Decoding the Brain’s Aging Mysteries: The Quasicriticality Framework

Published on November 30, 2022

Similar to how a symphony relies on the perfect harmony and coordination of its musicians, the human brain operates via complex interactions between neurons. As we age, these interactions undergo changes that can impact our cognitive abilities and overall neurological health. A team of scientists has delved into this intriguing subject by examining a rich dataset of brain activity recorded from individuals of different ages and genders. They applied the quasicriticality framework, a novel approach that links brain connectivity, information processing, and stimulus response. By doing so, they uncovered fascinating correlations between age, gender, and the dynamics of neuronal firing rates. Simulations further validated their findings, hinting at a potential connection between altered brain connectivity in aging individuals and increased fluctuations in how neurons fire. This groundbreaking research offers a promising foundation for developing biomarkers to assess neurological health. To dive deeper into the intricacies of the brain’s aging mysteries, check out the full article!

Aging impacts the brain’s structural and functional organization and over time leads to various disorders, such as Alzheimer’s disease and cognitive impairment. The process also impacts sensory function, bringing about a general slowing in various perceptual and cognitive functions. Here, we analyze the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) resting-state magnetoencephalography (MEG) dataset—the largest aging cohort available—in light of the quasicriticality framework, a novel organizing principle for brain functionality which relates information processing and scaling properties of brain activity to brain connectivity and stimulus. Examination of the data using this framework reveals interesting correlations with age and gender of test subjects. Using simulated data as verification, our results suggest a link between changes to brain connectivity due to aging and increased dynamical fluctuations of neuronal firing rates. Our findings suggest a platform to develop biomarkers of neurological health.

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