[4주차-2] Methods of Cognitive Neuroscience 2: A quantitative comparison of NIRS and fMRI across multiple cognitive tasks

A quantitative comparison of NIRS and fMRI across multiple cognitive tasks.

Xu Cui, Signe Bray, Daniel M Bryant, Gary H Glover, Allan L Reiss (2011)

NeuroImage 54 (4) p. 2808-21

http://dx.doi.org/10.1016/j.neuroimage.2010.10.069

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A quantitative comparison of NIRS and fMRI across multiple cognitive tasks

Abstract

Near infrared spectroscopy (NIRS) is ans increasingly popular technology for studying brain function. NIRS presents several advantages relative to functional magnetic resonance imaging(fMRI), such as measurement of concentration changes in both oxygenated and deoxygenated hemoglobin, finer temporal resolution, and ease of administration, as well as disadvantages, most prominently inferior spatial resolution and decreased signal-to-noise ratio (SNR). While fMRI has become the gold standard for in vivo imaging of the human brain, in practice NIRS is a more convenient and less expensive technology than fMRI. It is therefore of interest to many researchers how NIRS compares to fMRI in studies of brain function. in the present study we scanned participants with simultaneous NIRS and fMRI on a battery of cognitive tasks, placing NIRS probes over both frontal and parietal brain regions. We performed detailed comparisons of the signals in both temporal and spatial domains. We found that NIRS signals have significantly weaker SNR, but are nonetheless often highly correalted with fMRI measurements. Both SNR and the distance between the scalp and the brain contributed to variability in the NIRS/fMRI correlations. In the spatial domain, we found that a photon path forming an ellipse between the NIRS emitter and detector correlated most strongly with the BOLD response. Taken together these findings suggest that, while NIRS can be an appropriate substitute for fMIR for studying brain activity related to cognitive tasks, care should be taken when designing studies with NIRS to ensure that: 1) the spatial resolution is adequate for answering the question of interest and 2) the design accounts for weaker SNR, especially in brain regions more distal from the scalp
 

Introduction

NIRS
- 단점: SNR이 굉장히 낮고, 노이즈가 많고, 공간 해상도가 fMRI에 비해서 낮음.

fMRI
- 장점: 해상도가 높다
- 단점: 비싸고, 적용 task가 한정적이다.

fMRI는 MRI와는 다른데, MRI의 방법을 그대로 적용 할 수 있는지의 논쟁이 남아 있음
fMRI를 맹신하면 안되고, NIRS와 fMRI를 같이 측정하는 것은 좋다(저자의 입장).

fMRI 데이터 수집
- 특정 이벤트에 맞춘게 아니라 그 블럭의 크기에 맞춰서 수행


Methods

Participants

Experimental procedure

Task descriptions

Finger tapping (tap)
Go/no-go task (nog)
Judgment of line orientation task (jlo)
Visuospatial N-back working memory task (vis)

NIRS data acquisition

fMRI data acquisition

Identifying the channel locations

Scalp–brain distance

Temporal analysis

NIRS data processing
fMRI preprocessing
Region of interest (ROI)
fMRI–NIRS correlation
Noise level in NIRS signal
Contrast-to-noise ratio (CNR)

Spatial analysis

Finding the local best correlating voxel (LBCV)
Finding the optimal spherical volume
Finding the optimal spherical shell
Finding the optimal elliptical ring

General linear model (GLM)-based analysis in each modality

fMRI
NIRS

Results

Temporal analysis

fMRI–NIRS correlations show wide variability
Cognitive task does not affect NIRS/BOLD correlations
Longer scalp–brain distance degrades NIRS–fMRI correlations
Higher CNR yields higher NIRS–fMRI correlations

Spatial analysis

Spatial properties of local best correlating voxels (LBCVs)
Determining the optimal ROI shape

GLM-based analyses in each modality

Discussion 


연구 내용 자체로는 빵점. 이지만 세부적인 측정을 했기 때문에 의의가 있음.