There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
Principal Investigator | |
Principal Investigator's Name: | Skyler Cranmer |
Institution: | The Ohio State University |
Department: | Political Science |
Country: | |
Proposed Analysis: | My lab specializes is network analysis methodology. In the past few years, we have written a series of papers analyzing functional connectivity networks, with an eye to understanding subnetwork and whole-brain network structures, create generative models of the same, and link behaviors with these network structures. Much of this work has been methodological, developing the statistical tools for this analysis and some of it has been specific to neurological applications. While relatively new to this field and approaching it as a methodologists rather than an neuroscientists, our papers have been published in Computational Brain & Behavior (2020), Neuroimage (2019), Scientific Reports (2017), Journal of Statistical Physics (2018), Social Networks (2017), and PLoS One (2012). With these data, we are interested in seeing whether specific changes in functional connectivity networks can be tied to the aging process generally and the progression of Alzheimer’s disease specifically. We are also interested to see if we can identify network patterns associated with TBI/CBI and PTSD. We intend to do this by using a combination of machine learning algorithms (e.g. CNNs and random forests) and statistical modeling approaches (e.g. generalized exponential random graph models and hierarchical latent space models). For these reasons, we would like to request access to all of the datasets (AIBL, ADNI, ADNIDOD). |
Additional Investigators | |
Investigator's Name: | James Wilson |
Proposed Analysis: | My lab specializes is network analysis methodology. In the past few years, we have written a series of papers analyzing functional connectivity networks, with an eye to understanding subnetwork and whole-brain network structures, create generative models of the same, and link behaviors with these network structures. Much of this work has been methodological, developing the statistical tools for this analysis and some of it has been specific to neurological applications. While relatively new to this field and approaching it as a methodologists rather than an neuroscientists, our papers have been published in Computational Brain & Behavior (2020), Neuroimage (2019), Scientific Reports (2017), Journal of Statistical Physics (2018), Social Networks (2017), and PLoS One (2012). With these data, we are interested in seeing whether specific changes in functional connectivity networks can be tied to the aging process generally and the progression of Alzheimer’s disease specifically. We are also interested to see if we can identify network patterns associated with TBI/CBI and PTSD. We intend to do this by using a combination of machine learning algorithms (e.g. CNNs and random forests) and statistical modeling approaches (e.g. generalized exponential random graph models and hierarchical latent space models). For these reasons, we would like to request access to all of the datasets (AIBL, ADNI, ADNIDOD). |