Against hyperacuity in brain reading: Spatial smoothing does not hurt multivariate fMRI analyses?
Open accessAbstract
Recently it has been suggested that multivariate analyses of functional magnetic resonance imaging (fMRI) data can detect high spatial frequency components of cortical signals, like sub-millimeter columns. This 'hyperacuity' seems to be at odds with the common assumption that the fMRI signal has a low spatial resolution due to the spatial spread of the underlying hemodynamic events. To resolve this apparent contradiction, I checked a very straightforward prediction of the hyperacuity hypothesis: if multivariate analyses are picking up a small-scale functional organization, then it can be expected that smoothing will be detrimental to the ability to decode these fine-scale spatial signals. I tested this prediction using data obtained with two paradigms to which multivariate techniques have been applied previously, including the decoding of grating orientation from the pattern of activity in primary visual cortex. It was found that smoothing does not decrease the sensitivity of multivariate analyses. Further simulations in which the scale of cortical organization was known indicate that this effect of smoothing contradicts the idea that the patterns detected with multivariate techniques reflect a fine-scale spatial organization.
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
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Smoothing has been shown not to substantially affect information in multivariate data.
“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 [93]
The smoothing level (8-mm FWHM Gaussian kernel) has been shown to improve inter-subject functional alignment while retaining sensitivity to mesoscopic activity patterns that are consistent across individuals.
“This smoothing level has been shown to improve inter-subject functional alignment, while retaining sensitivity to mesoscopic activity patterns that are consistent across individuals48,66.”
From Separate neural representations for physical pain and social rejection (2014) · cites this paper as [66]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Ashburner, J., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.02.018 · Cited by 7,507 · see citing works
Distributed and overlapping representations of faces and objects in ventral temporal cortex
Haxby, J. V., Gobbini, M. I., Furey, M. L., Ishai, A., Schouten, J. L., & Pietrini, P. (2001) · Science · doi:10.1126/science.1063736 · Cited by 3,940 · see citing works
Beyond mind-reading: multi-voxel pattern analysis of fMRI data
Norman, K. A., Polyn, S. M., Detre, G. J., & Haxby, J. V. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.07.005 · Cited by 2,271 · see citing works
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 · see citing works
Decoding mental states from brain activity in humans
Haynes, J., & Rees, G. E. (2006) · Nature reviews. Neuroscience · doi:10.1038/nrn1931 · Cited by 1,804 · see citing works
Retinotopic organization in human visual cortex and the spatial precision of functional MRI
Engel, S. A. (1997) · Cerebral Cortex · doi:10.1093/cercor/7.2.181 · Cited by 1,606 · see citing works
Functional architecture of cortex revealed by optical imaging of intrinsic signals
Grinvald, A., Lieke, E. E., Frostig, R. D., Gilbert, C. D., & Wiesel, T. N. (1986) · Nature · doi:10.1038/324361a0 · Cited by 1,243 · see citing works
Predicting the orientation of invisible stimuli from activity in human primary visual cortex
Haynes, J., & Rees, G. E. (2005) · Nature Neuroscience · doi:10.1038/nn1445 · Cited by 866 · see citing works
Columns for visual features of objects in monkey inferotemporal cortex
Fujita, I., Tanaka, K., Ito, M., & Cheng, K. (1992) · Nature · doi:10.1038/360343a0 · Cited by 623 · see citing works
Miyawaki, Y., Uchida, H., Yamashita, O., Sato, M.-A., Morito, Y., Tanabe, H. C., Sadato, N., & Kamitani, Y. (2008) · Neuron · doi:10.1016/j.neuron.2008.11.004 · Cited by 543 · see citing works
Peelen, M. V., Wiggett, A. J., & Downing, P. E. (2006) · Neuron · doi:10.1016/j.neuron.2006.02.004 · Cited by 402 · see citing works
Anatomical Demonstration of Columns in the Monkey Striate Cortex
Hubel, D. H., & Wiesel, T. N. (1969) · Nature · doi:10.1038/221747a0 · Cited by 373 · see citing works
Spatio-temporal point-spread function of fMRI signal in human gray matter at 7 Tesla
Shmuel, A., Yacoub, E., Chaimow, D., Logothetis, N. K., & Ugurbil, K. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.12.030 · Cited by 294 · see citing works
Bonhoeffer, T., & Grinvald, A. (1993) · Journal of Neuroscience · doi:10.1523/jneurosci.13-10-04157.1993 · Cited by 294 · see citing works
de Beeck, H. O., Torfs, K., & Wagemans, J. P. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.2511-08.2008 · Cited by 265 · see citing works
Discrimination Training Alters Object Representations in Human Extrastriate Cortex
de Beeck, H. O., Baker, C. I., DiCarlo, J. J., & Kanwisher, N. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.2481-06.2006 · Cited by 250 · see citing works
Only some spatial patterns of fMRI response are read out in task performance
Williams, M., Dang, S., & Kanwisher, N. (2007) · Nature Neuroscience · doi:10.1038/nn1900 · Cited by 213 · see citing works
Quantifying the spatial resolution of the gradient echo and spin echo BOLD response at 3 Tesla
Parkes, L. M., Schwarzbach, J. V., Bouts, A. A., Deckers, R., Pullens, P., Kerskens, C., & Norris, D. G. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20712 · Cited by 187 · see citing works
Downing, P. E., Wiggett, A. J., & Peelen, M. V. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.3619-06.2007 · Cited by 181 · see citing works
Relating Retinotopic and Object-Selective Responses in Human Lateral Occipital Cortex
Sayres, R., & Kalanit Grill-spector, A. (2008) · Journal of Neurophysiology · doi:10.1152/jn.01383.2007 · Cited by 167 · see citing works
Serences, J. T., Saproo, S., Scolari, M., Ho, T. C., & Muftuler, L. T. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.07.043 · Cited by 125 · see citing works
Fukuda, M., Moon, C., Wang, P., & Kim, S. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.3098-06.2006 · Cited by 101 · see citing works
A Stable Topography of Selectivity for Unfamiliar Shape Classes in Monkey Inferior Temporal Cortex
de Beeck, H. O., Deutsch, J. A., Vanduffel, W., Kanwisher, N., & DiCarlo, J. J. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhm196 · Cited by 80 · see citing works
de Beeck, H. O., DiCarlo, J. J., Goense, J. B. M., Kalanit Grill-spector, A., Papanastassiou, A. M., Tanifuji, M., & Tsao, D. Y. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.3799-08.2008 · Cited by 39 · see citing works
Estimating the global order of the fMRI noise model
Gautama, T., & Hulle, M. M. V. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.03.015 · Cited by 14 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Friston, K., 2003. Introduction: experimental design and statistical parametric mapping, In: Frackowiak, R.S.J., et al. (Ed.), Human Brain Function, 2nd edition. Academic Press, pp. 599-633.
Cited by
Sorted by citations
A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives
Haynes, J.-D. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.025 · Cited by 402 · see citing works
Distributed Representations in Memory: Insights from Functional Brain Imaging
Rissman, J., & Wagner, A. D. (2012) · Annual Review of Psychology · doi:10.1146/annurev-psych-120710-100344 · Cited by 299 · see citing works
Separate neural representations for physical pain and social rejection
Woo, C.-W., Koban, L., Kross, E., Lindquist, M. A., Banich, M. T., Ruzic, L., Andrews-Hanna, J. R., & Wager, T. D. (2014) · Nature Communications · doi:10.1038/ncomms6380 · Cited by 310 · see citing works
Acute social isolation evokes midbrain craving responses similar to hunger
Tomova, L., Wang, K. L., Thompson, T., Matthews, G. A., Takahashi, A., Tye, K. M., & Saxe, R. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-00742-z · Cited by 283 · see citing works
Spatial smoothing hurts localization but not information: Pitfalls for brain mappers
Kamitani, Y., & Sawahata, Y. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.06.040 · Cited by 122 · see citing works
Shmuel, A., Chaimow, D., Raddatz, G., Ugurbil, K., & Yacoub, E. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.08.040 · Cited by 111 · see citing works
Neural pattern similarity predicts long-term fear memory
Visser, R. M., Scholte, H. S., Beemsterboer, T., & Kindt, M. (2013) · Nature Neuroscience · doi:10.1038/nn.3345 · Cited by 118 · see citing works
Iannaccone, R., Hauser, T. U., Ball, J., Brandeis, D., Walitza, S., & Brem, S. (2015) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-015-0678-4 · Cited by 74 · see citing works
The Effect of Spatial Smoothing on Representational Similarity in a Simple Motor Paradigm
Hendriks, M. H. A., Daniels, N., Pegado, F., & Op de Beeck, H. P. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00222 · Cited by 55 · see citing works
Self-citationMedial Frontal Cortex Activity Predicts Information Sampling in Economic Choice
Kaanders, P., Nili, H., O'Reilly, J. X., & Hunt, L. (2021) · The Journal of Neuroscience · doi:10.1523/jneurosci.0392-21.2021 · Cited by 27 · see citing works
- Authors
- Op de Beeck, H. P.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-02
- Volume
- 49
- Issue
- 3
- Pages
- 1943-1948
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1976734125
- Cited by
- 275
- References
- 25
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 5 · 2023: 16 · 2022: 11 · 2021: 11 · 2020: 14 · 2019: 35 · 2018: 18 · 2017: 20 · 2016: 20 · 2015: 19 · 2014: 15 · 2013: 13 · 2012: 20
- FWCI
- 10.16
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Lirias (submittedVersion, other-oa)
- Funders
- Vlaamse regering (METH 08/02)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- hyperacuity, spatial smoothing, multivariate pattern analysis, primary visual cortex, cortical columns, hemodynamic response
- MeSH terms
- Brain Mapping, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Sensitivity and Specificity, Visual Cortex, Multivariate Analysis
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
