RevieweLife2020
Hyperalignment: Modeling shared information encoded in idiosyncratic cortical topographies.
Review in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
101 citing papers in PubMed.
- Differences in functional connectivity distribution after transcranial direct-current stimulation: A connectivity density point of view.Human brain mapping · 2023Trial
- Review
- Brain Mechanisms of Lexicality in Bilingual Emotion Processing.bioRxiv : the preprint server for biology · 2026Article
- Article
- Article
- Opportunities and pitfalls of data contextualization in neuroimaging.Nature reviews. Neuroscience · 2026Review
- Inter-subject correlations and their behavioral associations vary across movies: Implications for generalizability.bioRxiv : the preprint server for biology · 2026Article
- Rethinking category-selectivity in human visual cortex.Cognitive neuroscience · 2026Review
- Cortical functional hierarchy disruption following subcortical stroke.BMC medicine · 2026Article
- Commonality and Variability in Functional Networks in Children Under 5 Years Old.bioRxiv : the preprint server for biology · 2026Article
- Exploiting correlations across trials and behavioral sessions to improve neural decoding.Neuron · 2026Article
- Aligning brains into a shared space improves their alignment with large language models.Nature computational science · 2026Article
- Universal scale-free representations in human visual cortex.PLoS computational biology · 2025Article
- Exploiting correlations across trials and behavioral sessions to improve neural decoding.bioRxiv : the preprint server for biology · 2025Article
- Invariant inter-subject relational structures in high order human visual cortex.Nature communications · 2025Article
- Spacetop: A multimodal fMRI dataset unifying naturalistic processes with a rich array of experimental tasks.Scientific data · 2025Article
- Familial transmission of neural representations for mental arithmetic across two generations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- What are we missing? What are we assuming? The need to foster feature discovery tools to improve statistical models.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Inter-individual and inter-site neural code conversion without shared stimuli.Nature computational science · 2025Article
- Cortical language areas are coupled via a soft hierarchy of model-based linguistic features.bioRxiv : the preprint server for biology · 2025Article
41 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Information that is shared across brains is encoded in idiosyncratic fine-scale functional topographies. Hyperalignment captures shared information by projecting pattern vectors for neural responses and connectivities into a common, high-dimensional information space, rather than by aligning topographies in a canonical anatomical space. Individual transformation matrices project information from individual anatomical spaces into the common model information space, preserving the geometry of pairwise dissimilarities between pattern vectors, and model cortical topography as mixtures of overlapping, individual-specific topographic basis functions, rather than as contiguous functional areas. The fundamental property of brain function that is preserved across brains is information content, rather than the functional properties of local features that support that content. In this Perspective, we present the conceptual framework that motivates hyperalignment, its computational underpinnings for joint modeling of a common information space and idiosyncratic cortical topographies, and discuss implications for understanding the structure of cortical functional architecture.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.