ArticleNeuroImage2020
Leveraging shared connectivity to aggregate heterogeneous datasets into a common response 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 21 papers.
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Who cites it
21 citing papers in PubMed.
- A neuroimaging dataset combining movie-watching, eye-tracking, sensorimotor mapping, and cognitive tasks.Scientific data · 2026Article
- Aligning brains into a shared space improves their alignment with large language models.Nature computational science · 2026Article
- Cortical language areas are coupled via a soft hierarchy of model-based linguistic features.bioRxiv : the preprint server for biology · 2025Article
- Lights, Camera, Emotion: REELMO's 1060 Hours of Affective Reports to Explore Emotions in Naturalistic Contexts.Scientific data · 2025Article
- Encoding models for developmental cognitive computational neuroscience: Promise, challenges, and potential.Developmental cognitive neuroscience · 2024Review
- A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations.Neuron · 2024Article
- Shared functional specialization in transformer-based language models and the human brain.Nature communications · 2024Article
- Methods for and Use of Functional Magnetic Resonance Imaging in Psychiatry.Advances in neurobiology · 2024Review
- Article
- A Novel Exploratory Graph-Based Analytical Tool for Functional Near-Infrared Spectroscopy in Naturalistic Experiments: An Illustrative Application in Typically Developing Children.Brain sciences · 2023Article
- The individualized neural tuning model: Precise and generalizable cartography of functional architecture in individual brains.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- Inferring Brain State Dynamics Underlying Naturalistic Stimuli Evoked Emotion Changes With dHA-HMM.Neuroinformatics · 2022Article
- Teacher-student neural coupling during teaching and learning.Social cognitive and affective neuroscience · 2022Article
- A massive 7T fMRI dataset to bridge cognitive neuroscience and artificial intelligence.Nature neuroscience · 2022Article
- On the encoding of natural music in computational models and human brains.Frontiers in neuroscience · 2022Review
- The "Narratives" fMRI dataset for evaluating models of naturalistic language comprehension.Scientific data · 2021Article
- Hybrid hyperalignment: A single high-dimensional model of shared information embedded in cortical patterns of response and functional connectivity.NeuroImage · 2021Article
- Article
- The default mode network: where the idiosyncratic self meets the shared social world.Nature reviews. Neuroscience · 2021Review
- BrainIAK: The Brain Imaging Analysis Kit.Aperture neuro · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Connectivity hyperalignment can be used to estimate a single shared response space across disjoint datasets. We develop a connectivity-based shared response model that factorizes aggregated fMRI datasets into a single reduced-dimension shared connectivity space and subject-specific topographic transformations. These transformations resolve idiosyncratic functional topographies and can be used to project response time series into shared space. We evaluate this algorithm on a large collection of heterogeneous, naturalistic fMRI datasets acquired while subjects listened to spoken stories. Projecting subject data into shared space dramatically improves between-subject story time-segment classification and increases the dimensionality of shared information across subjects. This improvement generalizes to subjects and stories excluded when estimating the shared space. We demonstrate that estimating a simple semantic encoding model in shared space improves between-subject forward encoding and inverted encoding model performance. The shared space estimated across all datasets is distinct from the shared space derived from any particular constituent dataset; the algorithm leverages shared connectivity to yield a consensus shared space conjoining diverse story stimuli.
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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.