Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis

Morren, Geert; Wolf, Ursula; Lemmerling, Philippe; Wolf, Martin; Choi, Jee Hyun; Gratton, Enrico; Lathauwer, Lieven De; Huffel, Sabine Van

doi:10.1007/bf02351016

Cited by 112 publications

(106 citation statements)

References 27 publications

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“…A signal with a time frame in milliseconds has been reported [31]- [34]. Gated fNIRS using a similar system to that used in this study also showed a "fast signal" with a latency of approximately 100 ms (10 Hz) [24].…”

Section: Discussionsupporting

confidence: 60%

Detection of inter-hemispheric functional connectivity in motor cortex with coherence analysis

Varshney¹,

Liapounova²,

Golestani³

et al. 2012

J. Eur. Opt. Soc.-Rapid Publ.

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Functional near-infrared spectroscopy (fNIRS) is showing promise as an alternate method to fMRI for studying cortical function. Resting state studies in both methods are showing functional linkages. The strength of functional connections is typically quantified by the level of significance of the temporal synchrony between brain regions, termed resting-state functional connectivity. Coherence analysis of resting state allows for phase insensitive and frequency specific analysis. This paper provides a detailed method for undertaking fNIRS in combination with resting-state coherence analysis. We show that maps of inter-hemispheric resting-state functional connectivity between the motor cortices can be reliably generated, and the frequency responses (to 50 Hz) for both oxy-and deoxyhemoglobin. Frequencies of 0-0.1 Hz provide robust data as have been shown previously. Higher frequencies (up to 5 Hz) also exhibit high coherence. Deoxyhemoglobin also shows high coherence above 10Hz. Coherence is similar during both resting and task activated states. fNIRS allows for mapping cortical function and, in combination with coherence analysis, allows one to study variations in frequency response.

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Section: Discussionsupporting

confidence: 60%

Detection of inter-hemispheric functional connectivity in motor cortex with coherence analysis

Varshney¹,

Liapounova²,

Golestani³

et al. 2012

J. Eur. Opt. Soc.-Rapid Publ.

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“…How to combine GLM with a Kalman estimator and to analyze fNIRI data was shown by Hu et al (2010). Methods using independent component analysis (ICA) (Akgül et al, 2006;Katura et al, 2008;Kohno et al, 2007;Markham et al, 2009;Medvedev et al, 2008;Morren et al, 2004;Schelkanova and Toronov, 2012) or principal component analysis (PCA) H. Zhang et al, 2010;H.…”

Section: Multivariate Methods Of Typementioning

confidence: 99%

“…Up to now, only a few methods were presented and evaluated that address this task. As an early approach, Morren et al (2004) used a pulse oximeter placed on the finger to record the heartbeat waveform which was used as a reference signal in an adaptive filter to remove the component from the fNIRI signals. Obviously, this approach is only able to partly remove systemic activity types 3 (SC5) and 4 (SC6) (i.e.…”

Section: Multivariate Methods Of Typementioning

confidence: 99%

A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology

Scholkmann¹,

Kleiser²,

Metz³

et al. 2014

NeuroImage

1,531

1,394

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This year marks the 20th anniversary of functional near-infrared spectroscopy and imaging (fNIRS/fNIRI). As the vast majority of commercial instruments developed until now are based on continuous wave technology, the aim of this publication is to review the current state of instrumentation and methodology of continuous wave fNIRI. For this purpose we provide an overview of the commercially available instruments and address instrumental aspects such as light sources, detectors and sensor arrangements. Methodological aspects, algorithms to calculate the concentrations of oxy-and deoxyhemoglobin and approaches for data analysis are also reviewed. From the single-location measurements of the early years, instrumentation has progressed to imaging initially in two dimensions (topography) and then three (tomography). The methods of analysis have also changed tremendously, from the simple modified Beer-Lambert law to sophisticated image reconstruction and data analysis methods used today. Due to these advances, fNIRI has become a modality that is widely used in neuroscience research and several manufacturers provide commercial instrumentation. It seems likely that fNIRI will become a clinical tool in the foreseeable future, which will enable diagnosis in single subjects. This year marks the 20th anniversary of functional near-infrared spectroscopy and imaging (fNIRS/fNIRI). As the vast majority of commercial instruments developed until now are based on continuous wave technology, the aim of this publication is to review the current state of instrumentation and methodology of continuous wave fNIRI. For this purpose we provide an overview of the commercially available instruments and address instrumental aspects such as light sources, detectors and sensor arrangements. Methodological aspects, algorithms to calculate the concentrations of oxy-and deoxyhemoglobin and approaches for data analysis are also reviewed. From the single-location measurements of the early years, instrumentation has progressed to imaging initially in two dimensions (topography) and then three (tomography). The methods of analysis have also changed tremendously, from the simple modified Beer-Lambert law to sophisticated image reconstruction and data analysis methods used today. Due to these advances, fNIRI has become a modality that is widely used in neuroscience research and several manufacturers provide commercial instrumentation. It seems likely that fNIRI will become a clinical tool in the foreseeable future, which will enable diagnosis in single subjects. Contents

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“…Morren et al, used ICA based source separation in extracting the fast neuronal signal from a set of detectors placed 3 cm away from sources in a circumferential manner [11,26]. Similar to their study, the ICA algorithm demands statistical independence of data and linearity.…”

Section: Experimental Protocolmentioning

confidence: 99%

Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals

2006

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We address the problem of prototypical waveform extraction in cognitive experiments using functional near-infrared spectroscopy (fNIRS) signals. These waveform responses are evoked with visual stimuli provided in an oddball type experimental protocol. As the statistical signal-processing tool, we consider the linear signal space representation paradigm and use independent component analysis (ICA). The assumptions underlying ICA is discussed in the light of the signal measurement and generation mechanisms in the brain. The ICA-based waveform extraction is validated based both on its conformance to the parametric brain hemodynamic response (BHR) model and to the coherent averaging technique. We assess the intra-subject and inter-subject waveform and parameter variability.

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Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis

Cited by 112 publications

References 27 publications

Detection of inter-hemispheric functional connectivity in motor cortex with coherence analysis

Detection of inter-hemispheric functional connectivity in motor cortex with coherence analysis

A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology

Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals

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