Fusion of fNIRS and fMRI data: identifying when and where hemodynamic signals are changing in human brains

Yuan, Zhen; Ye, Jong-Chul

doi:10.3389/fnhum.2013.00676

Cited by 45 publications

(34 citation statements)

References 22 publications

(28 reference statements)

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“…The corresponding relationship between fMRI BOLD and NIRS time courses has been shown by prior works with simultaneous measurement of brain hemodynamic signals using these two techniques. [45][46][47][48] The spontaneous oscillations in CTOI most likely reflected the oscillations in BOLD signal, which was obtained from the same subjects in this study. Therefore, the high coherence observed between the changes in MABP, CBFV, and CTOI suggests the impact of changes in MABP and CBFV on rs-fMRI BOLD signal.…”

Section: Discussionmentioning

confidence: 99%

Vascular Coupling in Resting-State FMRI: Evidence from Multiple Modalities

Zhu

Tarumi

Khan

et al. 2015

J Cereb Blood Flow Metab

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Resting-state functional magnetic resonance imaging (rs-fMRI) provides a potential to understand intrinsic brain functional connectivity. However, vascular effects in rs-fMRI are still not fully understood. Through multiple modalities, we showed marked vascular signal fluctuations and high-level coupling among arterial pressure, cerebral blood flow (CBF) velocity and brain tissue oxygenation at o0.08 Hz. These similar spectral power distributions were also observed in blood oxygen level-dependent (BOLD) signals obtained from six representative regions of interest (ROIs). After applying brain global, white-matter, cerebrospinal fluid (CSF) mean signal regressions and low-pass filtering ( o0.08 Hz), the spectral power of BOLD signal was reduced by 55.6% to 64.9% in all ROIs (P = 0.011 to 0.001). The coherence of BOLD signal fluctuations between an ROI pair within a same brain network was reduced by 9.9% to 20.0% (P = 0.004 to o 0.001), but a larger reduction of 22.5% to 37.3% (P = 0.032 to o0.001) for one not in a same network. Global signal regression overall had the largest impact in reducing spectral power (by 52.2% to 61.7%) and coherence, relative to the other three preprocessing steps. Collectively, these findings raise a critical question of whether a large portion of rs-fMRI signals can be attributed to the vascular effects produced from upstream changes in cerebral hemodynamics.

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Section: Discussionmentioning

confidence: 99%

Vascular Coupling in Resting-State FMRI: Evidence from Multiple Modalities

Zhu

Tarumi

Khan

et al. 2015

J Cereb Blood Flow Metab

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“…The optimization of the weight matrix is achieved by weight updating rule: [68]. The initial value for W, W(0) is a matrix composed of random vectors [69]. In our fusion approach, we assumed that the sources associated with EEG and fNIRS data modulated the same way across all subjects.…”

Section: Eeg and Fnirs Fusionmentioning

confidence: 99%

Mental stress assessment using simultaneous measurement of EEG and fNIRS

Al-Shargie

Kiguchi

Badruddin

et al. 2016

Biomed. Opt. Express

215

159

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Previous studies reported mental stress as one of the major contributing factors leading to various diseases such as heart attack, depression and stroke. An accurate stress assessment method may thus be of importance to clinical intervention and disease prevention. We propose a joint independent component analysis (jICA) based approach to fuse simultaneous measurement of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) on the prefrontal cortex (PFC) as a means of stress assessment. For the purpose of this study, stress was induced by using an established mental arithmetic task under time pressure with negative feedback. The induction of mental stress was confirmed by salivary alpha amylase test. Experiment results showed that the proposed fusion of EEG and fNIRS measurements improves the classification accuracy of mental stress by +3.4% compared to EEG alone and +11% compared to fNIRS alone. Similar improvements were also observed in sensitivity and specificity of proposed approach over unimodal EEG/fNIRS. Our study suggests that combination of EEG (frontal alpha rhythm) and fNIRS (concentration change of oxygenated hemoglobin) could be a potential means to assess mental stress objectively. References and links1. J. Decker, "The Stress Syndrome," Am. J. Nurs. 65(3), 97-99 (1965). 2. L. R. Murphy, "Stress management in work settings: a critical review of the health effects," Am. J. Health Promot. 11(2), 112-135 (1996). 3. B. Czéh, T. Michaelis, T. Watanabe, J. Frahm, G. de Biurrun, M. van Kampen, A. Bartolomucci, and E. Fuchs, "Stress-induced changes in cerebral metabolites, hippocampal volume, and cell proliferation are prevented by antidepressant treatment with tianeptine," Proc. Natl. Acad. Sci. U.S.A. 98(22), 12796-12801 (2001). 4. C. M. Vander Weele, C. Saenz, J. Yao, S. S. Correia, and K. A. Goosens, "Restoration of hippocampal growth hormone reverses stress-induced hippocampal impairment," Front. Behav. Neurosci. 7, 66 (2013). 5. A. Vyas, R. Mitra, B. S. Shankaranarayana Rao, and S. Chattarji, "Chronic stress induces contrasting patterns of dendritic remodeling in hippocampal and amygdaloid neurons," J. Neurosci. 22(15), 6810-6818 (2002). 6. B. S. McEwen, "Central effects of stress hormones in health and disease: Understanding the protective and damaging effects of stress and stress mediators," Eur. J. Pharmacol. 583(2-3), 174-185 (2008). 7. P. C. Strike and A. Steptoe, "Systematic review of mental stress-induced myocardial ischaemia," Eur. Heart J.24(8), 690-703 (2003). 8. A. Tsutsumi, K. Kayaba, and S. Ishikawa, "Impact of occupational stress on stroke across occupational classes and genders," Soc. Sci. Med. 72(10), 1652-1658 (2011). 9. R. A. Ajjan and P. J. Grant, "Cardiovascular disease prevention in patients with type 2 diabetes: The role of oral anti-diabetic agents," Diab. Vasc. Dis. Res. 3(3), 147-158 (2006). 10. C. Hammen, "Stress and depression," Annu. Rev. Clin. Psychol. 1(1), 293-319 (2005 532-545 (1972). 22. T. G. Vrijkotte, L. J. van Doornen, and E. ...

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“…HbO Δ is then decomposed by ICA, estimating the optimal inverse of the mixing matrix A, and a set of source time courses S. In terms of ICA estimation, 2 HbO Δ is further written, AS HbO 2 = Δ (4) in which A is the K-by-N mixing matrix, N is the number of unmixed sources and S are the N-by-M component time courses. Typically we utilize K ≥ N so that A is of full rank.…”

Section: B Independent Component Analysismentioning

confidence: 99%

“…Since the mid-1970, fNIRS has been developing a noninvasive technique to investigate brain cerebral hemodynamic levels associated with brain activity under different stimuli by measuring the absorption coefficient of the near-infrared light between 650 nm and 950 nm [1][2][3][4][5]. Compared to other functional imaging modalities, such as fMRI and PET, fNIRS has the advantages of portable, convenience and low cost, and more importantly, it offers unsurpassed high temporal resolution and quantitative information for both oxyhemoglobin and deoxyhemoglobin, which is essential for revealing rapid changes of dynamic patterns of brain activities including changes of blood oxygen, blood volume and blood flow.…”

Section: Introductionmentioning

confidence: 99%

Concurrent spatiotemporal analysis of functional near-infrared spectroscopy data using independent component analysis

Yuan¹

2013

2013 6th International Congress on Image and Signal Processing (CISP)

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Functional near infrared spectroscopy (fNIRS) recordings are the hemodynamic signals that come from the latent neural sources and physiological noise that are spatially and temporally mixed across the brain. The purpose of this work was to extract the temporal characteristics and the spatial activation patterns of human brains captured by independent component analysis (ICA). Both of the raw and filtered fNIRS datasets are processed with ICA. In particular the temporal components and spatial activity maps identified by ICA for a right finger tapping task were investigated in detail.

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Fusion of fNIRS and fMRI data: identifying when and where hemodynamic signals are changing in human brains

Cited by 45 publications

References 22 publications

Vascular Coupling in Resting-State FMRI: Evidence from Multiple Modalities

Vascular Coupling in Resting-State FMRI: Evidence from Multiple Modalities

Mental stress assessment using simultaneous measurement of EEG and fNIRS

Concurrent spatiotemporal analysis of functional near-infrared spectroscopy data using independent component analysis

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