Martial Mermillod

This study uses deep learning interpretability methods on resting-state fMRI data to show how functional brain networks reorganize with age and relate to cognitive performance.

This study uses graph signal processing to analyze structural and functional brain connectivity in healthy aging, revealing distinct age-related patterns in cognitive systems.

The paper analyzes resting-state fMRI data to show how brain network energy redistributes with age, supporting cognitive flexibility through an allostatic mechanism.

The paper examines how functional connectivity in the Default Mode Network (DMN) changes with age, showing a shift in temporal dynamics that helps maintain lexical production.

The paper examines age-related changes in language processing using fMRI and neuropsychological data, identifying neural mechanisms and a new model for cognitive aging.

This study identifies white matter changes and neurocognitive transitions in middle-aged adults associated with lexical production decline, highlighting age-related shifts in compensatory strategies.

This study investigates how real-world expectations and their affective value influence object processing using fMRI, showing distinct brain activity patterns in different regions based on expectation validity and context affect.

This study investigates epistemic curiosity by using a trivia quiz to examine its relationship with uncertainty, revealing neural correlates in specific brain regions.