The idea of Personally Identifiable Brain (PIB) has been in my mind for a long time. This was largely inspired by Poldrack’s MyConnectome Project. You can find the structural and functional imaging data of my own brain from here (updating). The newly-proposed Brain Imaging Data Structure (BIDS) was used for preparing the files.

As mentioned in my last blog, I will list some potential applications of this kind of datasets here.

1. To hack into neuroscientist’s brain. As a neuroscientist, one inevitably scan his/her own brain. If these datasets are collected and shared, it would be a unique resource for better understanding of human brain, in particular of the neuroscientists’ brain and their academic life. For example, with the data, we could answer questions like: what kind of brain ensures a scientist’s academic success? what kind of brain make researchers perfectly network/collaborate with each other in the social network or collaboration network?

2. To explore within-individual variability of neuroscientists’ brain. If multiple sessions of scanning are available, this would be a valuable resource for studying the variability of scientists’ brain (e.g., coffee or not; paper/funding accepted or rejected). Of course, the dataset can be used for developmental and aging studies, as well as methodological studies like test-retest reliability and reproducibility. If brain scanning can be done with different scanners in different places (e.g., during traveling around the world), it could be a great dataset to explore some question related to neuroimaging biomarkers. For example, how is the relability of one neuroimaging measure across different scanners around the world? A neuroscientist seems to have more oppotunity to travel the world, while it might be difficult to let your subjects travel the world to finish the data collection.

3. To be used as education/demostration resource with the brain’s owner name. It would make learning more interesting if we know from whom the brain is from, and what’s the stories behind the brain.

4. For long-term studies of human brain. A more crazy idea in my mind for potential applications of the dataset is to link the imaging data of our living brain to the brain after we die. For example, given both structural and functional imaging scans and possibly the brain after one dies can be available, it would be a great resource to explore the links between large-scale structural measures and cellular-level information, and the links between brain functions and specific molecular basis (e.g., gene expression). Of course, some information might have to be derived from the postmortem brain tissues. I have no idea how many scientists would like to donate their own brains when they die. Actually, I am not sure myself. Nonetherless, these brains could provide new insights into understanding our magical brain.

There might be many other potential applications of this kind of dataset, but it might be a long-term project. In addition, this is still an initial idea. If you are interested in this project, any suggestion/comment and support would be appreciated for this project.