The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping
Open accessAbstract
Functional neuroimaging commands a dominant role in current neuroscience research. However its use in bedside clinical and certain neuro-scientific studies has been limited because the current tools lack the combination of being non-invasive, non-ionizing and portable while maintaining moderate resolution and localization accuracy. Optical neuroimaging satisfies many of these requirements, but, until recent advances in high-density diffuse optical tomography (HD-DOT), has been hampered by limited resolution. While early results of HD-DOT have been promising, a quantitative voxel-wise comparison and validation of HD-DOT against the gold standard of functional magnetic resonance imaging (fMRI) has been lacking. Herein, we provide such an analysis within the visual cortex using matched visual stimulation protocols in a single group of subjects (n=5) during separate HD-DOT and fMRI scanning sessions. To attain the needed voxel-to-voxel co-registration between HD-DOT and fMRI image spaces, we implemented subject-specific head modeling that incorporated MRI anatomy, detailed segmentation, and alignment of source and detector positions. Comparisons of the visual responses found an average localization error between HD-DOT and fMRI of 4.4 +/− 1 mm, significantly less than the average distance between cortical gyri. This specificity demonstrates that HD-DOT has sufficient image quality to be useful as a surrogate for fMRI.
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
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783
Functional mapping of the human visual cortex by magnetic resonance imaging
Belliveau, J. W., Kennedy, D. N., McKinstry, R. C., Buchbinder, B. R., Weisskoff, R. M., Cohen, M. S., Vevea, J. M., Brady, T. J., & Rosen, B. R. (1991) · Science · doi:10.1126/science.1948051 · Cited by 1,883
Mapping human visual cortex with positron emission tomography
Fox, P. T., Mintun, M. A., Raichle, M. E., Miezin, F. M., Allman, J. M., & Van Essen, D. C. (1986) · Nature · doi:10.1038/323806a0 · Cited by 422 · cited 2×
“Visual activations were used because they have served extensively as a substrate for validation by other neuroimaging methodologies (Belliveau et al., 1991; Engel et al., 1997; Fox et al., 1986; Fox et al., 1985) and because the structure and function of the visual cortex has been comprehensively mapped via invasive a…”
Cited by
Semantic reconstruction of continuous language from non-invasive brain recordings
Tang, J., LeBel, A., Jain, S., & Huth, A. G. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01304-9 · Cited by 442
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
Hirsch, J., Zhang, X., Noah, J. A., & Ono, Y. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.018 · Cited by 236
A cross-brain neural mechanism for human-to-human verbal communication
Hirsch, J., Adam Noah, J., Zhang, X., Dravida, S., & Ono, Y. (2018) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsy070 · Cited by 114
Real-time eye-to-eye contact is associated with cross-brain neural coupling in angular gyrus
Noah, J. A., Zhang, X., Dravida, S., Ono, Y., Naples, A., McPartland, J. C., & Hirsch, J. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.00019 · Cited by 80
Metadata
- Authors
- Eggebrecht, A. T., White, B. R., Ferradal, S. L., Chen, C., Zhan, Y., Snyder, A. Z., Dehghani, H., & Culver, J. P.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-07
- Volume
- 61
- Issue
- 4
- Pages
- 1120-1128
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2154244503
- Cited by
- 239
- References
- 3
- FWCI
- 9.57
- Type
- journal article
- Language
- en
- Open access
- green
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping. https://app.cochat.ai/papers/10.1016/j.neuroimage.2012.01.124
- The paper
- Eggebrecht, A. T., White, B. R., Ferradal, S. L., Chen, C., Zhan, Y., Snyder, A. Z., Dehghani, H., & Culver, J. P. (2012). A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping. NeuroImage. https://doi.org/10.1016/j.neuroimage.2012.01.124
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.