Biology subjects

Schuetze, H.

Publications and source records attributed to Schuetze, H..

2 recordsLinked to original sources

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↗

bioRxiv2020

Bayesian model selection favors parametric over categorical models of the fMRI subsequent memory effect in young and elderly adults

Subsequent memory paradigms allow to identify neural correlates of successful encoding by separating brain responses as a function of memory performance during later retrieval. In functional magnetic resonance imaging (fMRI), the paradigm typically elicits activations of medial temporal lobe, prefrontal and parietal cortical structures in young, healthy participants. This categorical approach is, however, limited by insufficient memory performance in older and particularly memory-impaired individuals. A parametric modulation of encoding-related activations with memory confidence could overcome this limitation. Here, we applied cross-validated Bayesian model selection (cvBMS) for first-level fMRI models to a visual subsequent memory paradigm in young (18-35 years) and older (51-80 years) adults. Nested cvBMS revealed that parametric models, especially with non-linear transformations of memory confidence ratings, outperformed categorical models in explaining the fMRI signal variance during encoding. We thereby provide a framework for improving the modeling of encoding-related activations and for applying subsequent memory paradigms to memory-impaired individuals.

neuroscience↗