Scholarly Work

Introduction. The human brain is a complex and dynamical system that changes throughout the lifetime. Noninvasive imaging techniques, including magnetic resonance imaging (MRI), allow for the measurement of large scale functional and structural connectivity networks in the brain. Beyond trends, the dynamics across long timescales are still poorly understood. Methods. Our research aims to address the question of these long-term dynamics by adapting and applying the stochastic actor-oriented model to functional and structural brain networks derived from MRI data in an aging population. Conclusions. The resulting models of network change suggest that the brain is promoting modularity, local efficiency, and short-range connectivity during aging with more adaptive functional networks than the structural networks. Differences between individuals with and without cognitive impairment suggest a disruption in the maintenance of key brain topology in the progression of cognitive impairment with age. These results contribute to the emerging picture of long-term dynamics in aging.

Interdisciplinary work in science is a popular pursuit and often a buzzword in blurbs and bios. However, probing a little deeper into the philosophy of science reveals pitfalls and traps rarely addressed in the day-to-day practice of science. Disciplines in science have large gaps between their individual practices and assumptions that feel, on occasion, somewhat insurmountable. This, however, is the mission of the interdisciplinarian. This talk endeavours to discuss the gap between philosophical principles and practical interdisciplinary science through my experiences in neurophysics. Why is interdisciplinary science important – practically and philosophically? How are the practices and assumptions of a fundamentally interdisciplinary field like neurophysics informed by philosophy? What is the state of parity and collaboration between disciplines in the field?  If interdisciplinary science is key to understanding more about the world around us, not only must one bridge the gap between scientific disciplines like neuroscience and physics, but also incorporate philosophy into scientific practice.

The human brain is a complex and dynamical system that undergoes structural and functional changes throughout the lifetime. As the complexities of the human brain during aging are better understood, greater context can be provided to the experiences and challenges as well as the diseases that can affect these populations. Non-invasive imaging techniques such as functional magnetic resonance imaging (fMRI) allow us to measure large scale connectivity of the human brain. The changes to these networks across the lifetime are still poorly understood. My research develops and tests a model for changes to brain connectivity during aging. I constructed functional brain networks from fMRI data at longitudinal time windows across the lifetime. These time points have been analyzed for which factors, either internal or external to the network, are driving change over time. This can lead to greater understanding of the distinction between healthy and patient populations as well as the dynamics of the connections during aging. This will allow us to map how changes in these connections are linked to specific experiences or biomarkers that occur during the lifespan of an individual. These types of dynamics will bring greater insight to the experiences and challenges that occur during human aging and in future, help individuals experiencing neurodegenerative illness.

The human brain is a complex and dynamical system that undergoes structural and functional  changes throughout the lifetime. As the complexities of the human brain during aging are better  understood, greater context can be provided to the experiences and challenges as well as  understand more about diseases that can affect these populations. Non-invasive imaging  techniques such as functional magnetic resonance imaging allow us to measure large scale  connectivity of the human brain. The changes to these networks across the lifetime are still  poorly understood. My research is developing and testing a model for understanding changes to  brain connectivity during aging by constructing functional brain networks from fMRI data at  longitudinal time windows across the lifetime. These time points can be analyzed for which  factors, either internal or external to the network, are driving change over time. This can lead to  greater understanding of the distinction between healthy and patient populations as well as the  dynamics of the connections during aging. This will allow us to map how changes in these  connections are linked to specific experiences or biomarkers that occur during the lifespan of an  individual. These types of dynamics will bring greater insight to the experiences and challenges  that occur during human aging and in future, help individuals experiencing neurodegenerative  illness.