Network-based biOmarker Discovery of Neurodegenerative Diseases Using Multimodal Connectivity

Alzheimer's (AD) and Parkinson's (PD) diseases are characterized by pre-clinical and asymptomatic phases, which can extend over decades, before progressing through different clinical stages where cognitive and/or motor symptoms appear. A major challenge for clinical neuroscience is the availability of reliable, non-invasive and inexpensive biomarkers to enable early diagnosis, be clinically relevant, and ideally contribute to prognosis and patient monitoring. Current criteria, which are essentially clinical, have a relatively low diagnostic accuracy, which is unfortunately responsible for a delay in diagnosis, whereas it has been established that early diagnosis makes it possible to postpone the loss of autonomy, open up opportunities for clinical trials for patients, and, epidemiologically speaking, ultimately reduce the prevalence of major neurocognitive disorders. Recent advances in neuroimaging techniques and connectome analysis have led to the identification of innovative biomarkers that reflect the disorganization of brain networks and are associated with clinical symptoms. After participant inclusion, the experimental visit will take place over half a day, for patients with early-stage Alzheimer's or Parkinson's disease and for healthy control volunteers. After clinical assessment, participants will undergo an MRI scan and then perform the CONFMEM experimental task. The aim of this paradigm is to identify the impact of cognitive conflict situations on recognition memory (the ability to judge whether or not a stimulus has been previously presented). The cerebral connectome will be assessed for each patient, with the aim of determining whether patterns can lead to pathology-specific markers.