Otto-von-Guericke University Magdeburg

Background The lack of attention to Chronic Hand Eczema (CHE) and the lack of a specific International Classification of Diseases code for CHE may have limited the assessment of CHE prevalence. To date, prevalence estimates have primarily been derived from (partly small) single-country studies. Objectives To estimate the annual prevalence of self-reported physician-diagnosed CHE across socio-demographic characteristics among adults in Canada, France, Germany, Italy, Spain, and the United Kingdom (UK). Methods In this observational Chronic Hand Eczema epidemiology, Care, and Knowledge of real-life burden (CHECK) study, a questionnaire was administered to adults between 18 and 69 years old in the general population, recruited through online panels. Quotas and minor weighting adjustments were performed to ensure that the participants were representative of the general population regarding sex, age, region, employment status, urban/rural setting, and, in the UK only, ethnicity. Additional weights were applied to account for population size differences when aggregating country results. Information on self-reported physician-diagnosed CHE was collected. CHE was defined, in accordance with the European Society of Contact Dermatitis, as having hand eczema continuously for three months or more or at least two flares in the past 12 months. CHE annual prevalence with 95% confidence intervals (CIs) was determined for each country, and by subgroups of sex, age, employment, and urban/rural. Results Among 60,131 participants, 2,847 self-reported physician-diagnosed CHE, yielding an annual prevalence of 4.7% (CI: 4.6-4.9). Subgroup analyses revealed the CHE prevalence was significantly higher in females than males (5.6% [5.4-5.9] vs. 3.8% [3.6-4.1]; P<0.001), in employed versus unemployed participants (5.3% [5.1-5.6] vs. 3.3% [3.1-3.6]; P<0.001), and in urban versus rural residents (5.0% [4.8-5.2] vs. 3.7% [3.4-4.1]; P<0.001). The prevalence was highest among those aged 30-39 years (6.5% [6.0-7.0]) and lowest in those aged 60-69 years (2.6% [2.3-3.0]). Conclusions This large multi-national study is the first to assess CHE prevalence in Europe and Canada using a consistent definition across a broad geographical population. This study reveals that CHE is a common skin disease with annual prevalence of 4.7%, with higher prevalence among females, individuals aged 30-39, those employed, and those living in urban areas.

The collapse of an initially spherical cavitation bubble near a free surface leads to the formation of two jets: a downward jet into the liquid, and an upward jet penetrating the free surface. In this study, we examine the surprising interaction of a bubble trapped in a stable cavitating vortex ring approaching a free surface. As a result, a single fast and tall liquid jet forms. We find that this jet is observed only above critical Froude numbers (Fr) and Weber numbers (We) when Fr 2 (1.6 − 2.73/We) > 1, illustrating the importance of inertia, gravity and surface tension in accelerating this novel jet and thereby reaching heights several hundred times the radius of the vortex ring. Our experimental results are supported by numerical simulations, revealing that the underlying mechanism driving the vortex ring acceleration is the disruption of the equilibrium of high-pressure regions at the front and rear of the vortex ring caused by the free surface. Quantitative analysis based on the energy relationships elucidates that the velocity ratio between the maximum velocity of the free-surface jet and the translational velocity of the vortex ring is relatively stable yet is attenuated by surface tension when the jet is mild.

Background Environmental factors account for a considerable percentage of dementia cases. Studies in animal models have shown that environmental enrichment (EE; i.e., stimuli‐rich housing conditions) has positive effects on brain structure, including the memory system. In humans, EE as measured by the engagement in a variety of leisure activities has been associated with better fornix structure and memory (Klimecki et al., 2023). We assessed whether long‐term EE (in terms of engagement in diverse leisure activities) is related to functional brain activity in the memory system of older adults. Methods We operationalized individual EE in 372 older participants aged between 60 and 87 years of the DZNE Longitudinal Study on Cognitive Impairment and Dementia (DELCODE) study. We used subscales of the Lifetime of Experiences Questionnaire (LEQ; Valenzuela & Sachdev, 2007) that capture the frequency of engagement in diverse leisure activities in young adulthood and middle life (13‐30 and 30‐65 years). Memory‐related brain activity was assessed using individual FADE‐SAME scores in a functional magnetic resonance imaging (fMRI) paradigm on visual memory encoding and recognition. The scores capture the similarity of older adults’ brain activity patterns with typical activations of younger adults’ (Soch et al., 2021). We performed multiple regression analyses between long‐term EE as independent variable and FADE‐SAME scores related to novelty processing and subsequent memory as dependent variables. Result Long‐term EE was significantly associated with novelty‐based SAME scores. More specifically, older participants with higher EE in early and middle life showed a higher similarity of functional brain activity patterns during novelty processing with the patterns seen in younger adults (see Figure 1). Exploratory subgroup analysis showed that this association was predominantly found in participants with Subjective Cognitive Decline (SCD, n = 199). No other significant findings were obtained. Conclusion Engagement in a variety of leisure activities during early and middle life is related to more “youth‐like” memory‐related brain activity patterns in older adults, including older individuals at increased risk of AD. Higher EE during early life might contribute to preservation or promotion of memory functions in later life.

Background Training studies report beneficial effects of physical (PP) on cognitive performance (COG) in older adults, but are often accompanied by potentially biased parameters, conclusions, and lack of directionality. To address these issues, we used a dynamic Bayesian approach to analyse the dynamic session‐to‐session change and coupling of PP and COG over time. Methods We used two studies (N = 17 each): Study 1 contained 24‐weeks (72 sessions) of training of older adults with suspected Alzheimer’s disease (AD). Study 2 included four months (40 sessions) of training of older adults at metabolic risk. The hierarchical Bayesian continuous‐time dynamic modeling approach (R package ctsem) comprised: (i) A subject‐level latent dynamic model, (ii) subject‐level measurement model, and (iii) population model. The dynamic model was specified with two fully connected state variables enabling bidirectional coupling between PP and COG using default priors and starting values (4 chains and 8.000 iterations). Intercept and drift parameters were set to vary freely. Population and individual level parameters are estimated simultaneously using all data from all subjects. Second‐level models included MMSE, SF12 (physical health questionnaire) in study 1 and whole hippocampal volumes (wHCV: T2‐ASHS, longitudinal) and white matter hyperintensities (SAMSEG, longitudinal) in study 2 as time independent covariates. Results Study 1: Higher PP was dynamically linked to COG (‐1.335, 95%‐BCI [‐1.725, ‐0.954]). The effect was short‐term, lasting up to five days (‐0.368, 95%‐BCI [‐0.479, ‐0.266]). Study 2: PP improved COG in subsequent sessions (‐1.11, 95%‐BCI[‐1.22, ‐0.99]), which lasted for up to 15 days. Higher wHCV was associated with a stronger coupling‐effect of PP on COG (‐0.15, 95%‐BCI[‐0.18, ‐0.11] ) and lower persistence of COG (‐0.145, 95%‐BCI[‐0.21, ‐0.08]). Discussion Our results show immediate exercise‐induced improvements in COG, with a longer‐lasting effect for participants at metabolic risk compared to older adults with suspected AD. Despite impaired cognitive performance, the cognitive system was still able to fluctuate and change favorably. Physical exercise seems to mobilize capacities that would otherwise remain unused. Utilizing a Bayesian approach to examine time‐locked effects can provide insights for implementing individualized training approaches and guiding clinical decision‐making.

Background The posterior‐medial network is crucial for episodic memory. However, the medial temporal lobe (MTL) and posteromedial cortex (PMC) regions are vulnerable to aging and early Alzheimer’s disease (AD). Both processes might elicit distinct early functional connectivity (FC) changes which could be detrimental or protective/ compensatory regarding cognition. However, this is not well understood. We hypothesized that resting‐state FC strength between key regions (Figure 1a) would decrease with age and memory decline without AD pathology (A‐T‐) but increase with early AD pathology. Method We analysed longitudinal 3‐Tesla resting‐state fMRI data from cognitively unimpaired older adults (OA; PREVENT‐AD cohort). We assessed FC at baseline and after 24 months (FU24) in i) CSF or PET Aß‐ and tau‐negative OA (A‐T‐, N = 96, 63±5years, 70 female, 28 APOE4) and ii) Aß and p‐tau CSF‐characterized OA with available longitudinal p‐tau181/Aß1‐42 ratio (N = 65, 63±5years, 45 female, 22 APOE4). First, we investigated effects of age, APOE genotype and p‐tau181/Aß1‐42 ratio on FC controlling for sex and education. Second, we tested the association between baseline FC or change in FC and change in delayed memory recall in multiple regression analyses. Result In A‐T‐ OA, FC decreased mainly between regions within the PMC subnetwork over 24 months (Figure 1b). Higher baseline FCwithin‐PMC was related to increasing memory performance over time (p = 0.047; Figure 2a). Longitudinally, increasing FCMTL‐mPFC was associated with increasing memory in APOE4 non‐carriers and decreasing memory in APOE4 carriers (p = 0.016; Figure 2b). In CSF‐characterized OA, p‐tau181/Aß1‐42 ratio at baseline and FU24 was related to increasing FCMTL‐PMC over time (Figure 3a). Higher baseline FCMTL‐PMC was associated with longitudinally increasing memory in APOE4 non‐carriers and decreasing memory in APOE4 carriers (p = 0.028; Figure 3b). Conclusion Our results provide novel longitudinal evidence incorporating age, APOE, Aß and tau indicating specific memory‐related FC changes in cognitively unimpaired OA. APOE moderated the effects of FC strength on change in episodic memory performance. Higher FCMTL‐PMC and increasing FCMTL‐mPFC seem to be detrimental in APOE4 carriers but beneficial in APOE4 non‐carriers. Importantly, this effect was observed in A‐T‐ OA, hinting that APOE genotype may affect FC earlier than AD‐related pathology.

Background Memory clinic patients are a heterogeneous population representing various aetiologies of pathological aging. It is unknown if divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer’s disease (AD) patients, are prevalent and clinically meaningful in this group of older adults. Method To uncover atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to structural MRI data from 813 participants (mean ± SD age = 70.67 ± 6.07 years, 52% females) from the DELCODE cohort. Participants were cognitively unimpaired (CU; n = 285) or patients with subjective cognitive decline (SCD; n = 342), mild cognitive impairment (MCI; n = 118), or dementia of the Alzheimer’s type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid AD biomarkers, and domain‐specific cognitive performance. PACC‐5 trajectories over up to 240 weeks were examined. Clinical trajectories (PACC‐5 scores and MCI conversion rates) in only CU and SCD participants were analysed. SuStaIn modelling was repeated in participants from the Swedish BioFINDER‐2 study for replication and generalizability testing. Result Limbic‐predominant and hippocampal‐sparing atrophy subtypes were identified (Figure 1). Limbic‐predominant atrophy first affected the medial temporal lobes, followed by further temporal and, finally, the remaining cortical regions. This subtype was related to older age, more pathological AD biomarkers, APOE e4 carriership, and an amnestic cognitive impairment. Hippocampal‐sparing atrophy initially occurred outside the temporal lobe and spared the medial temporal lobe until advanced stages. This atrophy pattern also affected individuals with positive AD biomarkers and was associated with more generalised cognitive impairment. Limbic‐predominant atrophy, in all and in only unimpaired participants, was linked to more negative longitudinal PACC‐5 slopes than observed in participants without or with hippocampal‐sparing atrophy (Figure 2) and increased the risk of MCI conversion. In BioFINDER‐2, analogous atrophy subtypes and cognitive correlates were identified. Group‐ and subject‐level model generalizability were excellent, indicating reliable performance in novel data (Figure 3). Conclusion The proposed model is a promising tool for capturing heterogeneity among older adults at early at‐risk states for AD in applied settings. The implementation of atrophy subtype‐ and stage‐specific end‐points may increase the statistical power of pharmacological trials targeting early AD.

Background While some memory decline in old age is “normal”, there are some older individuals with maintained high cognitive performance. Using a multimodal approach including neuroimaging, fitness, genetic and questionnaire data (Fig1A), we aimed to identify factors that are related to successful cognitive aging and whether these differ between sexes. Method We analyzed 165 cognitively normal older adults age = 60 years from an ongoing study (SFB1436) (age = 71±8years, 43% female). For all participants, we determined plasma Abeta1‐42/Abeta1‐40. Temporal lobe tau burden was estimated by [18F]PI‐2620 in a subsample (see Fig.1A for sample sizes). We assessed global white matter hyperintensity (WMH) volumes and gray matter thickness for medial temporal lobe (MTL), anterior cingulate cortex (ACC) and whole brain. We measured aerobic and muscular capacity (and blood pressure) by fitness assessment and trait/state anxiety by self‐reports. Genetic profiling included KLOTHO and KIBRA polymorphisms and APOE genotype. To phenotype successful cognitive aging, we i) grouped individuals age = 79.5 years into SuperAgers (N = 18) based on delayed verbal recall performance = normative values at age of 50‐60 years versus typical agers (N = 19). For the whole sample we ii) calculated cognitive age gap (CAG) as the difference between cognition‐predicted age and chronological age (Fig.3A). We assessed how markers of pathology, brain structure, fitness, mental health and genetics were related to CAG, covarying for chronological age, sex and education. Result SuperAgers and typical agers did not differ in age, sex, education, fitness, anxiety or Abeta42/40 (all p‐values>0.1). However, SuperAgers had less WMH volume, higher ACC thickness, lower blood pressure and less temporal lobe tau‐tracer binding (small subgroup;). In the whole sample, younger cognitive age related to higher MTL and global cortical thickness, less temporal tau‐tracer binding, less anxiety (all p<0.05; Figure 3B) and marginally to higher muscular capacity (p = .06). Only the association between anxiety measures and CAG was moderated by sex (Fig.3B). CAG was not related to genotype. Conclusion Our results suggest that successful cognitive aging is related to resistance against age‐related pathology and higher brain integrity. Younger cognitive age is linked to better mental health, especially in females.

Background Differences in task‐fMRI activation have recently been found to be related to neuropathological hallmarks of AD. However, the evolution of fMRI‐based activation throughout AD disease progression and its relationship with other biomarkers remains elusive. Applying a disease progression model (DPM) to a multicentric cohort with up to four annual task‐fMRI visits, we hope to provide a deeper insight into these relationships. Method We estimated AD disease stages using a multivariate Gaussian Process (GP) DPM including CSF‐Aß42/40 ratio, CSF‐p‐tau181, hippocampal and entorhinal volume, ADAS13‐Cog sum and PACC5 scores. Disease stages from 493 participants with longitudinal task‐fMRI measurements from DELCODE (165 healthy controls (CN), 214 participants with SCD, 82 with MCI, 32 with suspected AD) were obtained. We derived subsequent memory and novelty contrasts from a visual memory encoding task using general linear modeling (GLM). Contrasts from all available follow‐ups were then submitted to voxel‐based group‐level GLM analyses. Activations from resulting disease‐stage‐related clusters were (1) used to estimate cluster‐level trajectory curves over disease stages using smoothing splines and (2) submitted to linear‐mixed effects models to test longitudinal changes over follow‐ups. Result Our DPM‐derived disease stages were associated with clinical groups, fMRI performance and white matter lesions (Figure 1C‐F). Generally, in both contrasts, activation increases were observed in task‐negative clusters while activation decreases were observed in task‐positive clusters (Figure 2C‐F). We did not find indications for inverted u‐shaped associations between disease stage and activation in whole brain voxel‐wise cross‐sectional analyses. However, smoothing splines revealed non‐linear monotonically increasing biomarker abnormality for task‐negative areas, showing earliest changes towards the beginning of disease progression. After a plateau, fMRI activation increases in abnormality conjointly with volume changes. For task‐positive areas, we observed linear relationships with disease stages (Figure 3). Activation changes over follow‐ups were not associated with disease stages. Conclusion Biomarker abnormality timing in our DPM reflected hypothetical AD progression. Changes in task‐fMRI activation and deactivation were both associated with progression towards AD. Smoothing spline fits indicated abnormality changes in task‐fMRI activation to begin in the earliest phases of the disease. Findings can be discussed as differential pathophysiological processes such as complex reorganization and neural noise.

Background Previous studies have examined the impact of post‐traumatic stress disorder and chronic stress on the Locus Coeruleus‐Noradrenergic System (LC‐NA) revealing significant neurobiological alterations (Aston‐Jones & Cohen, 2005; McCall et al., 2015). However, while animal studies have yielded valuable insights regarding the effects of traumatic experiences on the LC‐NA system, translation to human models remains relatively underexplored. Thus, our study aims to address this gap by investigating the relationship between traumatic experiences and LC‐NA integrity in human participants. Here, we present preliminary results on the association between traumatic events, resilience, and LC integrity. Method We recruited 90 healthy older adults (mean age: 68.17 ± 5.36) from the SFB‐1436 Cohort. We acquired neuromelanin‐sensitive 3T MRI scans using a Magnetization Transfer Contrast (MTC) sequence optimized for enhancing the visibility of the LC. We performed LC segmentation using an automated approach (based on Dünnwald et al., 2021) and assessed traumatic experiences using a self‐reported modified version of the Life Events Checklist for DSM‐5 (LEC‐5; Weathers et al., 2013). We conducted a linear regression analysis to examine whether traumatic experiences could predict LC integrity. Result A linear regression analysis was carried out to assess if traumatic events, age, and sex could predict LC integrity in healthy older adults. The results suggest a trend towards significance for individuals reporting Low traumatic events (p = 0.059) and Highly traumatic events (p = 0.082), indicating potential positive relationships with LC integrity, while controlling for age and sex. The overall model explained a small, non‐significant proportion of the variance in LC integrity (Adjusted R‐squared = 0.028, p = 0.1927). Conclusion The analysis indicates a potential association between LC integrity and traumatic events, particularly for low and high levels of trauma. However, the overall model including traumatic events, age, and sex did not explain a significant proportion of interindividual differences in LC integrity. This suggests that while there may be trends indicating associations, they are not robust enough to be considered statistically significant in this sample. Further mediational and moderational analyses will be conducted to gain a deeper understanding of interindividual differences in this regard.

Background Memory decline, which is especially prevalent in Alzheimer’s disease (AD), has been studied via fMRI, primarily focusing on the prefrontal cortex and hippocampus. However, emerging evidence suggests that the brainstem, alongside various midbrain regions, is an initial target for pathological processes like hyperphosphorylated TAU protein accumulation. Among these, the locus coeruleus, a noradrenergic nucleus in the pons, projects to critical midbrain areas supporting memory encoding. Hence, our study aimed to investigate BOLD task activations in AD relevant to memory, while focusing on differences in responses to emotional versus neutral stimuli in the brainstem and midbrain. Method Using event‐related fMRI, 53 subjects (28 healthy older adults, 25 with mild cognitive impairment (MCI)) (see table 1) underwent an incidental recognition memory task involving emotional and neutral images. Memory tests followed immediately, and 4 hours after encoding. Group differences in brain activations for remembered versus not remembered images using the study template were examined. Result Results revealed a trend for greater activation in the left caudate nucleus in older adults, compared to those with MCI, when subsequently remembered items were compared with not remembered ones (small volume correction (SVC), cluster level pFWE‐corr = 0.08). Similarly, a significant increased activation was observed in the locus coeruleus (SVC, cluster level pFWE‐corr = 0.018). However, after adjusting for group and individual differences in LC integrity and global grey matter volume (GMV), no significant differences persisted, suggesting that structural changes contribute significantly to differences in LC activation between healthy controls and MCI participants (see Figures 1 and 2). Conclusion In conclusion, our findings underscore the caudate nucleus’s role in memory encoding for healthy older adults versus those with MCI. A decline in LC function in MCI appears related to a decline in LC integrity. These insights contribute to understanding memory mechanisms in healthy aging versus MCI. Future studies are needed to explore potential neural memory compensatory processes in MCI.

Background Alzheimer’s Disease (AD), a progressively worsening neurodegenerative disorder, impacts millions globally. Understanding its progression is crucial for developing effective interventions and management strategies. However, high variability in disease progression amongst individuals and the complexity of neuroimaging data pose significant challenges. Current diagnostic methods often fail to capture the nuanced progression, leading to delayed interventions, and lack uncertainty estimates, necessary for reliable decision‐making (Schaar et al., 2022). To address these issues, we here propose a Structural MRI‐Based AD Score (SMAS) using a Bayesian supervised Variational Autoencoder (Bayesian sVAE). The approach captures distinct morphometrical brain patterns associated to cognitive impairment across stages of AD. The score and model has potential to support personalized treatment plans and improve the efficacy of diagnostic tools. Method We used 415 and 200 longitudinal MRI scans from DELCODE (Jessen et al., 2018;) and ADNI (Salvatore et al., 2018), respectively. We focused on features computed from T1‐w images using CAT12 longitudinal pipeline (Gaser et al., 2022). The Bayesian sVAE model (Fig. 1) consists of an encoder network that learns to map brain features into a lower‐dimensional embedding space. Moreover, a predictive block predicts memory performance based on the latent mapping, and a decoder block that reconstructs the original input images from the latent space. We trained the sVAE on baseline DELCODE cohort with the expectation that the model will capture brain signatures characterizing aging and progression towards AD. We then assessed its generalization ability on follow‐up data and on ADNI. Result The Bayesian sVAE model, trained on sMRI features, shows potential for a parsimonous anatomy‐based characterization of individual disease progression. The model’s capacity to differentiate among various clinical groups using a single score (SMAS), and its correlations with key clinical and demographic variables, suggest its potential for identifying structural brain related to progression (Fig. 2). Using longitudinal test data, the model‐based latent scores indicated expected group differences and changes (Fig. 3). Conclusion The Bayesian sVAE model has shown promise in continuously monitoring atrophy over stages of AD progression. We provide indications for generalizability to unseen data (ADNI), suggesting robustness across different imaging protocols and scanners, and considerable stability over repeated measures.

Background Inadequate glymphatic clearance through perivascular spaces (PVS) is hypothesized to contribute to the formation of white matter hyperintensities (WMH). However, longitudinal evidence for such a mechanistic link in aging remains limited. Using multivariate modelling, we investigated the interrelationship between PVS and WMH over time to elucidate potential cascades of early cerebrovascular alterations and tested whether AD‐biomarkers and inflammatory markers associated with vascular disease can explain individual variability in their occurrence and progression. Methods We quantified PVS and WMH using T1w MPRAGE and T2w FLAIR imaging of 439 cognitively unimpaired participants from the DELCODE study (52.85% females; meanage = 69.88±5.72), who underwent annual scans over a four‐year period and attended at least three visits (n observations = 1790; meannumber of visits = 4.08±0.79). We employed latent growth curve modelling to assess reciprocal connections between PVS and WMH, focusing on their initial volumes (latent intercepts) and their rates of change over four years (latent slopes). We used log10‐transformed total PVS and WMH volumes, and controlled for age, sex, years of education, total cardiovascular risk score, and total intracranial volume. We then derived interindividual latent factor scores and tested their relation to CSF‐derived AD‐biomarkers (Aβ42/40, pTau181; available for n = 195; z‐scored) and inflammatory markers (CRP, IL‐6; available for n = 125; Box‐Cox‐transformed) via Spearman’s correlation (FDR‐corrected). Results The model showed good model fit (CFI = 0.997; RMSEA = 0.021; SRMR = 0.017; Fig. 1A). WMH and PVS volumes increased over time (interceptWMH‐slope = 0.068, SE = 0.004, Z = 16.490, p<0.001; interceptPVS‐slope = 0.036, SE = 0.007, Z = 4.927, p<0.001; Fig. 1B). Participants with higher baseline PVS volumes not only had higher baseline WMH volumes (covariancePVS‐intercept&WMH‐intercept = 0.120, SE = 0.040, Z = 2.936, p = 0.003; Fig. 1C) but also tended to exhibit faster WMH volume increase over time (covariancePVS‐intercept&WMH‐slope = 0.007, SE = 0.004, Z = 1.796, p = 0.072; Fig. 1C). In this sample of cognitively unimpaired participants, biomarkers of AD and inflammation did neither relate to individual baseline differences nor progression rates (Table 1). Conclusion Our findings are consistent with the notion that PVS dysfunction might contribute to and precede WMH progression (Fig. 1D). However, the individual variability requires further investigation to elucidate mechanisms driving PVS dysfunction in the first place. Unraveling the interrelationships and further factors contributing to cerebrovascular alterations will be crucial to understand pathological cascades in aging that could inform targeted treatment strategies.

Background Episodic memory declines in old age. Successful memory relies on the process of mnemonic discrimination (MD) to establish distinct representations. However, the scope for improvement in older adults’ cognitive performance using cognitive training is poorly understood. Here we investigated whether cognitive training leads to improvement in MD and whether the benefits transfer across different stimulus types, tasks and cognitive functions Method 112 older adults (age M = 67.96, SD = 3.86) completed an 8‐week web‐based MD training intervention divided into 3 groups: one group training with object stimuli (OG), one group training with scene stimuli (SG), one active control group. The training was based on the object‐scene MD task which involves differentiating similar objects and scenes (‘lures’; correct response: ‘new’) from repeated items ('repeats’, correct response: ‘old’). Stimuli were first presented in a 2‐back set‐size: the first two stimuli were new images, while each of the subsequent two could be either a lure or a repeat trial. Then set‐size increased progressively across the training. Pre‐ and post‐training, the subjects performed a behavioral session including the 2‐back object‐scene MD task and several other transfer tasks. The latter included the mnemonic similarity task (MST; i.e. a different MD task), a pattern completion, working memory, spatial learning, and navigation task. Result Our results show a training‐induced improvement in the object‐scene MD task performance but not the MST. We found a bias‐corrected performance improvement (d prime) driven by the correct lures. Compared to the control group, the OG improved their MD performance in objects while the SG improved in scenes, but only the OG showed near transfer improvement to the non‐trained category (i.e. scenes). We found no significant training effect in other transfer tasks. Conclusion An 8‐week cognitive training intervention led to MD improvement in the trained task. We found a same modality improvement with the OG improving in objects and the SG in scenes, and evidence of near transfer from object to scenes but not vice versa. Cognitive training can lead to MD improvement in older adults. Longer‐duration interventions are needed to assess far‐transfer effects.

Background The Locus Coeruleus (LC) is prominently affected by neuronal loss in the earliest stages of Alzheimer’s disease (AD). Assessing LC integrity can serve as an important early biomarker for assessing AD progression. Neuromelanin (NM) accumulates in LC neurons and NM imaging has therefore been proposed as a means of imaging the LC. As signal intensity is taken as a proxy for cell density, a quantitative imaging approach of the LC, which is less variable across sites and time is desirable. The present study used a multi‐parameter mapping (MPM) protocol optimized for LC imaging to compare weighted and quantitative maps in healthy younger, healthy older adults and individuals with AD. Methods Structural MRI data was acquired in a group of 26 healthy young adults, 26 healthy older adults and 26 individuals with Alzheimer’s disease. Three sets of T1‐weighted, MT‐weighted, and PD‐weighted images yielded quantitative maps (R1, MTsat, PD, and R2*) in each individual within one scan session. Qualitative and quantitative methods were used to assess weighted and quantitative maps for LC imaging across groups. Results Qualitatively, LC visibility was higher in weighted images. The LC was also apparent in R1 maps, but less clearly visible in MTsat and R2* maps (Figure 1). LC contrast ratio (with pons as reference), was reduced in Alzheimer’s disease compared to younger adults as detected by MTw scans (p = .001) and to older adults as detected by T1w (p<.001), MTw (p<.001), and PDw scans (p = .007). No group differences were detected in quantitative maps, suggesting less sensitivity to pick up typical LC integrity reductions. PD maps could not be reliably estimated in the modified setup of the MPMs. Conclusion Although among the quantitative maps LC was most visible in R1 images, our findings indicate that R1 maps capture the LC signal intensity less well as compared to non‐quantitative LC imaging, as suggested by a qualitative assessment of LC visibility and inability to detect known group differences. Further research should improve sensitivity of quantitative maps for LC assessment by combining sequences capturing different aspects of LC tissue properties.

Background Locus coeruleus (LC) is a primary source of noradrenalin in the brain and plays a complex role in human behavior. In healthy aging and Alzheimer’s disease (AD), LC cell loss has been linked to a decline in overall cognitive function. This study aimed to explore age‐ and AD‐related differences in a proxy measure of LC activity. Using pupil dilation (PD) as a non‐exclusive proxy measure of the LC‐NE system activity, we examined whether pupillometric recordings during cognitive tasks are possible in early AD and whether they reveal differences in attentional modulation in aging and AD. Method 37 subjects (14 healthy OA and 23 individuals with AD) completed an auditory and visual oddball task to assess attentional modulation; 62 subjects (22 healthy YA, 20 healthy OA, and 20 individuals with AD) completed a Simon task to assess attention and cognitive control. LC integrity was assessed using neuromelanin‐sensitive MRI. Result A larger PD response for oddball compared to standard stimuli was observed, with no difference between OA and AD participants. In the visual task, greater PD correlated with faster reaction times (RTs) for hits in both groups, indicating the interindividual differences in PD can reflect heightened attentional involvement in aging and AD. Similarly, a consistent Simon effect, i.e., lower accuracy and longer RTs for incongruent trials, was observed in all groups, suggesting cognitive effort in discriminating between congruences. PD was higher for incongruent than congruent trials across all age groups, yet YA exhibited a less pronounced Simon effect, indicating age‐related differences in attentional resource allocation with a potentially larger need in OA and AD for attentional control on incongruent stimuli. In YA, slower RTs correlated with smaller PD in incongruent trials. YA and AD individuals with a stronger Simon effect in PD showed faster processing for incongruent trials and better performance for congruent trials, respectively. Conclusion Using PD as a measure of attentional allocation and effort during cognitive control is possible in AD. Moreover, it allows for the assessment of interindividual differences in the extent of attentional modulation in AD. Assessing PD could be a useful tool for distinguishing between healthy aging and early AD.

Background Non‐pharmacological interventions that improve cognitive functioning in patients with Alzheimer’s disease will play a crucial role in the coming years to support their independence in daily living. Here, we investigated the potential of a novel smartphone‐assisted real‐world wayfinding training, tailored for older adults, to improve their spatial memory as one of the first cognitive functions affected by the disease. Spatial memory performance was assessed using a VR‐based navigation task and the Gardony map drawing analyzer. Method To date, eight cognitively healthy older adults (65‐73 years) completed the wayfinding training on the medical campus area in Magdeburg, Germany, using our smartphone application “Explore” (Figure 1). In two egocentric sessions, participants had to walk repeatedly from a fixed start location to a target location and back. In four allocentric sessions, participants had to walk to several target locations consecutively by planning a route (four routes per session). All target locations were shown on a map in the app at the beginning of a track, which disappeared during walking but could be re‐opened. The app recorded GPS data and the number of map views. Potential changes in spatial memory were assessed by means of a pointing task in a virtual campus version before and after the training and by comparing the accuracy in the computerized map drawing after each session. Result A linear mixed‐effect model analysis confirmed a significant training effect on pointing errors, while controlling for pre‐training familiarity, p < .001 (Figure 2). Map drawing accuracy improved over the course of the training, p < .001 (Figure 3a), while the number of map views during walking in allocentric sessions decreased, p = .021 (Figure 3b). Conclusion We provide first evidence that a remotely administered real‐world wayfinding training might be able to improve spatial memory in older adults. As a next step, data will be collected in more participants with some of them assigned to a walking‐only control group. (f)MRI data, measured during the virtual pointing task, and biomarker status will be analyzed to investigate the mechanisms of the training effects and to determine the applicability as dementia intervention.

Background The timely diagnosis of mild cognitive impairment (MCI) in Alzheimer’s disease is challenging in routine care due to the complexity and time burden of required cognitive assessments. New unsupervised digital remote assessment tools could adress this challenge. Method The multicentric healthcare study “re.cogni.ze” evaluated usability, adherence and acceptance of remote digital assessment (neotivCare, installed on private smartphone) over a period of 22 months with 27 specialist physicians (neurologists and psychiatrists), 13 GPs and 3 memory clinics in Germany. Result 765 persons with subjectively perceived memory problems were recommended neotivCare by their doctors. 574 patients (75%) followed the recommendation (mean age 67 ‐ SD 10; 50.2% female). 573 (93%) used the app at home (one visual memory test per week over a period 12 weeks). 496 patients (93%) completed the assessment and discussed the results using the in‐app generated findings letter with their doctor. Of these, 368 patients also completed a separate (independent from the app) survey about usability, difficulty, worries, experienced added value etc. 40% of the patients fell below the prevalidated cut‐off for MCI in the app‐tests. Specialists reported a higher satisfaction with the app compared to standard paper‐pencil tests (5.2 versus 4.4 on a 7 point Likert scale). There was no such difference for GPs. 71% of all doctors found that the app easy to use. 80% saw an added value in using the app. 71.5% of the patients thought that the app was easy to use. 67.6% reported an added value over paper pencil tests. Using the app reduced experienced worries in 51% of the patients and left worries unchanged in 29%. The patients rated the duration of the app‐use and the self‐testing at home favourably (both 8.5 scores on a Likert scale 0 ‐10). Conclusion The topline results of the re.cog.nize study show that remote digital self‐assessment in routine care is feasible and is accepted by health care providers and patients. The high adherence rates indicate that a timely assessment of MCI is possible with this type of digital technology.

Background Mnemonic discrimination tasks (MDTs) hold potential for early detection of memory changes in Alzheimer’s disease (AD). Object and scene processing tasks differently tap into memory networks vulnerable to early tau and amyloid pathology, respectively. We used an object and scene MDT to assess longitudinal effects of AD on distinct functional memory networks and investigate their potential as markers for different disease stages. Method 202 participants from the DELCODE study completed an object and scene MDT of highly similar objects and scenes during fMRI scanning each year from baseline to 36‐month follow‐up. Participants were classified as cognitively unimpaired (CU; Table 1) or having subjective cognitive decline (SCD), mild cognitive impairment (MCI), or dementia of the Alzheimer’s type (DAT). Result The combined MCI/DAT group showed object and scene mnemonic discrimination impairment. SCDs only differed from CUs on scenes, but trended towards object discrimination decline over follow‐up. Cross‐sectionally, amygdala, BA35/36, anterior hippocampus, and parahippocampal cortex showed increased activity during successful discrimination of both scenes and objects. Entorhinal cortex, posterior hippocampus, and precuneus did so only for scenes, dovetailing with the framework of partially dissociable memory networks. Longitudinally, CUs showed increasing brain activity during object but not scene memory throughout the medial temporal lobe. SCDs showed a pattern of longitudinally increasing activity during scene memory coupled with decreasing activity during object memory in BA35, BA36, and hippocampus. Strikingly, the opposite was true for BA35 and entorhinal cortex in the MCI/DAT group. Conclusion These results provide a first glimpse at longitudinal changes in brain activity during mnemonic discrimination throughout the AD continuum. Both neural and behavioural indices of the MDT may be sensitive to longitudinal disease effects. Future analyses will assess the complex relationship between disease effects on neurodegeneration, neural activity, and memory to better understand how early AD erodes memory and brain systems.

Background Analysis of neuroimaging data based on convolutional neural networks (CNNs) can improve detection of clinically relevant characteristics of patients with Alzheimer’s disease (AD). Previously, our group developed a CNN‐based approach for detecting AD via magnetic resonance imaging (MRI) scans and for identifying features that are relevant to the decision of the network. In the current study, we aimed to evaluate the potential utility of applying this approach to MRI scans to assist in the identification of individuals at high risk for amyloid positivity to aid in the selection of study samples and case finding for treatment. Method In the current analysis, we have trained a CNN to detect amyloid positivity using MRI scans from 1461 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants (498 cognitively normal participants, 103 participants with significant memory concern, 640 participants with mild cognitive impairment, and 220 participants with AD dementia). Amyloid positivity was assessed via amyloid PET scans obtained with [¹⁸F]florbetapir or [¹⁸F]florbetaben and quantified on a Centiloid scale. A threshold of 24.1 CL categorized 46% of participants as amyloid‐positive. The modeling approach was evaluated using 10‐fold cross‐validation, the number of epochs in training was set to 10. Result For each of 10 cross‐validation folds, we selected a model state corresponding to an epoch showing best performance in the validation partition. Balanced accuracy across these models ranged from 0.62 to 0.72 with an average of 0.68 (SD = 0.03). Conclusion We used a previously established approach to train CNNs for detecting amyloid positivity using MRI scans. Such models, particularly when tuned to have low rates of false negatives, have a potential to enhance identification of patients who would benefit from more in‐depth assessments, which could then inform antibody treatment. We are conducting ongoing work to improve and characterize the modeling approach, including evaluation of relevance maps which indicate importance of brain regions for detecting amyloid positivity. Future work will evaluate the role of amyloid positivity threshold selection. Planned analyses also include validation in independent data such as the German DZNE ‐ Longitudinal Cognitive Impairment and Dementia Study (DELCODE) dataset.

Background Late‐life depression (LLD) is a risk factor for Alzheimer's disease (AD) dementia. Previous morphological studies have often associated LLD with atrophy within the medial temporal lobe (MTL), including the hippocampus. A number of previous studies have demonstrated the changes in several MTL subfields in LLD, such as the perirhinal cortex (PrC), cornu ammonis (CA), dentate gyrus (DG), subiculum and entorhinal cortex (EC), but with inconsistent results, which may be explained by the relatively low image resolution of the 3T scanner used in the previous studies. Method A total of 93 individuals over the age of 60 were included in this study, of which 23 LLD patients and 29 normal controls without a history of depression underwent T1 and T2tse scans on a 7‐Tesla MRI scanner. Images were pre‐processed and roughly segmented into CA1‐3, DG, SUB, EC, and PrC (area 35, 36) using the Automated Segmentation Hippocampal Subfields (ASHS) and further separated into anterior and posterior (head and body). All segmented images were manually edited. Group comparisons of MTL subfield volumes were made, adjusting for age, sex, and years of education. Cognitive and clinical scores were correlated with the volume of each subfield. Result LLD and controls did not differ in total hippocampal volume. LLD showed reduced volume in the head portion of the right DG (p=0.05) and a trend towards reduced ratio between left and right EC (p=0.07). No other group differences were observed. Correlational analyses revealed a significant association between bilateral hippocampal volume and TMT‐A speed, as well as the anxiety subscale of the Geriatric Depression Scale (GDS). Subfield analyses revealed significant associations between the anxiety subscale of the GDS and bilateral DG head volume (left: r=‐0.36, p=0.006; right: r=‐0.42, p=0.002) and between the left CA1 body and the cognition subscale of the GDS (r=0.29, p=0.03). Conclusion Using ultra‐high field MRI, we demonstrated an anterior‐posterior differentiation along the hippocampal long axis in the involvement of cognitive and clinical symptoms in LLD. Future work should investigate the relationship between AD pathological changes and behavioral symptoms in LLD and whether MTL subfields may play a mediating role.