Biology subjects

Wiltfang, J.

Publications and source records attributed to Wiltfang, J..

17 recordsLinked to original sources

bioRxiv2026

Mesoscale medial temporal lobe connectivity patterns relate to tau pathology and memory in older adults

The medial temporal lobe (MTL) is crucial for episodic memory. Tau pathology is a hallmark of Alzheimer's disease (AD) and accumulates in layer-specific patterns in the MTL during aging. It is, however, unclear whether early AD pathology relates to mesoscale network signatures distinct from non-pathological aging. To address this gap, we acquired 7 Tesla submillimeter-resolution resting-state fMRI, plasma-based AD biomarkers, glial fibrillary acidic protein (GFAP) levels, APOE genotype, regional [18F]PI-2620 tau PET burden, and longitudinal episodic memory data in 75 cognitively unimpaired older adults. Older age was associated with lower perirhinal-hippocampal connectivity and lower network segregation, whereas higher plasma-based AD pathology was associated with higher perirhinal-hippocampal connectivity. Furthermore, temporal-lobe tau burden was related to altered connectivity patterns in tau-vulnerable MTL subfields and layers, dependent on GFAP levels. Retrosplenial tau burden was associated with higher hippocampal-retrosplenial connectivity consistent with tau spread along canonical hippocampal output pathways. Finally, higher connectivity within the hippocampus attenuated the negative association between temporal-lobe tau burden and memory performance but predicted unfavorable memory trajectories. Our findings show differential associations of age and AD pathology with mesoscale MTL-connectivity patterns. Importantly, increased hippocampal connectivity may support memory function in the short term while contributing to subsequent memory decline.

neuroscience↗

bioRxiv2026

Automated quantification of white matter hyperintensity confluence: A measure of spatial organisation beyond volume and visual rating scales

White matter hyperintensities (WMH) are a highly prevalent finding on FLAIR MRI scans and a prominent feature of white matter pathology across cerebrovascular and neurodegenerative diseases. Currently, WMH are assessed with visual rating scales such as the Fazekas scale or with their volume, as calculated from automatic or manual segmentations. Both methods have limitations: Visual rating scales are rater-dependent and coarse, while WMH volume does not take the confluence of lesions into account and thus disregards their spatial organisation. As an alternative, here we propose a novel automated method for quantifying the confluence of white matter hyperintensities on a continuous standardised scale between 0 and 1. The metric is based on WMH segmentations from routine MRI and quantifies the extent to which individual WMH merge into coherent lesions, independently of total lesion volume. We apply the method to QMIN-MC, a large UK memory clinic cohort, and show associations of the confluence metric with age, cognitive performance across domains, and Fazekas ratings. Participants with vascular and mixed dementia showed higher confluence than other diagnostic groups, whereas cognitively unimpaired participants showed lower confluence. However, confluence did not explain additional cognitive variance after accounting for log-transformed WMH volume. Findings were validated in DELCODE, an independent cohort of individuals with neurodegenerative disorders, replicating our original results. In this validation cohort, periventricular WMH confluence remained associated with cognition after adjustment for WMH volume. These findings introduce WMH confluence as a reproducible, automated, and fine-grained measure of lesion spatial organisation. It provides complementary information about morphological WMH severity beyond volume and is an alternative to visual rating scales. Although related to WMH volume in memory-clinic populations, confluence captures clinically interpretable information and may complement existing WMH measures for improved lesion characterisation in studies of white matter disease, ageing, and cognitive impairment.

neuroscience↗

bioRxiv2025

Disrupted Forward Connectivity in Parieto-temporal Network Impairs Memory Performance in Alzheimer's Disease

Alzheimers disease (AD) is characterised by the accumulation of beta-amyloid (A{beta}) and tau proteins, leading to neurodegeneration and cognitive decline. While A{beta} and tau are known to disrupt synaptic function, the mechanisms linking these molecular pathologies to network-level dysfunction and memory impairment remain poorly understood. Here we investigated the effects of A{beta} and tau pathology (CSF A{beta}42/40 ratio and tau phosphorylated at position 181, p-tau-181, respectively) on effective connectivity (EC) related to memory encoding, which may constitute a link between synaptic pathology and cognitive outcomes. Functional magnetic resonance imaging (fMRI) during visual memory encoding was acquired from participants of the multicentric DZNE Longitudinal Cognitive Impairment and Dementia Study (DELCODE), including 203 cognitively normal older participants (CN) as well as individuals with subjective cognitive decline (SCD; N = 204), mild cognitive impairment (MCI; N = 65), and early dementia due to AD (DAT; N = 21). EC was assessed by applying Dynamic causal modelling (DCM) to the fMRI data, using brain regions previously implicated in memory-encoding: the parahippocampal place area (PPA), the hippocampus (HC) and the precuneus (PCU). Disruptions in forward connectivity from the PPA to the HC and PCU were associated with both memory impairment and indices of AD pathology. Specifically, reduced excitatory EC from the PPA to the HC was associated with higher p-tau-181 levels and correlated with poorer memory performance. Diminished inhibitory EC from the PPA to the PCU was driven by both tau and amyloid pathology and was likewise linked to memory decline. Our findings suggest that disrupted forward connectivity within the temporo-parietal memory network constitutes a candidate mechanism mediating the relationship between molecular pathology and cognitive dysfunction.

neuroscience↗

bioRxiv2025

Disease Severity Across Psychiatric Disorders Is Linked to Pro-Inflammatory Cytokines

ImportanceNumerous studies indicate that the traditional categorical classification of severe mental disorders (SMD), such as schizophrenia, bipolar disorders, and major depressive disorders, does not align with the underlying biology of those disorders as they frequently overlap in terms of symptoms and risk factors. ObjectiveThis study aimed to identify transdiagnostic patient clusters based on disease severity and explore the underlying biological mechanisms independently of the traditional categorical classification. DesignWe utilized data from 443 participants diagnosed with SMD of the PsyCourse Study, a longitudinal study with deep phenotyping across up to four visits. We performed longitudinal clustering to group patients based on symptom trajectories and cognitive performance. The resulting clusters were compared on cross-sectional variables, including independent measures of severity as well as polygenic risk scores, serum protein quantification, miRNA expression, and DNA methylation. ResultsWe identified two distinct clusters of patients that exhibited marked differences in illness severity but did not differ significantly in age, sex, or diagnostic proportions. We found 19 serum proteins significantly dysregulated between the two clusters. Functional enrichment pointed to a convergence of immune system dysregulation and neurodevelopmental processes. ConclusionThe observed differences in serum protein expression suggest that disease severity is associated with the convergence of immune system dysregulation and neurodevelopmental alterations, particularly involving pathways related to inflammation and brain plasticity. The identification of pro-inflammatory proteins among the differentially expressed markers underscores the potential role of systemic inflammation in the pathophysiology of SMD. These results highlight the importance of considering illness severity as a core dimension in psychiatric research and clinical practice and suggest that targeting immune-related mechanisms may offer promising new therapeutic avenues for patients with SMD. Key points QuestionCan analyzing symptom trajectories and cognitive profiles across diagnostic categories reveal clinically relevant subgroups in severe mental disorders? FindingsIn this longitudinal study of 443 individuals with severe mental disorders, two distinct clusters emerged, differing significantly in illness severity, with the more severe group displaying elevated pro-inflammatory serum proteins, suggesting an association between disease severity and inflammation. MeaningThese findings suggest that transdiagnostic clustering clarifies shared mechanisms, underscores the importance of inflammation in severe mental disorders, and highlights a promising avenue for novel therapeutic approaches.

immunology↗

bioRxiv2025

Epitope Sequence and Modification Fingerprints of Anti-Aβ Antibodies

A hallmark of Alzheimers disease (AD), the most common form of dementia, is the progressive accumulation of amyloid-beta (A{beta}) peptides across distinct brain regions. Anti-A{beta} antibodies (A{beta}-Abs) targeting specific A{beta} variants are essential tools for AD research, diagnostics, and therapy. The monoclonal antibodies Aducanumab, Lecanemab, and Donanemab have recently been approved as the first disease-modifying treatments for early AD, highlighting the clinical importance of their exact binding profiles. In this study, we systematically characterized the binding and modification requirements of 20 A{beta}-Abs, including biosimilars of Aducanumab, Lecanemab, and Donanemab, across monomeric, oligomeric, and aggregated A{beta} forms. Array-based analysis of 20,000 modified A{beta} peptides defined binding epitopes at single-residue resolution and revealed the impact of sequence variation, including familial AD mutations, as well as diverse post-translational modifications (PTMs). Notably, genetic variants such as H6R impaired binding of therapeutic A{beta}-Abs like Aducanumab. Donanemab showed strong preference for pyroglutamate-modified A{beta}pE3-10, while Lecanemab and Aducanumab exhibited aggregation- and sequence-context-dependent binding requirements. Comparison of peptide binding profiles with binding of full-length and aggregated A{beta} via immunoprecipitation-mass spectrometry, capillary immunoassays, Western blotting, and immunohistochemistry on AD brain tissue revealed distinct aggregation-dependent binding behaviours. The valency- and context-dependence of Aducanumab binding, together with its preference for Ser8-phosphorylated A{beta}, supports a dimerization-mediated binding mechanism. For Lecanemab, our data suggest that additional structural contributions beyond the minimal N-terminal epitope are required for binding to aggregated A{beta}, which remain to be fully resolved. Together, this work provides the most comprehensive dataset to date on aggregation-dependent sequence and modification selectivity of A{beta}-Abs. By integrating mutational, PTM, and aggregation contexts in a unified experimental framework, we establish a resource that enables rational selection of antibodies for research and diagnostic applications, and offers mechanistic insights that may inform the design and optimization of future therapeutic antibodies in AD.

biochemistry↗

bioRxiv2024

SMAS: Structural MRI-Based AD Score using Bayesian VAE

This study introduces the Structural MRI-based Alzheimers Disease Score (SMAS), a novel index intended to quantify Alzheimers Disease (AD)-related morphometric patterns using a deep learning Bayesian-supervised Variational Autoencoder (Bayesian-SVAE). SMAS index was constructed using baseline structural MRI data from the DELCODE study and evaluated longitudinally in two independent cohorts: DEL-CODE (n=415) and ADNI (n=190). Our findings indicate that SMAS has strong associations with cognitive performance (DELCODE: r=-0.83; ADNI: r=-0.62), age (DEL-CODE: r=0.50; ADNI: r=0.28), hippocampal volume (DEL-CODE: r=-0.44; ADNI: r=-0.66), and total grey matter volume (DELCODE: r=-0.42; ADNI: r=-0.47), suggesting its potential as a biomarker for AD-related brain atrophy. Moreover, our longitudinal studies suggest that SMAS may be useful for early identification and tracking of AD. The model demonstrated significant predictive accuracy in distinguishing cognitively healthy individuals from those with AD (DELCODE: AUC=0.971 at baseline, 0.833 at 36 months; ADNI: AUC=0.817 at baseline, improving to 0.903 at 24 months). Notably, over a 36-month period, SMAS index outperformed existing measures such as SPARE-AD and hippocampal volume. Relevance map analysis revealed significant morphological changes in key AD-related brain regions--including the hippocampus, posterior cingulate cortex, precuneus, and lateral parietal cortex--highlighting that SMAS is a sensitive and interpretable biomarker of brain atrophy, suitable for early AD detection and longitudinal monitoring of disease progression.

neuroscience↗

bioRxiv2024

Dysfunction of the episodic memory network in the Alzheimer's disease cascade

Alzheimers disease (AD) is a major cause of dementia and cognitive decline. Here we assessed how episodic memory circuit dysfunction, a hallmark of AD, is related to the longitudinal cascade of AD biomarkers, neurodegeneration and cognition using data from the DZNE Longitudinal Cognitive Impairment and Dementia study. This data set is unique by including over 1000 longitudinal functional magnetic resonance imaging (fMRI) measurements during episodic memory encoding. We leveraged a disease progression model (DPM) to obtain AD progression scores. Voxel-wise analyses revealed widespread loss of deactivation (hyperactivation) and activation (hypoactivation) with increasing disease stage. Hyperactivation trajectories were nonlinear and visually preceded trajectories of cognition. Overall, hyperactivation was independently associated with co-occurrence of amyloid- and tau-positivity and neurodegeneration, suggesting synaptic dysfunction and neurodegeneration as two independent drives of cognitive decline. Our results therefore provide evidence for a critical time window in which pharmacological treatments targeting the synapse may improve cognition.

neuroscience↗

bioRxiv2023

Oligodendrocytes and neurons contribute to amyloid-β deposition in Alzheimer's disease

In Alzheimers disease (AD), amyloid-{beta} (A{beta}) is thought to be of neuronal origin. However, in single-cell RNAseq datasets from mouse and human, we found transcripts of amyloid precursor protein (APP) and the amyloidogenic-processing machinery equally abundant in oligodendrocytes (OLs). By cell-type-specific deletion of Bace1 in a humanized knock-in AD model, APPNLGF, we demonstrate that almost a third of cortical A{beta} deposited in plaques is derived from OLs. However, excitatory projection neurons must provide a threshold level of A{beta} production for plaque deposition to occur and for oligodendroglial A{beta} to co-aggregate. Indeed, very few plaques are deposited in the absence of neuronally-derived A{beta}, although soluble A{beta} species are readily detected, especially in subcortical white matter. Our data identify OLs as a source of A{beta} in vivo and further underscore a non-linear relationship between cellular A{beta} production and resulting plaque formation. Ultimately, our observations are relevant for therapeutic strategies aimed at disease prevention in AD.

neuroscience↗

bioRxiv2023

Diagnostic images for mild cognitive impairment reveal biomarker status and abnormal scene processing

Research on the impairment of episodic memory in Alzheimers disease often focuses on the processes of memory rather than the content of the specific images being remembered. We recently showed that patients with mild cognitive impairment (MCI), Stage 3 of Alzheimers disease, can memorize certain images quite well, suggesting that episodic memory is not uniformly impaired. Certain images, on the other hand, could not be memorized by MCI patients and were instead diagnostic for distinguishing MCI from healthy older adults. In this study, we investigate whether poor memory for diagnostic images is related to impaired neural processing in specific brain regions due to Alzheimers biomarker pathology. 64 healthy controls and 48 MCI participants in the DELCODE dataset performed a visual scene memory task during fMRI, with CSF Alzheimers disease biomarker data collected (i.e., amyloid and tau biomarkers). We found that diagnostic images have larger behavior-biomarker correlations for total tau, phospho-tau, A{beta}42/A{beta}40, A{beta}42/phospho-tau compared to non-diagnostic images, suggesting that memory for these specific images are more affected by Alzheimers disease pathology. The fMRI data revealed an interaction effect between group membership (healthy control / MCI) and image diagnosticity (diagnostic / non-diagnostic scene images), with MCI participants having higher activation in scene processing regions (parahippocampal place area, retrosplenial cortex and occipital place area) for diagnostic images than non-diagnostic images. In contrast, healthy controls showed no differences in processing between diagnostic and non-diagnostic images. These results suggest that MCI individuals may engage in inefficiently heightened encoding activation for these diagnostic images. Our results show that special "diagnostic" images exist that can reveal amyloid and tau pathology and differences in neural activity in scene regions.

neuroscience↗

bioRxiv2023

Cognitive Reserve Against Alzheimer's Pathology Is Linked to Brain Activity During Memory Formation

The cognitive reserve (CR) hypothesis posits that individuals can differ in how their brain function is disrupted by pathology associated with aging and neurodegeneration. Here, we tested this hypothesis in the Alzheimers disease continuum using longitudinal data from 490 participants of the DELCODE multicentric observational study. Brain function was measured using task fMRI of visual memory encoding. Using a multivariate moderation analysis we identified a CR-related activity pattern underlying successful memory encoding that moderated the detrimental effect of AD pathological load on cognitive performance. CR was mainly represented by a more pronounced expression of the task-active network encompassing the default mode network (DMN), anterior cingulate cortex (ACC) and inferior temporal regions including the fusiform gyrus. We devised personalized fMRI-based CR scores that moderated the impact of AD pathology on cognitive performance and were positively associated with years of education. Furthermore, higher CR scores were associated with slower cognitive decline over time. Our findings suggest maintenance of core cognitive circuits including the DMN and ACC as the primary mechanism of CR. Individual brain activity levels of these areas during memory encoding have prognostic value for future cognitive decline.

neuroscience↗

bioRxiv2023

Fornix fractional anisotropy mediates the association between Mediterranean diet adherence and memory four years later in older adults without dementia

Here, we investigated whether fractional anisotropy (FA) of hippocampus-relevant white-matter tracts mediates the association between baseline Mediterranean diet adherence (MeDiAd) and verbal episodic memory over four years. Participants were healthy older adults with and without subjective cognitive decline and patients with amnestic mild cognitive impairment from the DELCODE cohort study (n = 376; age: 71.47 {+/-} 6.09 years; 48.7% female). MeDiAd and diffusion data were obtained at baseline. Verbal episodic memory was assessed at baseline and four yearly follow-ups. The associations between baseline MeDiAd and white matter, and verbal episodic memorys mean and rate of change over four years were tested with latent growth curve modeling. Baseline MeDiAd was associated with verbal episodic memory four years later (95% confidence interval, CI [0.01, 0.32]) but not with its rate of change over this period. Baseline Fornix FA mediated - and, thus, explained - that association (95% CI [0.002, 0.09]). Fornix FA may be an appropriate response biomarker of Mediterranean diet interventions on verbal memory in older adults.

neuroscience↗

bioRxiv2022

Functional Neuroligin-2-MDGA1 interactions differentially regulate synaptic GABAARs and cytosolic gephyrin aggregation

AO_SCPLOWBSTRACTC_SCPLOWThe function of GABAergic synapses is critically shaped by cell adhesion proteins that recruit GABAARs to synapses and mediate transsynaptic signalling, but the synapse-type-specific function of such synaptic adhesion proteins and their mutual interaction remain incompletely understood. A ubiquitous cell adhesion protein at GABAergic synapses is Neuroligin-2 (Nlgn2), which recruits synaptic GABAARs by promoting the assembly of the postsynaptic gephyrin scaffold. While Nlgn2 is present at virtually all GABAergic synapses throughout the forebrain, its loss affects different GABAergic synapse subtypes with different severity, indicating that synapse-specific interactors and synapse-organizer-redundancies define the function of Nlgn2 for a given synapse type. Here we investigated how Nlgn2 function at GABAergic synapses in mouse hippocampal area CA1 is modulated by two recently identified interaction partners, MDGA1 and MDGA2. We show that Nlgn2 and MDGA1 colocalize most prominently in the stratum radiatum (S.R.) of area CA1, and that combined Nlgn2 and MDGA1 deletion causes a layer-specific exacerbation of the loss of gephyrin puncta in layer S.R. seen following Nlgn2 deletion. Intriguingly, combined Nlgn2 and MDGA1 deletion concurrently ameliorates the abnormal cytosolic gephyrin aggregation, the reduction in inhibitory synaptic transmission and the exacerbated anxiety-related behavior seen in Nlgn2 knockout (KO) mice. In contrast, heterozygous deletion of MDGA2 in Nlgn2 KO mice has only minor effects on gephyrin and GABAAR puncta and does not normalize cytosolic gephyrin aggregates, inhibitory synaptic transmission or anxiety-related behavior. Our data indicate that MDGA1, but not MDGA2, modulates Nlgn2 function, primarily by regulating the formation of cytosolic gephyrin aggregates. Given that both Nlgn2 and the MDGA family of proteins have been linked to psychiatric disorders, such as autism and schizophrenia, our data lead to the notion that abnormal gephyrin aggregation may contribute to the pathophysiology of these disorders, and that intervention with gephyrin aggregation could present a novel therapeutic strategy.

neuroscience↗

bioRxiv2022

Individualized Gaussian Process-based Prediction of Memory Performance and Biomarker Status in Ageing and Alzheimer's disease

Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as informative covariates, vascular risks, brain activity, neuropsychological test etc.,) might provide useful predictions of clinical outcomes during progression towards Alzheimers disease (AD). The Bayesian approach aims to provide a trade-off by employing relevant features combinations to build decision support systems in clinical settings where uncertainties are relevant. We tested the approach in the MRI data across 959 subjects, aged 59-89 years and 453 subjects with available neuropsychological test scores and CSF biomarker status (amyloid-beta (A{beta})42/40 & and phosphorylated tau (pTau)) from a large sample multi-centric observational cohort (DELCODE). In order to explore the beneficial combinations of information from different sources, we presented a MRI-based predictive modelling of memory performance and CSF biomarker status (positive or negative) in the healthy ageing group as well as subjects at risk of Alzheimers disease using a Gaussian process multikernel framework. Furthermore, we systematically evaluated predictive combinations of input feature sets and their model variations, i.e. (A) combinations of brain tissue classes and feature type (modulated vs. unmodulated), choices of filter size of smoothing (ranging from 0 to 15 mm full width at half maximum), and image resolution (1mm, 2mm, 4mm and 8mm); (B) incorporating demography and covariates (C) the impact of the size of the training data set (i.e., number of subjects); (D) the influence of reducing the dimensions of data and (E) choice of kernel types. Finally, the approach was tested to reveal individual cognitive scores at follow-up (up to 4 years) using the baseline features. The highest accuracy for memory performance prediction was obtained for a combination of neuroimaging markers, demographics, genetic information (ApoE4) and CSF-biomarkers explaining 57% of outcome variance in out of sample predictions. The best accuracy for A{beta}42/40 status classification was achieved for combination demographics, ApoE4 and memory score while usage of structural MRI improved the classification of individual patients pTau status.

neuroscience↗

bioRxiv2021

Lifelong musical activity is associated with multi-domain cognitive and brain benefits in older adults

1AO_SCPLOWBSTRACTC_SCPLOWRegular musical activity as a highly-stimulating lifestyle activity is proposed to be protective against age-related cognitive decline and Alzheimers disease (AD). This study investigated associations between lifelong regular musical instrument playing, late-life cognitive abilities and brain morphology in older adults. We show that musical activity over the life course is associated with better global cognition, working memory, executive functions, language, and visuospatial abilities accounting for reserve proxies. Playing music is not significantly associated with gray matter volume in regions most affected by aging and AD. Selectively in the musically active participants, multi-domain cognitive abilities were enhanced with preserved gray matter volume in frontal and temporal regions. Our correlational findings suggest that playing a musical instrument may improve the recruitment of existing brain resources to facilitate late-life cognitive capacities. We propose that engaging in regular musical activity could serve as a low-threshold multimodal enrichment strategy that may promote cognitive resilience in advanced age.

neuroscience↗

bioRxiv2021

A comprehensive score reflecting memory-related fMRI activations and deactivations as potential biomarker for neurocognitive aging

Older adults and particularly those at risk for developing dementia typically show a decline in episodic memory performance, which has been associated with altered memory network activity detectable via functional magnetic resonance imaging (fMRI). To quantify the degree of these alterations, a score has been developed as a putative imaging biomarker for successful aging in memory for older adults (Functional Activity Deviations during Encoding, FADE; Duzel et al., 2011). Here, we introduce and validate a more comprehensive version of the FADE score, termed FADE-SAME (Similarity of Activations during Memory Encoding), which differs from the original FADE score by considering not only activations but also deactivations in fMRI contrasts of stimulus novelty and successful encoding, and by taking into account the variance of young adults activations. We computed both scores for novelty and subsequent memory contrasts in a cohort of 217 healthy adults, including 106 young and 111 older participants, as well as a replication cohort of 117 young subjects. We further tested the stability and generalizability of both scores by controlling for different MR scanners and gender, as well as by using different data sets of young adults as reference samples. Both scores showed robust age-group-related differences for the subsequent memory contrast, and the FADE-SAME score additionally exhibited age-group-related differences for the novelty contrast. Furthermore, both scores correlate with behavioral measures of cognitive aging, namely memory performance. Taken together, our results suggest that single-value scores of memory-related fMRI responses may constitute promising biomarkers for quantifying neurocognitive aging.

neuroscience↗

bioRxiv2020

Regional expression profiles of risk genes for depression are associated with brain activation patterns in emotion and reward tasks

The spatial relationship between gene expression profiles and neural response patterns known to be altered in neuropsychiatric disorders, e.g. depression, can guide the development of more targeted therapies. Here, we estimated the correlation between human transcriptome data and two different brain activation maps measured with functional magnetic resonance imaging (fMRI) in healthy subjects. Whole-brain activation patterns evoked during an emotional face recognition task were associated with topological mRNA expression of genes involved in cellular transport. In contrast, fMRI activation patterns related to the acceptance of monetary rewards were associated with genes implicated in neuronal development, synapse regulation, and gene transcription. An overlap of these genes with risk genes from major depressive disorder genome-wide associations studies revealed the involvement of the master regulators TCF4 and MEF2C. These results were further validated by means of meta-analytic fMRI data. Overall, the identification of stable relationships between spatial gene expression profiles and fMRI data may reshape the prospects for imaging transcriptomics studies.

neuroscience↗

bioRxiv2019

Memorability of photographs in subjective cognitive decline and mild cognitive impairment: implications for cognitive assessment

INTRODUCTIONImpaired long-term memory is a defining feature of Mild Cognitive Impairment (MCI). We tested whether this impairment is item-specific, limited to some memoranda whereas some remain consistently memorable.\n\nMETHODSWe conducted item-based analyses of long-term visual recognition memory. 394 participants (healthy controls (HC), Subjective Cognitive Decline (SCD), and MCI) in the multicentric DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) were tested with images from a pool of 835 photographs.\n\nRESULTSWe observed consistent memorability for images in HCs, SCDs, and MCI, predictable by a neural network trained on another healthy sample. Looking at memorability differences between groups, we identified images that could successfully categorize group membership with higher success and a substantial image reduction than the original image set.\n\nDISCUSSIONIndividuals with SCD and MCI show consistent memorability for specific items, while other items show significant diagnosticity. Certain stimulus features could optimize diagnostic assessment, while others could support memory.

neuroscience↗