ArticlePLoS computational biology2017
Multivariate pattern dependence.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Altered functional connectivity of the hippocampus in cortico-subcortical networks in early-stage and emerging psychosis.European archives of psychiatry and clinical neuroscience · 2026Article
- Distinct Portions of Superior Temporal Sulcus Combine Auditory Representations with Different Visual Streams.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Multi-voxel pattern analysis for developmental cognitive neuroscientists.Developmental cognitive neuroscience · 2025Review
- Linear and nonlinear multidimensional functional connectivity methods reveal similar networks for semantic processing in EEG/MEG data.Frontiers in human neuroscience · 2025Article
- Hemispheric functional organization, as revealed by naturalistic neuroimaging, in pediatric epilepsy patients with cortical resections.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- A bicoherence approach to analyze multi-dimensional cross-frequency coupling in EEG/MEG data.Scientific reports · 2024Article
- Time-Lagged Multidimensional Pattern Connectivity (TL-MDPC): An EEG/MEG pattern transformation based functional connectivity metric.NeuroImage · 2023Article
- Representations and decodability of diverse cognitive functions are preserved across the human cortex, cerebellum, and subcortex.Communications biology · 2022Article
- Controlling for Spurious Nonlinear Dependence in Connectivity Analyses.Neuroinformatics · 2022Article
- The Dorsal Visual Pathway Represents Object-Centered Spatial Relations for Object Recognition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
- A Multivariate Functional Connectivity Approach to Mapping Brain Networks and Imputing Neural Activity in Mice.Cerebral cortex (New York, N.Y. : 1991) · 2022Article
- Multivariate connectivity: A brief introduction and an open question.Frontiers in neuroscience · 2022Article
- Caveats and Nuances of Model-Based and Model-Free Representational Connectivity Analysis.Frontiers in neuroscience · 2022Article
- PyMVPD: A Toolbox for Multivariate Pattern Dependence.Frontiers in neuroinformatics · 2022Article
- Functional coordinates: Modeling interactions between brain regions as points in a function space.Network neuroscience (Cambridge, Mass.) · 2022Article
- Computational approaches to the neuroscience of social perception.Social cognitive and affective neuroscience · 2021Review
- Article
- Acquisition of concrete and abstract words is modulated by tDCS of Wernicke's area.Scientific reports · 2021Article
- Improved dynamic connection detection power in estimated dynamic functional connectivity considering multivariate dependencies between brain regions.Human brain mapping · 2020Article
- Neural Correlates of Evidence and Urgency During Human Perceptual Decision-Making in Dynamically Changing Conditions.Cerebral cortex (New York, N.Y. : 1991) · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analysis. In the present article, we introduce and apply multivariate pattern dependence (MVPD): a technique to study the statistical dependence between brain regions in humans in terms of the multivariate relations between their patterns of responses. MVPD characterizes the responses in each brain region as trajectories in region-specific multidimensional spaces, and models the multivariate relationship between these trajectories. We applied MVPD to the posterior superior temporal sulcus (pSTS) and to the fusiform face area (FFA), using a searchlight approach to reveal interactions between these seed regions and the rest of the brain. Across two different experiments, MVPD identified significant statistical dependence not detected by standard functional connectivity. Additionally, MVPD outperformed univariate connectivity in its ability to explain independent variance in the responses of individual voxels. In the end, MVPD uncovered different connectivity profiles associated with different representational subspaces of FFA: the first principal component of FFA shows differential connectivity with occipital and parietal regions implicated in the processing of low-level properties of faces, while the second and third components show differential connectivity with anterior temporal regions implicated in the processing of invariant representations of face identity.
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