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Author

Emrah Düzel

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Open access Jul 2026

Disruption of temporo-parietal network in Alzheimer’s disease and its association with memory impairment

Alzheimer’s disease (AD) is characterised by the accumulation of β-amyloid (Aβ) and tau proteins, resulting in neurodegeneration and cognitive decline. Although Aβ and tau disrupt synaptic function, the association linking these molecular pathologies to network-level dysfunction and memory impairment remains poorly understood. Here, we investigated the effects of Aβ and tau pathology (CSF Aβ42/40 ratio and tau phosphorylated at position 181, p-tau-181, respectively) on effective connectivity related to memory encoding, which may provide a link between synaptic pathology and cognitive outcomes. Functional magnetic resonance imaging (fMRI) during visual memory encoding was acquired from 205 participants in the multicentric DZNE Longitudinal Cognitive Impairment and Dementia Study (DELCODE) across the AD spectrum. Effective connectivity was assessed using Dynamic Causal Modelling (DCM) of task-fMRI data, focusing on the parahippocampal place area (PPA), hippocampus (HC), and precuneus (PCU)—regions central to memory encoding. Disruptions in connectivity between temporal and parietal lobes were associated with both memory impairment and indices of AD pathology. Specifically, reduced positive effective connectivity from the PCU to the PPA and from the HC to the PCU were linked to higher p-tau-181 levels, with an amplification effect observed in the presence of amyloid accumulation for the latter connectivity. The disruption from the PCU to the PPA was found to be associated with decreased memory performance. Together, these findings indicate that temporo-parietal connectivity is associated with both AD molecular pathology and, for a subset of connections, with memory performance.

Yanin Suksangkharn, B. Schott, P. Zeidman et al. · 0 citations
Open access Jul 2026

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.

Tatjana Schmidt, Robert Salzmann, M. Montagnese et al. · 0 citations