Literature DB >> 33727581

Deconvolution of hemodynamic responses along the cortical surface using personalized functional near infrared spectroscopy.

A Machado1, Z Cai2,3, T Vincent2,3, G Pellegrino4, J-M Lina5,6,7, E Kobayashi4, C Grova2,3,4,6.   

Abstract

In functional near infrared spectroscopy (fNIRS), deconvolution analysis of oxy and deoxy-hemoglobin concentration changes allows estimating specific hemodynamic response functions (HRF) elicited by neuronal activity, taking advantage of the fNIRS excellent temporal resolution. Diffuse optical tomography (DOT) is also becoming the new standard reconstruction procedure as it is more accurate than the modified Beer Lambert law approach at the sensor level. The objective of this study was to assess the relevance of HRF deconvolution after DOT constrained along the cortical surface. We used local personalized fNIRS montages which consists in optimizing the position of fNIRS optodes to ensure maximal sensitivity to subject specific target brain regions. We carefully evaluated the accuracy of deconvolution when applied after DOT, using realistic simulations involving several HRF models at different signal to noise ratio (SNR) levels and on real data related to motor and visual tasks in healthy subjects and from spontaneous pathological activity in one patient with epilepsy. We demonstrated that DOT followed by deconvolution was able to accurately recover a large variability of HRFs over a large range of SNRs. We found good performances of deconvolution analysis for SNR levels usually encountered in our applications and we were able to reconstruct accurately the temporal dynamics of HRFs in real conditions.

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Year:  2021        PMID: 33727581      PMCID: PMC7966407          DOI: 10.1038/s41598-021-85386-0

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  71 in total

1.  Classical and Bayesian inference in neuroimaging: theory.

Authors:  K J Friston; W Penny; C Phillips; S Kiebel; G Hinton; J Ashburner
Journal:  Neuroimage       Date:  2002-06       Impact factor: 6.556

2.  How short is short? Optimum source-detector distance for short-separation channels in functional near-infrared spectroscopy.

Authors:  Sabrina Brigadoi; Robert J Cooper
Journal:  Neurophotonics       Date:  2015-05-26       Impact factor: 3.593

Review 3.  Statistical analysis of fNIRS data: a comprehensive review.

Authors:  Sungho Tak; Jong Chul Ye
Journal:  Neuroimage       Date:  2013-06-15       Impact factor: 6.556

4.  Analysis of task-evoked systemic interference in fNIRS measurements: insights from fMRI.

Authors:  Sinem B Erdoğan; Meryem A Yücel; Ata Akın
Journal:  Neuroimage       Date:  2013-10-19       Impact factor: 6.556

5.  A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans.

Authors:  T J Huppert; R D Hoge; S G Diamond; M A Franceschini; D A Boas
Journal:  Neuroimage       Date:  2005-11-21       Impact factor: 6.556

6.  The variability of human, BOLD hemodynamic responses.

Authors:  G K Aguirre; E Zarahn; M D'esposito
Journal:  Neuroimage       Date:  1998-11       Impact factor: 6.556

7.  Commentary on the statistical properties of noise and its implication on general linear models in functional near-infrared spectroscopy.

Authors:  Theodore J Huppert
Journal:  Neurophotonics       Date:  2016-03-02       Impact factor: 3.593

8.  BOLD changes occur prior to epileptic spikes seen on scalp EEG.

Authors:  Colin S Hawco; Andrew P Bagshaw; Yingli Lu; François Dubeau; Jean Gotman
Journal:  Neuroimage       Date:  2007-01-25       Impact factor: 6.556

9.  Statistical analysis of high density diffuse optical tomography.

Authors:  Mahlega S Hassanpour; Brian R White; Adam T Eggebrecht; Silvina L Ferradal; Abraham Z Snyder; Joseph P Culver
Journal:  Neuroimage       Date:  2013-06-02       Impact factor: 6.556

10.  The NIRS Analysis Package: noise reduction and statistical inference.

Authors:  Tomer Fekete; Denis Rubin; Joshua M Carlson; Lilianne R Mujica-Parodi
Journal:  PLoS One       Date:  2011-09-02       Impact factor: 3.240

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  2 in total

1.  Diffuse optical reconstructions of functional near infrared spectroscopy data using maximum entropy on the mean.

Authors:  Zhengchen Cai; Alexis Machado; Rasheda Arman Chowdhury; Amanda Spilkin; Thomas Vincent; Ümit Aydin; Giovanni Pellegrino; Jean-Marc Lina; Christophe Grova
Journal:  Sci Rep       Date:  2022-02-10       Impact factor: 4.379

2.  Extracting electrophysiological correlates of functional magnetic resonance imaging data using the canonical polyadic decomposition.

Authors:  Dylan Mann-Krzisnik; Georgios D Mitsis
Journal:  Hum Brain Mapp       Date:  2022-05-14       Impact factor: 5.399

  2 in total

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