ArticleSocial cognitive and affective neuroscience2021
Multivariate spatial feature selection in fMRI.
Article in Social cognitive and affective neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Hand-Specific Engagement of Cerebello-Thalamo-Cortical and Higher-Order Sensorimotor Networks in Essential Tremor: Converging Evidence From GLM and MVPA-Based fMRI Analysis.European journal of neurology · 2026Article
- Structured Neural Variability from Repeated Naturalistic Video Watching Experiences.bioRxiv : the preprint server for biology · 2025Article
- The Neurocomputational Mechanism Underlying Decision-Making on Unfairness to Self and Others.Neuroscience bulletin · 2024Article
- Computational methods in social neuroscience: recent advances, new tools and future directions.Social cognitive and affective neuroscience · 2021Article
- Endogenous variation in ventromedial prefrontal cortex state dynamics during naturalistic viewing reflects affective experience.Science advances · 2021Article
- Naturalistic Stimuli in Affective Neuroimaging: A Review.Frontiers in human neuroscience · 2021Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Multivariate neuroimaging analyses constitute a powerful class of techniques to identify psychological representations. However, not all psychological processes are represented at the same spatial scale throughout the brain. This heterogeneity is apparent when comparing hierarchically organized local representations of perceptual processes to flexible transmodal representations of more abstract cognitive processes such as social and affective operations. An open question is how the spatial scale of analytic approaches interacts with the spatial scale of the representations under investigation. In this article, we describe how multivariate analyses can be viewed as existing on a spatial spectrum, anchored by searchlights used to identify locally distributed patterns of information on one end, whole brain approach used to identify diffuse neural representations at the other and region-based approaches in between. We describe how these distinctions are an important and often overlooked analytic consideration and provide heuristics to compare these different techniques to choose based on the analyst's inferential goals.
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Registered trials
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