Graph Theoretical Approach to Functional Connectivity in Prefrontal Cortex Via FNIRS

Overview

Journal Neurophotonics

Date 2017 Aug 26

PMID 28840159

Citations 10

Authors

Zahra Einalou

Keivan Maghooli

Seyaed Kamaledin Setarehdan

Ata Akin

Affiliations

Soon will be listed here.

Abstract

Functional near-infrared spectroscopy (fNIRS) has been proposed as an affordable, fast, and robust alternative to many neuroimaging modalities yet it still has long way to go to be adapted in the clinic. One request from the clinicians has been the delivery of a simple and straightforward metric (a so-called biomarker) from the vast amount of data a multichannel fNIRS system provides. We propose a simple-straightforward signal processing algorithm derived from [Formula: see text] data collected during a modified version of the color-word matching Stroop task that consists of three different conditions. The algorithm starts with a wavelet-transform-based preprocessing, then uses partial correlation analysis to compute the functional connectivity matrices at each condition and then computes the global efficiency values. To this end, a continuous wave 16 channels fNIRS device (ARGES Cerebro, Hemosoft Inc., Turkey) was used to measure the changes in [Formula: see text] concentrations from 12 healthy volunteers. We have considered 10% of strongest connections in each network. A strong Stroop interference effect was found between the incongruent against neutral condition ([Formula: see text]) while a similar significance was observed for the global efficiency values decreased from neutral to congruent to incongruent conditions [[Formula: see text], [Formula: see text]]. The findings bring us closer to delivering a biomarker derived from fNIRS data that can be reliably and easily adopted by the clinicians.

Citing Articles

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References

Akgul C, Sankur B, Akin A . Spectral analysis of event-related hemodynamic responses in functional near infrared spectroscopy. J Comput Neurosci. 2005; 18(1):67-83. DOI: 10.1007/s10827-005-5478-2. View

Langer N, Pedroni A, Jancke L . The problem of thresholding in small-world network analysis. PLoS One. 2013; 8(1):e53199. PMC: 3536769. DOI: 10.1371/journal.pone.0053199. View

Irani F, Platek S, Bunce S, Ruocco A, Chute D . Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders. Clin Neuropsychol. 2007; 21(1):9-37. DOI: 10.1080/13854040600910018. View

Ruocco A, Medaglia J, Tinker J, Ayaz H, Forman E, Newman C . Medial prefrontal cortex hyperactivation during social exclusion in borderline personality disorder. Psychiatry Res. 2010; 181(3):233-6. DOI: 10.1016/j.pscychresns.2009.12.001. View

Becerra L, Harris W, Grant M, George E, Boas D, Borsook D . Diffuse optical tomography activation in the somatosensory cortex: specific activation by painful vs. non-painful thermal stimuli. PLoS One. 2009; 4(11):e8016. PMC: 2778627. DOI: 10.1371/journal.pone.0008016. View

Gelinas C, Choiniere M, Ranger M, Denault A, Deschamps A, Johnston C . Toward a new approach for the detection of pain in adult patients undergoing cardiac surgery: near-infrared spectroscopy--a pilot study. Heart Lung. 2010; 39(6):485-93. DOI: 10.1016/j.hrtlng.2009.10.018. View

Schroeter M, Bucheler M, Muller K, Uludag K, Obrig H, Lohmann G . Towards a standard analysis for functional near-infrared imaging. Neuroimage. 2004; 21(1):283-90. DOI: 10.1016/j.neuroimage.2003.09.054. View

Palada I, Obad A, Bakovic D, Valic Z, Ivancev V, Dujic Z . Cerebral and peripheral hemodynamics and oxygenation during maximal dry breath-holds. Respir Physiol Neurobiol. 2007; 157(2-3):374-81. DOI: 10.1016/j.resp.2007.02.002. View

Niu H, Li Z, Liao X, Wang J, Zhao T, Shu N . Test-retest reliability of graph metrics in functional brain networks: a resting-state fNIRS study. PLoS One. 2013; 8(9):e72425. PMC: 3767699. DOI: 10.1371/journal.pone.0072425. View

10.

Chance B, Anday E, Nioka S, Zhou S, Hong L, Worden K . A novel method for fast imaging of brain function, non-invasively, with light. Opt Express. 2009; 2(10):411-23. DOI: 10.1364/oe.2.000411. View

11.

Wolf M, Ferrari M, Quaresima V . Progress of near-infrared spectroscopy and topography for brain and muscle clinical applications. J Biomed Opt. 2008; 12(6):062104. DOI: 10.1117/1.2804899. View

12.

Obrig H, Villringer A . Beyond the visible--imaging the human brain with light. J Cereb Blood Flow Metab. 2002; 23(1):1-18. DOI: 10.1097/01.WCB.0000043472.45775.29. View

13.

Akgul C, Akin A, Sankur B . Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals. Med Biol Eng Comput. 2006; 44(11):945-58. DOI: 10.1007/s11517-006-0116-3. View

14.

Kirilina E, Jelzow A, Heine A, Niessing M, Wabnitz H, Bruhl R . The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy. Neuroimage. 2012; 61(1):70-81. PMC: 3348501. DOI: 10.1016/j.neuroimage.2012.02.074. View

15.

Hlinka J, Palus M, Vejmelka M, Mantini D, Corbetta M . Functional connectivity in resting-state fMRI: is linear correlation sufficient?. Neuroimage. 2010; 54(3):2218-25. PMC: 4139498. DOI: 10.1016/j.neuroimage.2010.08.042. View

16.

Izzetoglu M, Izzetoglu K, Bunce S, Ayaz H, Devaraj A, Onaral B . Functional near-infrared neuroimaging. IEEE Trans Neural Syst Rehabil Eng. 2005; 13(2):153-9. DOI: 10.1109/TNSRE.2005.847377. View

17.

Zhang L, Sun J, Sun B, Luo Q, Gong H . Studying hemispheric lateralization during a Stroop task through near-infrared spectroscopy-based connectivity. J Biomed Opt. 2014; 19(5):57012. DOI: 10.1117/1.JBO.19.5.057012. View

18.

Platek S, Fonteyn L, Izzetoglu M, Myers T, Ayaz H, Li C . Functional near infrared spectroscopy reveals differences in self-other processing as a function of schizotypal personality traits. Schizophr Res. 2004; 73(1):125-7. DOI: 10.1016/j.schres.2004.09.024. View

19.

Mesquita R, Franceschini M, Boas D . Resting state functional connectivity of the whole head with near-infrared spectroscopy. Biomed Opt Express. 2011; 1(1):324-336. PMC: 3005169. DOI: 10.1364/BOE.1.000324. View

20.

Schroeter M, Zysset S, Kruggel F, von Cramon D . Age dependency of the hemodynamic response as measured by functional near-infrared spectroscopy. Neuroimage. 2003; 19(3):555-64. DOI: 10.1016/s1053-8119(03)00155-1. View