregation and integration. RESULTS: Perceived fatigue was more severe in MCI than HCs. Despite a trend for greater network alterations in MCI, there were no significant group differences in integration or segregation. Greater perceived fatigue was related to higher segregation across groups; more perceived fatigue was related to higher segregation and lower integration in MCI but not HCs. CONCLUSION: Findings of this study support the notion that altered whole-brain small-worldness properties in brain aging or neurodegeneration may underpin perceived fatigue.

Age-related changes in ongoing thought relate to external context and individual cognition.

Understanding how age-related changes in cognition manifest in the real world is an important goal. One means of capturing these changes involves "experience sampling" participant's self-reported thoughts. Research has shown age-related changes in ongoing thought: e.g., older adults have fewer thoughts unrelated to the here-and-now. However, it is currently unclear how these changes reflect cognitive aging or lifestyle changes. 78 younger adults and 35 older adults rated their thought contents along 20 dimensions and the difficulty of their current activity in their daily lives. They also performed cognitive tasks in the laboratory. In a set of exploratory analyses, we found that older adults spent more time thinking positive, wanted thoughts, particularly in demanding contexts, and less time mind wandering about their future selves. Past-related thought related to episodic memory differently in older and younger adults. These findings inform the use of experience sampling to understand cognitive aging.

Exploring patterns of ongoing thought under naturalistic and conventional task-based conditions.

Previous research suggests that patterns of ongoing thought are heterogeneous, varying across situations and individuals. The current study investigated the influence of multiple tasks and affective style on ongoing patterns of thought. We used 9 different tasks and measured ongoing thought using multidimensional experience sampling. A Principal Component Analysis of the experience sampling data revealed four patterns of ongoing thought: episodic social cognition, unpleasant intrusive, concentration and self focus. Linear Mixed Modelling was used to conduct a series of exploratory analyses aimed at examining contextual distributions of these thought patterns. We found that different task contexts reliably evoke different thought patterns. Moreover, intrusive and negative thought pattern expression were influenced by individual affective style (depression level). The data establish the influence of task context and intrinsic features on ongoing thought, highlighting the importance of documenting how thought patterns emerge in cognitive tasks with different requirements.

Increased segregation of structural brain networks underpins enhanced broad cognitive abilities of cognitive training.

A major challenge in the cognitive training field is inducing broad, far-transfer training effects. Thus far, little is known about the neural mechanisms underlying broad training effects. Here, we tested a set of competitive hypotheses regarding the role of brain integration versus segregation underlying the broad training effect. We retrospectively analyzed data from a randomized controlled trial comparing neurocognitive effects of vision-based speed of processing training (VSOP) and an active control consisting of mental leisure activities (MLA) in older adults with MCI. We classified a subset of participants in the VSOP as learners, who showed improvement in executive function and episodic memory. The other participants in the VSOP (i.e., VSOP non-learners) and a subset of participants in the MLA (i.e., MLA non-learners) served as controls. Structural brain networks were constructed from diffusion tensor imaging. Clustering coefficients (CCs) and characteristic path lengths were computed as measures of segregation and integration, respectively. Learners showed significantly greater global CCs after intervention than controls. Nodal CCs were selectively enhanced in cingulate cortex, parietal regions, striatum, and thalamus. Among VSOP learners, those with more severe baseline neurodegeneration had greater improvement in segregation after training. Our findings suggest broad training effects are related to enhanced segregation in selective brain networks, providing insight into cognitive training related neuroplasticity.

The neural correlates of ongoing conscious thought.

A core goal in cognitive neuroscience is identifying the physical substrates of the patterns of thought that occupy our daily lives. Contemporary views suggest that the landscape of ongoing experience is heterogeneous and can be influenced by features of both the person and the context. This perspective piece considers recent work that explicitly accounts for both the heterogeneity of the experience and context dependence of patterns of ongoing thought. These studies reveal that systems linked to attention and control are important for organizing experience in response to changing environmental demands. These studies also establish a role of the default mode network beyond task-negative or purely episodic content, for example, implicating it in the level of vivid detail in experience in both task contexts and in spontaneous self-generated experiential states. Together, this work demonstrates that the landscape of ongoing thought is reflected in the activity of multiple neural systems, and it is important to distinguish between processes contributing to how the experience unfolds from those linked to how these experiences are regulated.

Longitudinal stability of medial temporal lobe connectivity is associated with tau-related memory decline.

The relationship between Alzheimer's disease (AD) pathology and cognitive decline is an important topic in the aging research field. Recent studies suggest that memory deficits are more susceptible to phosphorylated tau (Ptau) than amyloid-beta. However, little is known regarding the neurocognitive mechanisms linking Ptau and memory-related decline. Here, we extracted data from Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with cerebrospinal fluid (CSF) Ptau collected at baseline, diffusion tensor imaging measure twice, 2 year apart, and longitudinal memory data over 5 years. We defined three age- and education-matched groups: Ptau negative cognitively unimpaired, Ptau positive cognitively unimpaired, and Ptau positive individuals with mild cognitive impairment. We found the presence of CSF Ptau at baseline was related to a loss of structural stability in medial temporal lobe connectivity in a way that matched proposed disease progression, and this loss of stability in connections known to be important for memory moderated the relationship between Ptau accumulation and memory decline.