Frederic Brosseron

The paper examines how disrupted forward connectivity in the parieto-temporal network relates to memory impairment and AD pathology using fMRI and DCM in a longitudinal study.

This study examines how episodic memory network dysfunction relates to AD biomarkers, neurodegeneration, and cognition using longitudinal fMRI data from the DZNE study.

This paper introduces ELSI-Net, a deep learning method for automated Locus Coeruleus segmentation and feature extraction in aging and Alzheimer's Disease dementia, showing high agreement with manual ratings and correlations to CSF biomarkers.

The paper links cognitive reserve to brain activity during memory formation, showing it moderates the impact of Alzheimer's pathology on cognitive performance and predicts slower decline.

This paper introduces SMAS, a Bayesian VAE-based AD score from structural MRI data, showing strong correlations with cognitive decline and brain atrophy markers, and outperforming existing measures in predicting AD.

The paper identifies diagnostic images that correlate with Alzheimer's biomarkers and show differential neural processing in MCI patients compared to healthy controls.

The paper uses Gaussian process multikernel modeling to predict memory performance and CSF biomarkers in ageing and Alzheimer's disease using MRI and other data.

This study shows that SFRP1 from astrocytes promotes microglial activation in acute and chronic neuroinflammation, suggesting it as a therapeutic target.

The paper assesses memorability of photographs in healthy controls, subjective cognitive decline, and mild cognitive impairment, identifying images with diagnostic potential.