Evaluation of Electroencephalographic Biomarkers in Physiological Aging

Aging is the inevitable biological process that results in a progressive structural and functional decline from the cellular level to whole body function. It is associated with functional changes in the resting brain activity, brain morphology, plasticity, complexity and function. Moreover, aging is the main risk factor for neurodegenerative disease.

Understanding the molecular mechanisms underlying the age-related neurophysiological changes and identifying novel biomarkers of healthy brain ageing is thus instrumental for the development of efficient interventions against age-related motor/cognitive impairments. Within this context, there is now a significant literature establishing the enhanced efficacy of secreted exosomes over the stem cells from which they are derived when used as a possible treatment for neurodegenerative disorders. Exosomes are a subgroup of extracellular vesicles which regulate intercellular communication and, unlike stem cells, easily cross into the brain and can be administered in non-syngeneic species without immune rejection.

Studies on brain ageing in humans has major limitation in the lack of accessibility of the central nervous system. EEG has allowed the non-invasive assessment of functional changes in the aging brain. In fact, this technique can provide a direct assessment of neural activity and information flow with a higher temporal resolution that is particularly important for investigating the dynamics of brain changes underlying cognitive processing and age-related changes, providing novel biomarkers of brain aging that could be used to unveil differences between healthy and unhealthy processes particularly in the pre-symptomatic and pre-clinical stage. To reach this aim, it is necessary to demonstrate, in experimental models, the relationship between age-dependent changes in brain activity and cellular/molecular processes occurring in aged brain.

Our project will pursue this overall goal by:

1) identifying neurophysiological biomarkers of brain aging in human subjects based on functional network and complexity analyses; 2) characterizing age-dependent changes in brain connectivity and complexity in mice and correlating them to changes in motor and cognitive performances and to molecular alterations occurring in both the brain and blood; 3) evaluating changes of the identified electrophysiological and molecular biomarkers in mice treated with stem cell derived exosomes for the rejuvenation of the aged brain.

4) designing Artificial Intelligence (AI) predictor of brain age trajectories on individual basis to evaluate individual neural reserve and resilience.

This study will identify novel electrophysiological biomarkers of healthy brain ageing and will advance knowledge on cellular/molecular signature of brain aging that could targeted for the preservation of brain health.