The default mode network (DMN) changes with Alzheimer’s disease (AD), mild cognitive impairment (MCI), and normal aging, but these changes are not well characterized. The posterior cingulate cortex (PCC) is a critical hub in the DMN. Using data from the Alzheimer’s Disease Neuroimaging Initiative database, we modeled longitudinal change in PCC connectivity in three subject groups: healthy controls, MCI, and AD, and tested whether connectivity changes were linear or quadratic with time. The HC group had no evidence of Aβ accumulation (N=56, 25 male, 75.7±6.23 years). The MCI group pooled all MCI and significant memory concern subjects with no signs of dementia (N=127, 59 male, 72.6±7.14 years). The AD group fulfilled the National Institute of Neurological and Communicative Disorders and Stroke (NINCDS) and the Alzheimer's Disease and Related Disorders Association (ADRDA, now known as the Alzheimer’s Association) criteria for probable AD (N=34, 16 male, 74.2±7.47 years). We processed resting state fMRI images using a workflow that represents best practices for removal of noise, censoring motion outliers. We measured individual connectivity to a 10mm sphere in the PCC (2,-52,28) and transformed the Pearson correlations using a Fisher Z-transformation. We used a software developed in our lab called neuropointillist to fit a mixed effects growth model in R to each voxel, comparing linear and quadratic forms of longitudinal change. Data were cluster corrected for multiple comparisons at p=.05, α=.05. A linear model was superior to a quadratic model for all groups across the brain. All three groups showed decreased connectivity with age of the PCC to the medial frontal wall. However, we found increased connectivity to the dorsal attention network only in the MCI group. We identified distinct regions of the brain that increased and decreased in connectivity to the PCC with age in the three subgroups. These differences likely represent the different pathophysiological processes occurring in normal aging, MCI, and AD.

We are developing a program that allows us to thank research participants who are involved in Magnetic Resonance Imaging (MRI) studies in a unique and inexpensive way. Our program takes a participant’s structural brain scan and turns it into a personalized birthday card. This project involves testing the program to ensure that it is portable to different scanner sites and subject populations (children through adults), and modifying it as necessary. Upon completion we want to document and share this program using GitHub, a code repository. This program is a Bash shell script that has been developed to be run from the command line in Linux, using only additional programs from a popular neuroimaging package called FSL. The program is designed to use input brain images in Neuroimaging Informatics Technology Initiative (NiFTI) format. Our program takes the brain images, identifies an attractive sagittal slice, overlays a party hat image, text that states “Happy Birthday” and “We Lobe You” on this slice, and creates an output image that can be used to create a birthday card. We will test NiFTI files from our own scanner and from other sites to ensure portability across multiple sites, and modify the hat positioning algorithm as necessary to make it work across different head sizes and image dimensions. We will document not just program use, but a system for creating cards in advance using photo frame holders. We will evaluate ease of use by asking target potential users to install the program and generate cards. In the end we will have a completely portable program ready for distribution and published on GitHub. This project is a good example of how neuroimaging data can be used in a non-scientific way to thank participants for their contribution, conveying to them that their time is important and appreciated.