Resting state fMRI-based temporal coherence mapping

Long-range temporal coherence (LRTC) is a fundamental characteristic of self-organized dynamic systems and plays a crucial role in their function. In the brain, LRTC has been shown to be essential for cognition. Assessing LRTC may provide critical insights into the underlying mechanisms of brain organization, function, and cognition. To facilitate this overarching goal, I present a method called temporal coherence mapping (TCM) to explicitly quantify brain LRTC and validate it using resting-state fMRI in this paper. TCM is based on correlation analysis of the transit states of the phase space reconstructed by temporal embedding. Several TCM properties were derived to measure LRTC, including the averaged correlation, anti-correlation, the balance between correlation and anticorrelation, the mean coherent and incoherent duration, and the balance between the coherent and incoherent time. TCM was first evaluated with simulations and then applied to the large-scale Human Connectome Project data. The results showed that TCM metrics can successfully differentiate signals with different temporal coherence regardless of the parameters used to reconstruct the phase space. In the human brain, all TCM metrics showed high test-retest reproducibility; TCM metrics were associated with age, sex, and total cognitive scores. In summary, TCM provides a first-of-its-kind tool to assess LRTC and the balance between coherence and incoherence. The physiological and cognitive relevance of TCM properties highlights their potential for advancing our understanding of brain dynamics.