The DOI matches its Crossref record; 3 of the 5 references it cites were found in a registry or an index.
Spatial smoothing hurts localization but not information: Pitfalls for brain mappers
Abstract
Op de Beeck (Op de Beeck, H., 2009. Against hyperacuity in brain reading: Spatial smoothing does not hurt multivariate fMRI analyses? Neuroimage) challenges the possibility of extracting information from subvoxel representations via random biases associated with voxel sampling, the hypothesis proposed by Kamitani and Tong (Kamitani, Y., Tong, F., 2005. Decoding the visual and subjective contents of the human brain. Nat. Neurosci. 8, 679-685). Here, we show that his results provide no evidence against the possibility, being consistent with both of the subvoxel and supravoxel representation models. Classification of spatially smoothed fMRI data is not an effective means to probe into information sources for multivoxel decoding, since smoothing does not hurt the information contents of multivoxel patterns. We point out the danger of interpreting multivoxel decoding results based on intuitions guided by the conventional brain mapping paradigm.
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“Although smoothing has been shown not to substantially affect information in multivariate data91–93”
From Acute social isolation evokes midbrain craving responses similar to hunger (2020) · cites this paper as [92]
Citations
Cites
Decoding the visual and subjective contents of the human brain
Kamitani, Y., & Tong, F. (2005) · Nature Neuroscience · doi:10.1038/nn1444 · Cited by 1,829
Self-citationTurner, R. (2002) · NeuroImage · doi:10.1006/nimg.2002.1082 · Cited by 365
Against hyperacuity in brain reading: Spatial smoothing does not hurt multivariate fMRI analyses?
Op de Beeck, H. P. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.02.047 · Cited by 275
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Items 101–121 of 121
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Effect of spatial smoothing on regions of interested analysis basing on general linear model
Wang, B., Hikino, Y., Imajyo, S., Ohno, S., Kanazawa, S., & Wu, J. (2012) · IEEE International Conference on Mechatronics and Automation (ICMA) · doi:10.1109/icma.2012.6284341 · Cited by 1
Information Decoding from fMRI Images
Martino, F. D., Olman, C. A., & Valente, G. (2015) · Biological magnetic resonance · doi:10.1007/978-1-4899-7591-1_23 · Cited by 1
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From stimuli to motor responses : Decoding rules and decision mechanisms in the human brain
Bode, S. (2010) · Max Planck Digital Library · Cited by 1
Correction: Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis
Xu, R., Zhen, Z., & Jia Liu, B. (2011) · PLoS ONE · doi:10.1371/annotation/0cca502f-3308-44a1-9536-be92153df9ea
Saliency processing in the human brain
Bogler, C. (2014) · edoc Publication server (Humboldt University of Berlin) · doi:10.18452/17025
Diffraction as a resolution enhancer: Visual hyperacuity simulation method
Lagunas, A., Dominguez, O., & Bocio, C. D. R. (2016) · International Conference on Applied Electromagnetics and Communications · doi:10.1109/icecom.2016.7843910
Human Eye Visual Hyperacuity: A New Paradigm for Sensing?Preprint
Lagunas, A., Dominguez, O., Martínez‐Conde, S., Macknik, S. L., & del-Rio, C. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1703.00249
Bode, S. (2017) · Kölner Universitäts PublikationsServer (Universität zu Köln)
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Zhang, X., Liu, R., Huang, J., Yang, Y., Kuai, H., & Zhong, N. (2019) · International Conference on Artificial Intelligence and Advanced Manufacture (AIAM) · doi:10.1109/aiam48774.2019.00078
Cabeza, R. E. L., & Wing, E. A. (2013) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.718106892.793486230
Baker, C. I. (2020) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.733846884.793575154
Subjective Perception of Feature Binding in Visual CorticesPreprint
Chiang, T.-C., Kao, C.-H. T., & Chen, C. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4533899
Flexible encoding of multiple task dimensions in human cerebral cortex
Tamber-Rosenau, B. J., Newton, A. T., & Marois, R. (2024) · Frontiers in Cognition · doi:10.3389/fcogn.2024.1438390
Imai, F., Shinozaki, J., Saito, H., Nagahama, H., Sakurai, Y., & Ogawa, K. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.11.664262
Decoding Shitsukan in The Brain
Kamitani, Y., Tanaka, M., & Horikawa, T. (2026) · Springer eBooks · doi:10.1007/978-981-95-4762-3_6
Self-citationImai, F., Shinozaki, J., Saito, H., Nagahama, H., Sakurai, Y., & Ogawa, K. (2026) · Imaging Neuroscience · doi:10.1162/imag.a.1141
Common neural representation between visual perception and imagery in eidetikersPreprint
Nabata, R., Niida, M., Takahashi, K., & Ogawa, K. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.18.705196
Deep-learning-based fMRI decoding of real-world size for hand-held objects
Lang, C., Miyoshi, K., & Takeda, M. (2026) · Scientific Reports · doi:10.1038/s41598-026-74629-7
Metadata
- Authors
- Kamitani, Y., & Sawahata, Y.
- Affiliations
- Advanced Telecommunications Research Institute International (JP)
- Corresponding author
- Kamitani, Yukiyasu
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-02
- Volume
- 49
- Issue
- 3
- Pages
- 1949-1952
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2053644821
- Cited by
- 122
- References
- 5
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 2 · 2023: 4 · 2022: 4 · 2021: 3 · 2020: 9 · 2019: 6 · 2018: 5 · 2017: 10 · 2016: 10 · 2015: 7 · 2014: 9 · 2013: 8 · 2012: 15
- FWCI
- 5.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Nissan Global Foundation
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- spatial smoothing, brain mapping, fMRI classification, hyperacuity
- MeSH terms
- Brain, Brain Mapping, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging
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