ArticleNeuroImage2017
Effects of spatial fMRI resolution on the classification of naturalistic movies.
Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- From Contrasts to Representations: Rethinking fMRI Approaches for Cortico-Cerebellar Networks.Cerebellum (London, England) · 2026Review
- Comparing reliability-based measures of functional connectivity between movie and rest: An ROI-based approach.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Closed-loop fMRI at the mesoscopic scale of columns and layers: Can we do it and why would we want to?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Elucidating the underlying components of metacognitive systematic bias in the human dorsolateral prefrontal cortex and inferior parietal cortex.Scientific reports · 2024Article
- Acquisition and processing methods of whole-brain layer-fMRI VASO and BOLD: The Kenshu dataset.Aperture neuro · 2023Article
- Do sparse brain activity patterns underlie human cognition?NeuroImage · 2022Article
- Representational coding of overt and covert orienting of visuospatial attention in the frontoparietal network.NeuroImage · 2022Article
- Toward Precise Localization of Abnormal Brain Activity: 1D CNN on Single Voxel fMRI Time-Series.Frontiers in computational neuroscience · 2022Article
- Layer-dependent functional connectivity methods.Progress in neurobiology · 2021Review
- Studying the visual brain in its natural rhythm.NeuroImage · 2020Review
- Article
- Multimodal Integration of Brain Images for MRI-Based Diagnosis in Schizophrenia.Frontiers in neuroscience · 2019Article
- Decoding of columnar-level organization across cortical depth using BOLD- and CBV-fMRI at 7 T.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Studies involving multivariate pattern analysis (MVPA) of BOLD fMRI data generally attribute the success of the information-theoretic approach to BOLD signal contrast on the fine spatial scale of millimeters facilitating the classification or decoding of perceptual stimuli. However, to date MVPA studies that have actually explored fMRI resolutions at less than 2 mm voxel size are rare and limited to small sets of unnatural stimuli (like visual gratings) as well as specific sub-regions of the brain, notably the primary somatosensory cortices. To investigate what spatial scale best supports high information extraction under more general conditions this study combined naturalistic movie stimuli with high-resolution fMRI at 7 T and linear discriminant analysis (LDA) of global and local BOLD signal patterns. Contrary to predictions, LDA and similar classifiers reached a maximum in classification accuracy (CA) at a smoothed resolution close to 3 mm, well above the 1.2 mm voxel size of the fMRI acquisition. Maximal CAs around 90% were contingent upon global fMRI signal patterns comprising 4 k-16 k of the most reactive voxels distributed sparsely throughout the occipital and ventro-temporal cortices. A Searchlight analysis of local fMRI patterns largely confirmed the global results, but also revealed a small subset of brain regions in early visual cortex showing limited increases in CA with higher resolution. Principal component analysis of the global and local fMRI signal patterns suggested that reproducible neuronal contributions were spatially auto-correlated and smooth, while other components of higher spatial frequency were likely related to physiological noise and responsible for the reduced CA at higher resolution. Systematic differences between experiments and subjects suggested that higher CA was significantly correlated with more consistent behavior revealed by eye tracking. Thus, the optimal resolution of fMRI data for MVPA was mainly limited by physiological noise of high spatial frequency as well as behavioral (in-)consistency.
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