Pittsburgh Imaging Project (PIP) Dataset

 The Pittsburgh Imaging Project (PIP) fMRI dataset was generated for the research publication Gianaros et al. (2017). Participants conducted interleaved trials of congruent and incongruent phases of the both the Stroop and Multi-Source Inference Tasks (MSIT) with 10 second fixation rest in between trials. There was a separate resting state scan collected from these participants where they simply stared at a fixed crosshair. 

 Initially this data was meant to be utilized as a stressor evoked task since the Stroop and MSIT tasks are adaptive, whereby higher accuracy scores in the incongruent phases led to shorter intervals between trials. The number of trials were matched to the congruent phases of the task. The data has been processed from functional connectivity matrices to edge time series (Faskowitz et al., 2020) co-fluctuations for the entire timescale of the fMRI task. 

 In our research, in the linked preprint below, this dataset was used to examine a network perspective of the brain. Cortical flexibility is shown to be paramount to the resolution of a number of tasks, both novel and habitual. During these instances of heightened cortical flexibility there is network change from integrative (more communication across specialized brain regions) to segregative (more communication within regions or hubs) states. We sought to examine whether the basal ganglia and cerebellum act as control states for initiating integration and segregation of cortical networks respectively. 

arXiv preprint:

https://arxiv.org/abs/2408.07977

References

Gianaros, P. J., Sheu, L. K., Uyar, F., Koushik, J., Jennings, J. R., Wager, T. D., Singh, A., & Verstynen, T. D. (2017). A Brain Phenotype for Stressor‐Evoked Blood Pressure Reactivity. Journal of the American Heart Association, 6(9), e006053. https://doi.org/10.1161/JAHA.117.006053

Faskowitz, J., Esfahlani, F. Z., Jo, Y., Sporns, O., & Betzel, R. F. (2020). Edge-centric functional network representations of human cerebral cortex reveal overlapping system-level architecture. Nature Neuroscience, 23(12), 1644–1654. https://doi.org/10.1038/s41593-020-00719-y