ReviewNature neuroscience2017
Computational approaches to fMRI analysis.
Review in Nature neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
106 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review.Frontiers in neuroscience · 2019Pooled it
- A double-blind trial of decoded neurofeedback intervention for specific phobias.Psychiatry and clinical neurosciences · 2024Trial
- The Human Cerebellum Encodes Temporally Sensitive Reinforcement Learning Signals.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- How the brain represents a romantic partner: Dissociable roles of the nucleus accumbens and anterior insula.Cognitive, affective & behavioral neuroscience · 2026Article
- A digital twin approach for simultaneous reconstruction of brain anatomy and dynamics from neural data.PLOS digital health · 2026Article
- Rethinking Naturalistic Movie Neuroimaging Through Film Form.Behavioral sciences (Basel, Switzerland) · 2026Review
- Probabilistic Cognitive State Modeling (PCSM): Decoding dynamic brain states to derive emergent cognitive processing properties from task fMRI.NeuroImage · 2026Article
- Aligning brains into a shared space improves their alignment with large language models.Nature computational science · 2026Article
- Addressing low statistical power in computational modelling studies in psychology and neuroscience.Nature human behaviour · 2026Article
- A habit and working memory model as an alternative account of human reward-based learning.Nature human behaviour · 2026Article
- Reduced neural specificity for a romantic partner in the nucleus accumbens over relationship duration.Social cognitive and affective neuroscience · 2026Article
- Probabilistic Cognitive State Modeling (PCSM): Decoding Latent Spatiotemporal Dynamics to Reveal Serial-Parallel Processing, Cognitive Demand, and Serial Bottleneck in Task-Based fMRI.bioRxiv : the preprint server for biology · 2025Article
- Neurocomputational basis of learning when choices simultaneously affect both oneself and others.Nature communications · 2025Article
- Large-Scale Color Biases in the Retinotopic Functional Architecture Are Region Specific and Shared across Human Brains.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- The human cerebellum encodes temporally sensitive reinforcement learning signals.bioRxiv : the preprint server for biology · 2025Article
- Latent variable sequence identification for cognitive models with neural network estimators.Behavior research methods · 2025Article
- Multi-voxel pattern analysis for developmental cognitive neuroscientists.Developmental cognitive neuroscience · 2025Review
- Review
- Decoding Visual Spatial Attention Control.eNeuro · 2025Article
- The medial and lateral orbitofrontal cortex jointly represent the cognitive map of task space.Communications biology · 2025Article
46 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
11 authors.
Funding
Abstract
Analysis methods in cognitive neuroscience have not always matched the richness of fMRI data. Early methods focused on estimating neural activity within individual voxels or regions, averaged over trials or blocks and modeled separately in each participant. This approach mostly neglected the distributed nature of neural representations over voxels, the continuous dynamics of neural activity during tasks, the statistical benefits of performing joint inference over multiple participants and the value of using predictive models to constrain analysis. Several recent exploratory and theory-driven methods have begun to pursue these opportunities. These methods highlight the importance of computational techniques in fMRI analysis, especially machine learning, algorithmic optimization and parallel computing. Adoption of these techniques is enabling a new generation of experiments and analyses that could transform our understanding of some of the most complex-and distinctly human-signals in the brain: acts of cognition such as thoughts, intentions and memories.
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What OpenQuestion holds
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.