TY - JOUR
T1 - A joint time-frequency analysis of resting-state functional connectivity reveals novel patterns of connectivity shared between or unique to schizophrenia patients and healthy controls
AU - Yaesoubi, Maziar
AU - Miller, Robyn L.
AU - Bustillo, Juan
AU - Lim, Kelvin O.
AU - Vaidya, Jatin
AU - Calhoun, Vince D.
N1 - Funding Information:
We need to thank investigators who collected the data. The Authors have declared that there are no conflicts of interest in relation to the subject of this study. This work was supported by National Institutes of Health grants: P20GM103472, 1R01EB006841, R01EB020407, and National Science Foundation #1539067.
Publisher Copyright:
© 2017 The Authors
PY - 2017
Y1 - 2017
N2 - Functional connectivity of the resting-state (RS) brain is a vehicle to study brain dysconnectivity aspects of diseases such as schizophrenia and bipolar. Methods that are developed to measure functional connectivity are based on the underlying hypotheses regarding the actual nature of RS-connectivity including evidence of temporally dynamic versus static RS-connectivity and evidence of frequency-specific versus hemodynamically-driven connectivity over a wide frequency range. This study is derived by these observations of variation of RS-connectivity in temporal and frequency domains and evaluates such characteristics of RS-connectivity in clinical population and jointly in temporal and frequency domains (the spectro-temporal domain). We base this study on the hypothesis that by studying functional connectivity of schizophrenia patients and comparing it to the one of healthy controls in the spectro-temporal domain we might be able to make new observations regarding the differences and similarities between diseased and healthy brain connectivity and such observations could be obscured by studies which investigate such characteristics separately. Interestingly, our results include, but are not limited to, a spectrally localized (mostly mid-range frequencies) modular dynamic connectivity pattern in which sensory motor networks are anti-correlated with visual, auditory and sub-cortical networks in schizophrenia, as well as evidence of lagged dependence between default-mode and sensory networks in schizophrenia. These observations are unique to the proposed augmented domain of connectivity analysis. We conclude this study by arguing not only resting-state connectivity has structured spectro-temporal variability, but also that studying properties of connectivity in this joint domain reveals distinctive group-based differences and similarities between clinical and healthy populations.
AB - Functional connectivity of the resting-state (RS) brain is a vehicle to study brain dysconnectivity aspects of diseases such as schizophrenia and bipolar. Methods that are developed to measure functional connectivity are based on the underlying hypotheses regarding the actual nature of RS-connectivity including evidence of temporally dynamic versus static RS-connectivity and evidence of frequency-specific versus hemodynamically-driven connectivity over a wide frequency range. This study is derived by these observations of variation of RS-connectivity in temporal and frequency domains and evaluates such characteristics of RS-connectivity in clinical population and jointly in temporal and frequency domains (the spectro-temporal domain). We base this study on the hypothesis that by studying functional connectivity of schizophrenia patients and comparing it to the one of healthy controls in the spectro-temporal domain we might be able to make new observations regarding the differences and similarities between diseased and healthy brain connectivity and such observations could be obscured by studies which investigate such characteristics separately. Interestingly, our results include, but are not limited to, a spectrally localized (mostly mid-range frequencies) modular dynamic connectivity pattern in which sensory motor networks are anti-correlated with visual, auditory and sub-cortical networks in schizophrenia, as well as evidence of lagged dependence between default-mode and sensory networks in schizophrenia. These observations are unique to the proposed augmented domain of connectivity analysis. We conclude this study by arguing not only resting-state connectivity has structured spectro-temporal variability, but also that studying properties of connectivity in this joint domain reveals distinctive group-based differences and similarities between clinical and healthy populations.
KW - Dynamic and frequency-specific connectivity
KW - Resting-state functional connectivity
KW - Time-frequency analysis
KW - Wavelet transform coherence
UR - http://www.scopus.com/inward/record.url?scp=85021455254&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85021455254&partnerID=8YFLogxK
U2 - 10.1016/j.nicl.2017.06.023
DO - 10.1016/j.nicl.2017.06.023
M3 - Article
C2 - 28706851
AN - SCOPUS:85021455254
SN - 2213-1582
VL - 15
SP - 761
EP - 768
JO - NeuroImage: Clinical
JF - NeuroImage: Clinical
ER -