Journal article
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
NeuroImage clinical, Vol.15, pp.761-768
2017
DOI: 10.1016/j.nicl.2017.06.023
PMCID: PMC5496209
PMID: 28706851
Abstract
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
). 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.
Details
- Title: Subtitle
- 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
- Creators
- Maziar Yaesoubi - The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM 87106, USA; Dept. of ECE, University of New Mexico, Albuquerque, NM 87131, USA. Electronic address: myaesoubi@mrn.orgRobyn L Miller - The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM 87106, USAJuan Bustillo - Dept. of Psychiatry and Behavioral Science, University of New Mexico, Albuquerque, NM 87131, USAKelvin O Lim - Dept. of Psychiatry, University of Minnesota, Minneapolis, MN 55414, USAJatin Vaidya - Dept. of Psychiatry, University of Iowa, Iowa City, IA 52242, USAVince D Calhoun - The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM 87106, USA; Dept. of ECE, University of New Mexico, Albuquerque, NM 87131, USA
- Resource Type
- Journal article
- Publication Details
- NeuroImage clinical, Vol.15, pp.761-768
- DOI
- 10.1016/j.nicl.2017.06.023
- PMID
- 28706851
- PMCID
- PMC5496209
- NLM abbreviation
- Neuroimage Clin
- ISSN
- 2213-1582
- eISSN
- 2213-1582
- Publisher
- Netherlands
- Grant note
- R01 EB006841 / NIBIB NIH HHS P20 GM103472 / NIGMS NIH HHS R01 EB020407 / NIBIB NIH HHS
- Language
- English
- Date published
- 2017
- Academic Unit
- Psychiatry; Iowa Neuroscience Institute; University College Courses
- Record Identifier
- 9984070308902771
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