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Hear Res. 2014 Jan;307:153-62. doi: 10.1016/j.heares.2013.07.010. Epub 2013 Jul 26.

Using resting state functional connectivity to unravel networks of tinnitus.

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Department of Speech and Hearing Science, University of Illinois at Urbana-Champaign, Champaign, IL, USA; Neuroscience Program, University of Illinois at Urbana-Champaign, Champaign, IL, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, USA. Electronic address:


Resting state functional connectivity (rs-fc) using fMRI has become an important tool in examining differences in brain activity between patient and healthy populations. Studies employing rs-fc have successfully identified altered intrinsic neural networks in many neurological and psychiatric disorders, including Alzheimer's disease, schizophrenia, and more recently, tinnitus. The neural mechanisms of subjective tinnitus, defined as the perception of sound without an external source, are not well understood. Several inherent networks have been implicated in tinnitus; these include default mode, auditory, dorsal attention, and visual resting-state networks. Evidence from several studies has begun to suggest that tinnitus causes consistent modifications to these networks, including greater connectivity between limbic areas and cortical networks not traditionally involved with emotion processing, and increased connectivity between attention and auditory processing brain regions. Such consistent changes to these networks may allow for the identification of objective brain imaging measures of tinnitus, leading to a better understanding of the neural basis of the disorder. Further, examination of rs-fc allows us to correlate behavioral measures, such as tinnitus severity and comorbid factors including hearing loss, with specific intrinsic networks. This article is part of a Special Issue entitled Human Auditory Neuroimaging.


BOLD; DAN; DMN; DTI; EEG; ICA; MEG; PET; RSN; Resting state functional connectivity; blood oxygen level-dependent; default mode network; diffuser tensor imaging; dorsal attention network; electroencephalography; fMRI; functional magnetic resonance imaging; independent component analysis; magnetoencephalography; positron emission tomography; resting state network; rs-fc

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