Dynamic Functional Network Connectivity Clustering and Harmonization Evaluation Metric

Neuroscience studies have improved significantly through multi-site datasets. Brain dynamic functional network connectivity (dFNC) often uses clustering to represent various patterns of functional connectivity that repeat with time. Data collected from different sources combined may be affected by site effects. This can be mitigated by harmonizing the dataset before doing additional analysis. Here, we explore the impact of ComBat harmonization on dFNC data collected from two different mild traumatic brain injury (mTBI) studies. Our research showed that site effects significantly influence the formation of dFNC states. We developed a new method to measure the distribution of samples among the clusters based on site effects in clustering called an 'Inclusivity' model. With this inclusivity model, we evaluate how site effects influence the clustering of dFNC states before and after data harmonization.