Thalamo-cortical network activity between migraine attacks: Insights from MRI-based microstructural and functional resting-state network correlation analysis

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Abstract

Background

Resting state magnetic resonance imaging allows studying functionally interconnected brain networks. Here we were aimed to verify functional connectivity between brain networks at rest and its relationship with thalamic microstructure in migraine without aura (MO) patients between attacks.

Methods

Eighteen patients with untreated MO underwent 3 T MRI scans and were compared to a group of 19 healthy volunteers (HV). We used MRI to collect resting state data among two selected resting state networks, identified using group independent component (IC) analysis. Fractional anisotropy (FA) and mean diffusivity (MD) values of bilateral thalami were retrieved from a previous diffusion tensor imaging study on the same subjects and correlated with resting state ICs Z-scores.

Results

In comparison to HV, in MO we found significant reduced functional connectivity between the default mode network and the visuo-spatial system. Both HV and migraine patients selected ICs Z-scores correlated negatively with FA values of the thalamus bilaterally.

Conclusions

The present results are the first evidence supporting the hypothesis that an abnormal resting within networks connectivity associated with significant differences in baseline thalamic microstructure could contribute to interictal migraine pathophysiology.

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Most cited references 53

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Searching for a baseline: functional imaging and the resting human brain.

Debra A Gusnard, Marcus E. Raichle (2001)

Functional brain imaging in humans has revealed task-specific increases in brain activity that are associated with various mental activities. In the same studies, mysterious, task-independent decreases have also frequently been encountered, especially when the tasks of interest have been compared with a passive state, such as simple fixation or eyes closed. These decreases have raised the possibility that there might be a baseline or resting state of brain function involving a specific set of mental operations. We explore this possibility, including the manner in which we might define a baseline and the implications of such a baseline for our understanding of brain function.

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Electrophysiological signatures of resting state networks in the human brain.

D. Mantini, M G Perrucci, C Del Gratta … (2007)

Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1-80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies.

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A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

Madiha J Jafri, Godfrey D. Pearlson, Michael Stevens … (2008)

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in healthy individuals as well as in patients with brain disorders. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject's ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients.

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Author and article information

Contributors

Gianluca Coppola: +39 06 85356727 , gianluca.coppola@gmail.com

Journal

Journal ID (nlm-ta): J Headache Pain

Journal ID (iso-abbrev): J Headache Pain

Title: The Journal of Headache and Pain

Publisher: Springer Milan (Milan )

ISSN (Print): 1129-2369

ISSN (Electronic): 1129-2377

Publication date (Electronic): 24 October 2016

Publication date PMC-release: 24 October 2016

Publication date Collection: 2016

Volume: 17

Issue: 1

Electronic Location Identifier: 100

Affiliations

[1 ]Research Unit of Neurophysiology of Vision and Neurophthalmology, G.B. Bietti Foundation-IRCCS, Via Livenza 3, 00198 Rome, Italy

[2 ]Department of Neurology and Psychiatry, Neuroradiology Section, “Sapienza” University of Rome, Rome, Italy

[3 ]Department of Medico-Surgical Sciences and Biotechnologies, Neurology Section, “Sapienza” University of Rome, Rome, Italy

[4 ]Don Carlo Gnocchi Onlus Foundation, Milan, Italy

[5 ]Laboratory of Psychophysiology, Psychiatric Clinic, Department of Systems Medicine, University of Rome “Tor Vergata”, Rome, Italy

[6 ]Department of Medico-Surgical Sciences and Biotechnologies, “Sapienza” University of Rome Polo Pontino, Latina, Italy

[7 ]IRCCS Neuromed, Pozzilli, (IS) Italy

[8 ]Headache Research Unit, Department of Neurology-CHR Citadelle, University of Liège, Liège, Belgium

Article

Publisher ID: 693

DOI: 10.1186/s10194-016-0693-y

PMC ID: 5078119

PubMed ID: 27778244

SO-VID: a208bd2d-08a3-4fc5-a9b9-419fb20a32ae

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

History

Date received : 12 March 2016

Date accepted : 18 October 2016

Funding

Funded by: Italian Ministry of Health

Funded by: Fondazione Roma

Custom metadata

ScienceOpen disciplines: Anesthesiology & Pain management

Keywords: migraine,thalamus,resting state,fractional anisotropy,magnetic resonance imaging

Data availability:

ScienceOpen disciplines: Anesthesiology & Pain management

Keywords: migraine, thalamus, resting state, fractional anisotropy, magnetic resonance imaging

Thalamo-cortical network activity between migraine attacks: Insights from MRI-based microstructural and functional resting-state network correlation analysis

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Abstract

Background

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Conclusions

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Karger: Neurology and Neuroscience

Most cited references 53

Searching for a baseline: functional imaging and the resting human brain.

Electrophysiological signatures of resting state networks in the human brain.

A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

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