Mechanisms underlying decoding at 7 T: ocular dominance columns, broad structures, and macroscopic blood vessels in V1 convey information on the stimulated eye
Open accessAbstract
Recent studies have demonstrated that multivariate machine learning algorithms applied to human functional MRI data can decode information segregated in cortical columns, despite the voxel size being large relative to the width of columns. The mechanism by which low spatial resolution imaging decodes information represented in a fine-scale organization is not clear. To investigate mechanisms underlying decoding signals we employed high-resolution gradient-echo BOLD functional MRI of visual area V1. We show that in addition to the fine-scale ocular dominance columns, coarse-scale structures extending over several millimeters also convey discriminative power for decoding the stimulated eye. Discriminative power is conveyed by both macroscopic blood vessels and gray matter regions. We hypothesize that gray-matter regions which drain into specific vessels may preferentially contain ocular-dominance columns biased towards one eye; the bias of a specific region thereby causing a functionally selective ocular-dominance response in the associated vessel. Our findings indicate that coarse-scale structures and macroscopic blood vessels contribute to decoding of the stimulated eye based on low-resolution multivariate data.
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This smoothing level improves inter-subject functional alignment, while retaining sensitivity to mesoscopic activity patterns that are consistent across individuals.
“This smoothing level improves inter-subject functional alignment, while retaining sensitivity to mesoscopic activity patterns that are consistent across individuals [97].”
From Distinct Brain Systems Mediate the Effects of Nociceptive Input and Self-Regulation on Pain (2015) · cites this paper as [97]
MVPA is more likely to reflect population codes across neurons and has greater sensitivity and specificity to particular types of mental events.
“MVPA is more likely to reflect population codes across neurons43,45,48, as they have demonstrably greater sensitivity and specificity to particular types of mental events17,31,32.”
From Separate neural representations for physical pain and social rejection (2014) · cites this paper as [48]
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 [48]
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- Authors
- Shmuel, A., Chaimow, D., Raddatz, G., Ugurbil, K., & Yacoub, E.
- Affiliations
- Montreal Neurological Institute and Hospital (CA)
- Max Planck Society (DE)
- University of Minnesota (US)
- Corresponding author
- Shmuel, Amir
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-02
- Volume
- 49
- Issue
- 3
- Pages
- 1957-1964
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC8485895
- OpenAlex
- W1980209472
- Cited by
- 111
- References
- 27
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 3 · 2023: 3 · 2022: 7 · 2021: 3 · 2020: 3 · 2019: 5 · 2018: 3 · 2017: 12 · 2016: 8 · 2015: 11 · 2014: 6 · 2013: 4 · 2012: 12
- FWCI
- 5.99
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Canada Research Chairs
- Max-Planck-Gesellschaft
- National Institutes of Health (P30 NS057091, P41 RR08079, R01-EB000331, R01-MH070800)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- ocular dominance columns, visual area V1, high-resolution fMRI, multivariate decoding, low spatial resolution
- MeSH terms
- Algorithms, Brain Mapping, Cerebrovascular Circulation, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Photic Stimulation, Visual Cortex, Visual Pathways, Visual Perception, Dominance, Ocular
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