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Related Experiment Video

Updated: Feb 28, 2026

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

Ultra high-field (7 T) multi-resolution fMRI data for orientation decoding in visual cortex.

Ayan Sengupta^1,2,3, Renat Yakupov⁴, Oliver Speck^4,5,6,7

¹Department of Experimental Psychology, Institute of Psychology II, Otto-von-Guericke University, Universitätsplatz 2, 39016 Magdeburg, Germany.

|June 16, 2017

Summary

This summary is machine-generated.

This study investigates the optimal spatial resolution for decoding visual orientation from ultra-high field fMRI data. Findings reveal that finer resolutions are crucial for accurately decoding orientation information in the visual cortex.

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Last Updated: Feb 28, 2026

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

Topographical Estimation of Visual Population Receptive Fields by fMRI

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

Area of Science:

Neuroimaging
Cognitive Neuroscience
Machine Learning

Background:

Multivariate pattern classification decodes visual stimuli orientation from BOLD fMRI in human visual cortex.
Previous research on the spatial scale of orientation signals has been inconclusive regarding optimal acquisition resolution for decoding.

Purpose of the Study:

To empirically investigate the effect of spatial acquisition resolution on orientation decoding from ultra-high field fMRI data.
To analyze the strength and spatial scale of orientation-discriminating signals at varying resolutions.

Main Methods:

Acquired ultra-high field fMRI data at four spatial resolutions: 0.8 mm, 1.4 mm, 2 mm, and 3 mm isotropic voxel size.
Applied multivariate pattern classification methods for orientation decoding in the visual cortex.
Ensured dataset compliance with the Brain Imaging Data Structure (BIDS) format.

Main Results:

Presents novel empirical ultra-high field fMRI data for orientation decoding.
Data recorded at multiple resolutions (0.8-3 mm) to assess the impact of spatial resolution.
Dataset is publicly available via the OpenfMRI portal (ds000113c).

Conclusions:

Provides crucial empirical data on the relationship between spatial resolution and orientation decoding accuracy.
Highlights the importance of acquisition resolution for successful fMRI-based decoding of visual information.
Facilitates future research by offering a standardized, high-resolution fMRI dataset.