The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Statistical analysis of fNIRS data: A comprehensive review
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Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
Small sample inference for fixed effects from restricted maximum likelihood
Kenward, M. G., & Roger, J. H. (1997) · Biometrics · doi:10.2307/2533558 · Cited by 4,552 · cited 1×
“This idea is the so-called restricted maximum likelihood (ReML) method (Friston et al., 2011; Graser et al., 1987; Harville, 1977; Kenward and Roger, 1997; Searle, 1979).”
Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
Harville, D. A. (1977) · Journal of the American Statistical Association · doi:10.1080/01621459.1977.10480998 · Cited by 2,667
HomER: A review of time-series analysis methods for near-infrared spectroscopy of the brain
Huppert, T. J., Diamond, S. G., Franceschini, M. A., & Boas, D. A. (2009) · Applied Optics · doi:10.1364/ao.48.00d280 · Cited by 1,817
Detecting activations in PET and fMRI: levels of inference and power
Friston, K. J., Holmes, A., Poline, J.-B., Price, C. J., & Frith, C. D. (1996) · NeuroImage · doi:10.1006/nimg.1996.0074 · Cited by 1,148 · cited 1×
“Recall that SPM for fMRI analysis assumes that the residuals after the GLM fitting are dense samples on lattice representations from an underlying continuous Gaussian random field (Friston et al., 1996) due to the Gaussian kernel smoothing .”
Cooper, R. J., Selb, J., Gagnon, L., Phillip, D., Schytz, H. W., Iversen, H. K., Ashina, M., & Boas, D. A. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00147 · Cited by 421
Mehagnoul‐Schipper, D. J., van der Kallen, B. F. W., Colier, W. N. J. M., van der Sluijs, M. C., van Erning, L. J. T. O., Thijssen, H. O. M., Oeseburg, B., Hoefnagels, W. H. L., & Jansen, R. W. M. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10026 · Cited by 264
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Cited by
Tachtsidis, I., & Scholkmann, F. (2016) · Neurophotonics · doi:10.1117/1.nph.3.3.031405 · Cited by 607
Twenty years of functional near-infrared spectroscopy: introduction for the special issue
Boas, D. A., Elwell, C. E., Ferrari, M., & Taga, G. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.033 · Cited by 561
Herold, F., Wiegel, P., Scholkmann, F., & Müller, N. (2018) · Journal of Clinical Medicine · doi:10.3390/jcm7120466 · Cited by 482
Pinti, P., Scholkmann, F., Hamilton, A., Burgess, P., & Tachtsidis, I. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00505 · Cited by 464
A Review on the Use of Wearable Functional Near‐Infrared Spectroscopy in Naturalistic Environments
Pinti, P., Aichelburg, C., Gilbert, S., Hamilton, A., Hirsch, J., Burgess, P., & Tachtsidis, I. (2018) · Japanese Psychological Research · doi:10.1111/jpr.12206 · Cited by 325
Metadata
- Authors
- Tak, S., & Ye, J. C.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 85
- Pages
- 72-91
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1987143349
- Cited by
- 465
- References
- 10
- FWCI
- 10.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- Tak, S., & Ye, J. C. (2014). Statistical analysis of fNIRS data: A comprehensive review. NeuroImage. https://doi.org/10.1016/j.neuroimage.2013.06.016
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
