ArticleNeuroImage2020
Joint embedding: A scalable alignment to compare individuals in a connectivity space.
Article in NeuroImage, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genetic and phylogenetic uncoupling of structure and function in human transmodal cortex.Nature communications · 2022Pooled it
- Preserved intrinsic neural timescale organization with hierarchical variation in autism spectrum disorder.Cerebral cortex (New York, N.Y. : 1991) · 2026Article
- Intrinsic cortical geometry is associated with individual differences in local functional organization.Research square · 2026Article
- Hierarchical Flows of Human Cortical Activity.bioRxiv : the preprint server for biology · 2026Article
- Cross-Species Cortical Geometry Reveals Conserved Gradients Across Primates and Human-Specific Expansion.bioRxiv : the preprint server for biology · 2025Article
- The generalizability of cortical area parcellations across early childhood.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Multivariate Neural Markers of Individual Differences in Thought Control Difficulties.bioRxiv : the preprint server for biology · 2025Article
- Deep learning-based embedding of functional connectivity profiles for precision functional mapping.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Multivariate neural markers of individual differences in thought control difficulties.NeuroImage. Clinical · 2025Article
- Multiscale comparative connectomics.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Disruption of structural connectome hierarchy in age-related hearing loss.Frontiers in neuroscience · 2025Article
- Consecutive-Contrastive Spherical U-Net: Enhancing Reliability of Individualized Functional Brain Parcellation for Short-Duration fMRI Scans.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2024Article
- Reshaping the Cortical Connectivity Gradient by Long-Term Cognitive Training During Development.Neuroscience bulletin · 2024Article
- Comparison of different group-level templates in gradient-based multimodal connectivity analysis.Network neuroscience (Cambridge, Mass.) · 2024Article
- Test-retest reliability and predictive utility of a macroscale principal functional connectivity gradient.Human brain mapping · 2023Article
- Association between gene expression and functional-metabolic architecture in Parkinson's disease.Human brain mapping · 2023Article
- Omnipresence of the sensorimotor-association axis topography in the human connectome.NeuroImage · 2023Article
- Evolution of cortical geometry and its link to function, behaviour and ecology.Nature communications · 2023Article
- Article
- Evaluate the efficacy and reliability of functional gradients in within-subject designs.Human brain mapping · 2023Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
A common coordinate space enabling comparison across individuals is vital to understanding human brain organization and individual differences. By leveraging dimensionality reduction algorithms, high-dimensional fMRI data can be represented in a low-dimensional space to characterize individual features. Such a representative space encodes the functional architecture of individuals and enables the observation of functional changes across time. However, determining comparable functional features across individuals in resting-state fMRI in a way that simultaneously preserves individual-specific connectivity structure can be challenging. In this work we propose scalable joint embedding to simultaneously embed multiple individual brain connectomes within a common space that allows individual representations across datasets to be aligned. Using Human Connectome Project data, we evaluated the joint embedding approach by comparing it to the previously established orthonormal alignment model. Alignment using joint embedding substantially increased the similarity of functional representations across individuals while simultaneously capturing their distinct profiles, allowing individuals to be more discriminable from each other. Additionally, we demonstrated that the common space established using resting-state fMRI provides a better overlap of task-activation across participants. Finally, in a more challenging scenario - alignment across a lifespan cohort aged from 6 to 85 - joint embedding provided a better prediction of age (r2 = 0.65) than the prior alignment model. It facilitated the characterization of functional trajectories across lifespan. Overall, these analyses establish that joint embedding can simultaneously capture individual neural representations in a common connectivity space aligning functional data across participants and populations and preserve individual specificity.
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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.