Higher Dimensional Meta-State Analysis Reveals Reduced Resting fMRI Connectivity Dynamism in Schizophrenia Patients

• DOI: 10.1371/journal.pone.0149849
• Publication Date: 2016-03-16T20:16:22Z
• Authors: Robyn L. Miller; Maziar Yaesoubi; Jessica A. Turner; Daniel Mathalon; Adrian Preda; Godfrey Pearlson; Tulay Adali; Vince D. Calhoun
• Keywords: Dynamism; Dynamic functional connectivity

Resting-state functional brain imaging studies of network connectivity have long assumed that connections are stationary on the timescale a typical scan. Interest in moving beyond this simplifying assumption has emerged only recently. The great hope is training right lens time-varying properties whole-brain will shed additional light previously concealed activation patterns characteristic serious neurological or psychiatric disorders. We present evidence multiple explicitly dynamical strongly associated with schizophrenia, complex mental illness whose symptomatic presentation can vary enormously across subjects. As so much brain-imaging research, central challenge for dynamic lies determining transformations data both reduce its dimensionality and expose features predictive important population characteristics. Our paper introduces an elegant, simple method reducing organizing around which large constellation mutually informative intuitive analyses be performed. This framework combines discrete multidimensional data-driven representation space four core dynamism measures computed from large-scale each subject’s trajectory, ie., not identifiable any specific moment time therefore reasonable to employ settings lacking inter-subject time-alignment, such as resting-state studies. analysis exposes pronounced differences between schizophrenia patients (Nsz = 151) healthy controls (Nhc 163). Time-varying found markedly less dynamically active patients, effect even more high levels hallucinatory behavior. To best our knowledge first demonstration high-level connectivity, generic enough commensurable under many decompositions data, exhibit robust systematic controls.