Literature DB >> 22036999

Quantification of the cortical contribution to the NIRS signal over the motor cortex using concurrent NIRS-fMRI measurements.

Louis Gagnon1, Meryem A Yücel, Mathieu Dehaes, Robert J Cooper, Katherine L Perdue, Juliette Selb, Theodore J Huppert, Richard D Hoge, David A Boas.   

Abstract

Near-Infrared Spectroscopy (NIRS) measures the functional hemodynamic response occurring at the surface of the cortex. Large pial veins are located above the surface of the cerebral cortex. Following activation, these veins exhibit oxygenation changes but their volume likely stays constant. The back-reflection geometry of the NIRS measurement renders the signal very sensitive to these superficial pial veins. As such, the measured NIRS signal contains contributions from both the cortical region as well as the pial vasculature. In this work, the cortical contribution to the NIRS signal was investigated using (1) Monte Carlo simulations over a realistic geometry constructed from anatomical and vascular MRI and (2) multimodal NIRS-BOLD recordings during motor stimulation. A good agreement was found between the simulations and the modeling analysis of in vivo measurements. Our results suggest that the cortical contribution to the deoxyhemoglobin signal change (ΔHbR) is equal to 16-22% of the cortical contribution to the total hemoglobin signal change (ΔHbT). Similarly, the cortical contribution of the oxyhemoglobin signal change (ΔHbO) is equal to 73-79% of the cortical contribution to the ΔHbT signal. These results suggest that ΔHbT is far less sensitive to pial vein contamination and therefore, it is likely that the ΔHbT signal provides better spatial specificity and should be used instead of ΔHbO or ΔHbR to map cerebral activity with NIRS. While different stimuli will result in different pial vein contributions, our finger tapping results do reveal the importance of considering the pial contribution.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22036999      PMCID: PMC3279595          DOI: 10.1016/j.neuroimage.2011.10.054

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  28 in total

1.  Factors affecting the accuracy of near-infrared spectroscopy concentration calculations for focal changes in oxygenation parameters.

Authors:  Gary Strangman; Maria Angela Franceschini; David A Boas
Journal:  Neuroimage       Date:  2003-04       Impact factor: 6.556

2.  Discrepancies between BOLD and flow dynamics in primary and supplementary motor areas: application of the balloon model to the interpretation of BOLD transients.

Authors:  Takayuki Obata; Thomas T Liu; Karla L Miller; Wen Ming Luh; Eric C Wong; Lawrence R Frank; Richard B Buxton
Journal:  Neuroimage       Date:  2004-01       Impact factor: 6.556

Review 3.  Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders.

Authors:  Farzin Irani; Steven M Platek; Scott Bunce; Anthony C Ruocco; Douglas Chute
Journal:  Clin Neuropsychol       Date:  2007-01       Impact factor: 3.535

4.  Dynamics of blood flow and oxygenation changes during brain activation: the balloon model.

Authors:  R B Buxton; E C Wong; L R Frank
Journal:  Magn Reson Med       Date:  1998-06       Impact factor: 4.668

5.  Estimation of optical pathlength through tissue from direct time of flight measurement.

Authors:  D T Delpy; M Cope; P van der Zee; S Arridge; S Wray; J Wyatt
Journal:  Phys Med Biol       Date:  1988-12       Impact factor: 3.609

6.  System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination.

Authors:  M Cope; D T Delpy
Journal:  Med Biol Eng Comput       Date:  1988-05       Impact factor: 2.602

7.  A theoretical framework for estimating cerebral oxygen metabolism changes using the calibrated-BOLD method: modeling the effects of blood volume distribution, hematocrit, oxygen extraction fraction, and tissue signal properties on the BOLD signal.

Authors:  Valerie E M Griffeth; Richard B Buxton
Journal:  Neuroimage       Date:  2011-06-06       Impact factor: 6.556

8.  Near infrared spectroscopy (NIRS): a new tool to study hemodynamic changes during activation of brain function in human adults.

Authors:  A Villringer; J Planck; C Hock; L Schleinkofer; U Dirnagl
Journal:  Neurosci Lett       Date:  1993-05-14       Impact factor: 3.046

9.  A flow velocity zeugmatographic interlace for NMR imaging in humans.

Authors:  P R Moran
Journal:  Magn Reson Imaging       Date:  1982       Impact factor: 2.546

10.  Estimating cerebral oxygen metabolism from fMRI with a dynamic multicompartment Windkessel model.

Authors:  Theodore J Huppert; Monica S Allen; Solomon G Diamond; David A Boas
Journal:  Hum Brain Mapp       Date:  2009-05       Impact factor: 5.038

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  64 in total

1.  Optimized multimodal functional magnetic resonance imaging/near-infrared spectroscopy probe for ultrahigh-resolution mapping.

Authors:  Lia Maria Hocke; Kenroy Cayetano; Yunjie Tong; Blaise Frederick
Journal:  Neurophotonics       Date:  2015-12-10       Impact factor: 3.593

2.  Tutorial on platform for optical topography analysis tools.

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Journal:  Neurophotonics       Date:  2016-01-11       Impact factor: 3.593

3.  Online binary decision decoding using functional near-infrared spectroscopy for the development of brain-computer interface.

Authors:  Noman Naseer; Melissa Jiyoun Hong; Keum-Shik Hong
Journal:  Exp Brain Res       Date:  2013-11-21       Impact factor: 1.972

4.  Linear regression models and k-means clustering for statistical analysis of fNIRS data.

Authors:  Viola Bonomini; Lucia Zucchelli; Rebecca Re; Francesca Ieva; Lorenzo Spinelli; Davide Contini; Anna Paganoni; Alessandro Torricelli
Journal:  Biomed Opt Express       Date:  2015-01-28       Impact factor: 3.732

5.  Quantification of extra-cerebral and cerebral hemoglobin concentrations during physical exercise using time-domain near infrared spectroscopy.

Authors:  Héloïse Auger; Louis Bherer; Étienne Boucher; Richard Hoge; Frédéric Lesage; Mathieu Dehaes
Journal:  Biomed Opt Express       Date:  2016-09-01       Impact factor: 3.732

6.  Method for the discrimination of superficial and deep absorption variations by time domain fNIRS.

Authors:  Lucia Zucchelli; Davide Contini; Rebecca Re; Alessandro Torricelli; Lorenzo Spinelli
Journal:  Biomed Opt Express       Date:  2013-11-20       Impact factor: 3.732

7.  Physiological denoising of BOLD fMRI data using Regressor Interpolation at Progressive Time Delays (RIPTiDe) processing of concurrent fMRI and near-infrared spectroscopy (NIRS).

Authors:  Blaise deB Frederick; Lisa D Nickerson; Yunjie Tong
Journal:  Neuroimage       Date:  2012-02-09       Impact factor: 6.556

8.  Cortical activation patterns to spatially presented pure tone stimuli with different intensities measured by functional near-infrared spectroscopy.

Authors:  Günther Bauernfeind; Selina C Wriessnegger; Sabine Haumann; Thomas Lenarz
Journal:  Hum Brain Mapp       Date:  2018-03-08       Impact factor: 5.038

9.  Brain activation patterns underlying upper limb bilateral motor coordination in unilateral cerebral palsy: an fNIRS study.

Authors:  Ana Carolina de Campos; Theresa Sukal-Moulton; Theodore Huppert; Katharine Alter; Diane L Damiano
Journal:  Dev Med Child Neurol       Date:  2020-02-07       Impact factor: 5.449

10.  Increased prefrontal oxygenation related to distractor-resistant working memory in children with attention-deficit/hyperactivity disorder (ADHD).

Authors:  Satoshi Tsujimoto; Akira Yasumura; Yushiro Yamashita; Miyuki Torii; Makiko Kaga; Masumi Inagaki
Journal:  Child Psychiatry Hum Dev       Date:  2013-10
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