Joelle Zimmermann presents her work on Alzheimer's disease using TVB at the International Conference on Learning & Memory, in celebration of the 35th anniversary of the Center for the Neurobiology of Learning and Memory at UC Irvine.
Alzheimer’s disease (AD) is marked by cognitive dysfunction emerging from altered brain network activity. Developing markers specific to AD require the assessment of mechanisms at the cellular scale, difficult to detect with noninvasive neuroimaging acquisitions. Our new computational framework “The Virtual Brain (TVB)” is a quantitative tool that links neuroimaging profiles, large-scale brain network dynamics and the cellular mechanisms underlying neurodegeneration that we use to comprehensively “reconstruct” the diseased brain. TVB integrates empirical neuroimaging data of different modalities and spatiotemporal scales to construct biologically-plausible models of brain dynamics. We model individual resting-state functional activity of 124 individuals across the spectrum from healthy aging, to Mild Cognitive Impairment (MCI), to AD. Model parameters correlate with cognition across the spectrum of disease severity. Model parameters actually exceed empirical connectomes in their covariation with cognition.