Characterizing Connectivity in Brain Networks Using Magnetic Resonance Imaging

The human brain is a system of neurons that provides great computational capacity via a complicated communication network. A complete description of this network, also known as the human connectome, is an active topic of research as it would provide invaluable knowledge to cognitive neuroscience. Historically, the study of brain connectivity has been marked by a dichotomy between structure and function. Recent advances in magnetic resonance imaging (MRI) provide a potential framework for bridging this divide and allowing for a more complete window onto brain connectivity. Here, a framework for examining structural connectivity and functional connectivity in a network is presented with a focus upon the study of well-known subnetworks. An examination of the thalamo-cortical system exhibits the ability to use multivariate MRI data to model a brain network and identify localized connectivity disruptions. A study of a language-based decision-making task shows how functional and structural connectivity may be used to examine the integration of multiple subnetworks and their influence upon cognitive performance. Finally, a study of lateralization in aging demonstrates that both age-related functional and structural are associated with maintaining a high level of cognitive performance.

Author dc:creator

• Duda, Jeffrey T

Advisor dc:contributor.advisor

• James Gee

Repository record dc:identifier.uri

https://repository.upenn.edu/handle/20.500.14332/28770

OAI identifier oai:identifier

oai:repository.upenn.edu:20.500.14332/28770