Nov
27
2012

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  • Host Department: Center for the Study of Complex Systems
  • Date: 11/27/2012
  • Time: 12:00PM - 1:30PM

  • Location: 411 West Hall

  • Description:

    Title: Network Architecture and Predictive Dynamics of Brain Systems

    Abstract: The study of complex systems poses significant mathematical
    challenges but can simultaneously provide an increased mechanistic
    understanding of real-world system function. I focus on recent
    developments in network science that have provided methods to
    characterize the organization and dynamics of systems that are
    composed of many interacting parts. At the interdisciplinary boundary
    between applied mathematics, statistical physics, and neuroscience, I
    study the human brain as a network of cortical areas connected by
    structural or functional highways along which information propagates.
    Data acquired from non-invasive neuroimaging techniques has
    demonstrated that brain network structure varies between individuals,
    can be linked to our IQ and cognitive abilities, displays altered
    patterns in disease states like schizophrenia, and changes over time.
    A mathematical assessment of these dynamics enables the identification
    of network signatures that predict individual differences in cognitive
    behaviors such as learning, facilitating a direct feedback loop
    between theory and experiment. Using these approaches, we can begin to
    determine fundamental organizational principles of both underlying
    brain structure and its functional dynamics. Moreover, these results
    lay the groundwork for statistical approaches to predict individual
    brain responses to injury, disease, and clinical interventions, that
    could enable the construction of personalized therapeutics,
    diagnostics, and biomarkers for monitoring disease progression and
    rehabilitation. In addition to understanding phenomena specific to the
    human brain, these studies facilitate the examination of more general
    questions about the relationships between system organization – both
    static and dynamic – and performance, as well as the influence of
    external energetic or spatial constraints on that organization. In
    ongoing work, we seek to link brain network dynamics with smaller
    scale genetic drivers and larger scale social structures to build a
    better understanding of the biophysical constraints on and neural
    mechanisms of human decision making and their implications for a
    statistical mechanics of human collective phenomena.


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