ArticleNeuroImage2022
A framework For brain atlases: Lessons from seizure dynamics.
Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed.
- Connectome dysfunction in patients at clinical high risk for psychosis and modulation by oxytocin.Molecular psychiatry · 2024Trial
- AI-Driven Mapping of Seizure Spread Patterns.Annals of neurology · 2026Article
- White matter signals reflect information transmission between brain regions during seizures.Brain : a journal of neurology · 2026Article
- Disease detection and classification in temporal lobe epilepsy: step-wise versus simultaneous AI decision models in a multisite neuroimaging study.Brain communications · 2026Article
- Structurally constrained functional connectivity reveals efficient visuomotor decision-making mechanisms in action video gamers.Scientific reports · 2025Article
- Brain Myelin Covariance Networks: Gradients, Cognition, and Higher-Order Landscape.Behavioral sciences (Basel, Switzerland) · 2025Article
- MesoSCOUT: A novel tool for revealing mesoscale organization in the white-matter connectome.bioRxiv : the preprint server for biology · 2025Article
- Article
- A network correspondence toolbox for quantitative evaluation of novel neuroimaging results.Nature communications · 2025Article
- Controllability of nonlinear epileptic-seizure spreading dynamics in large-scale subject-specific brain networks.Scientific reports · 2025Article
- Mapping the white-matter functional connectome: a personal perspective.Psychoradiology · 2025Review
- Supervised brain node and network construction under voxel-level functional imaging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Quantifying hubness to predict surgical outcomes in epilepsy: Assessing resection-hub alignment in interictal intracranial EEG networks.Epilepsia · 2024Article
- Predicting Cognitive Functioning for Patients with a High-Grade Glioma: Evaluating Different Representations of Tumor Location in a Common Space.Neuroinformatics · 2024Article
- Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics.Nature communications · 2024Article
- Artificial intelligence in epilepsy - applications and pathways to the clinic.Nature reviews. Neurology · 2024Review
- iEEG-recon: A fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices.Epilepsia · 2024Article
- Mapping Brain Structure Variability in Chronic Pain: The Role of Widespreadness and Pain Type and Its Mediating Relationship With Suicide Attempt.Biological psychiatry · 2024Article
- Homological landscape of human brain functional sub-circuits.Mathematics (Basel, Switzerland) · 2024Article
- Adding the third dimension: 3D convolutional neural network diagnosis of temporal lobe epilepsy.Brain communications · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Brain maps, or atlases, are essential tools for studying brain function and organization. The abundance of available atlases used across the neuroscience literature, however, creates an implicit challenge that may alter the hypotheses and predictions we make about neurological function and pathophysiology. Here, we demonstrate how parcellation scale, shape, anatomical coverage, and other atlas features may impact our prediction of the brain's function from its underlying structure. We show how network topology, structure-function correlation (SFC), and the power to test specific hypotheses about epilepsy pathophysiology may change as a result of atlas choice and atlas features. Through the lens of our disease system, we propose a general framework and algorithm for atlas selection. This framework aims to maximize the descriptive, explanatory, and predictive validity of an atlas. Broadly, our framework strives to provide empirical guidance to neuroscience research utilizing the various atlases published over the last century.
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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.