People change. And when they do, their brains change too.
The MyConnectome project has characterized how the brain of one person changes over the course of more than one year. It is almost certainly the most ambitious study of a single living person’s brain ever attempted. The data will provide new insights into the dynamics of brain activity and their relationship to bodily metabolism and psychological function. The project is also openly sharing a large amount of biological data for future reuse.
The data from this study have already resulted in a number of academic papers:
- Poldrack RA, Laumann TO, Koyejo O, Gregory B, Hover A, Chen MY, Luci J, Joo SJ, Handwerker D, Liang J, Boyd R, Hunicke- Smith S, Simpson ZB, Caven T, Sochat V, Shine JM, Gordon E, Snyder AZ, Adeyemo B, Petersen SE, Glahn D, McKay DR, Curran JE, Göring HHH, Carless MA, Blangero J, Frick L, Marcotte E, Mumford JA (2015). Long-term neural and physiological phenotyping of a single human. Nature Communications
- Laumann T, Gordon E, Adeyemo B, Snyder AZ, Joo SJ, Chen MY, Mumford JA, Poldrack RA, Petersen SE (2015). Functional network and areal organization of a densely-sampled individual human brain. Neuron, 87, 657-70.
- Qin Y, Yao J, Wu DC, Nottingham RM, Mohr S, Hunicke-Smith S, Lambowitz AM (2015). High-throughput sequencing of human plasma RNA by using thermostable group II intron reverse transcriptase. RNA, 22: 111-128.
- Shine JM, Koyejo O, Poldrack RA (2016). Temporal meta-states are associated with di erential patterns of dynamic connectivity, network topology and attention. Proceedings of the National Academy of Sciences. 113(35):9888-91.
- Betzel RF, Satterthwaite TD, Gold JI, Bassett DS (2017). Positive affect, surprise, and fatigue are correlates of network flexibility. Scientific Reports, 31;7(1):520.
- Power JD (2017). A simple but useful way to assess fMRI scan qualities. Neuroimage, 154:150-158.
- Tong Y, Yao JF, Chen JJ, Frederick BD. (2018). The resting-state fMRI arterial signal predicts differential blood transit time through the brain. Journal of Cerebral Blood Flow & Metabolism.
- Rasero J, Pellicoro M, Angelini L, Cortes JM, Marinazzo D, Stramaglia S. (2018). Consensus clustering approach to group brain connectivity matrices. Network Neuroscience.