The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Functional near‐infrared optical imaging: Utility and limitations in human brain mapping
Abstract
Abstract Although near‐infrared spectroscopy (NIRS) was developed as a tool for clinical monitoring of tissue oxygenation, it also has potential for neuroimaging. A wide range of different NIRS instruments have been developed, and instruments for continuous intensity measurements with fixed spacing [continuous wave (CW)‐type instruments], which are most readily available commercially, allow us to see dynamic changes in regional cerebral blood flow in real time. However, quantification, which is necessary for imaging of brain functions, is impossible with these CW‐type instruments. Over the past 20 years, many different approaches to quantification have been tried, and several multichannel time‐resolved and frequency‐domain instruments are now in common use for imaging. Although there are still many problems with this technique, such as incomplete knowledge of how light propagates through the head, NIRS will not only open a window on brain physiology for subjects who have rarely been examined until now, but also provide a new direction for functional mapping studies.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Fox, P. T., & Raichle, M. E. (1986) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.83.4.1140 · Cited by 2,056
Cited by
Human brain mechanisms of pain perception and regulation in health and disease
Apkarian, A. V., Bushnell, M. C., Treede, R., & Zubieta, J. (2005) · European Journal of Pain · doi:10.1016/j.ejpain.2004.11.001 · Cited by 3,126
Ferrari, M., & Quaresima, V. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.049 · Cited by 2,274
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
Principles, Techniques, and Limitations of Near Infrared Spectroscopy
Ferrari, M., Mottola, L., & Quaresima, V. (2004) · Canadian Journal of Applied Physiology · doi:10.1139/h04-031 · Cited by 997
Using Fiberless, Wearable fNIRS to Monitor Brain Activity in Real-world Cognitive Tasks
Pinti, P., Aichelburg, C., Lind, F., Power, S., Swingler, E., Merla, A., Hamilton, A., Gilbert, S., Burgess, P., & Tachtsidis, I. (2015) · Journal of Visualized Experiments · doi:10.3791/53336 · Cited by 169
Metadata
- Authors
- Hoshi, Y.
- Venue
- Psychophysiology
- Publisher
- Wiley
- Published
- 2003-06-10
- Volume
- 40
- Issue
- 4
- Pages
- 511-520
- ISSN
- 0048-5772 (ISSN-L)
- 1469-8986
- OpenAlex
- W2027078803
- Cited by
- 532
- References
- 1
- FWCI
- 10.60
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
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.
