ArticleeLife2020
Human Neocortical Neurosolver (HNN), a new software tool for interpreting the cellular and network origin of human MEG/EEG data.
Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.
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Who cites it
70 citing papers in PubMed.
- Transient frontal spectral events from EEG predict antidepressant response to sertraline in depression.Journal of psychiatric research · 2026Trial
- Simulated field potentials capture multiple simultaneous processes underlying human temporal attention.bioRxiv : the preprint server for biology · 2026Article
- Concept2Brain: an AI model for predicting neurophysiological responses to text and pictures.Nature communications · 2026Article
- Deviance detection via competitive inhibition between local neocortical ensembles.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Resting-state EEG alpha-BOLD coupling spatially follows cortical cell-type and receptor gradients.bioRxiv : the preprint server for biology · 2026Article
- Uncovering putative neural mechanisms of neurotherapeutic impacts on EEG using the Human Neocortical Neurosolver.bioRxiv : the preprint server for biology · 2026Article
- Thermodynamic rigidity of harmonic brain states relates to general mental ability in juvenile myoclonic epilepsy.bioRxiv : the preprint server for biology · 2026Article
- Testing circuit-level theories of consciousness in humans.Trends in cognitive sciences · 2026Review
- Transient frontal spectral events from EEG predict antidepressant response to sertraline in depression.medRxiv : the preprint server for health sciences · 2026Article
- Bridging Model and Experiment in Systems Neuroscience with Cleo: The Closed-Loop, Electrophysiology, and Optophysiology Simulation Testbed.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Blind identification of state transitions and latent neural dynamics from electrophysiological recordings.Journal of neuroscience methods · 2026Article
- Multi-scale model of neural entrainment by transcranial alternating current stimulation in realistic cortical anatomy.Journal of computational neuroscience · 2025Article
- SmartERD: a pipeline for referencing subjects to a common peak in the analysis of ERD dynamics.Scientific reports · 2025Article
- Article
- Neurophysiology of mismatch negativity generation: a biophysical modeling study.bioRxiv : the preprint server for biology · 2025Article
- Deviance detection via competitive inhibition between local neocortical ensembles.bioRxiv : the preprint server for biology · 2025Article
- Bridging model and experiment in systems neuroscience with Cleo: the Closed-Loop, Electrophysiology, and Optophysiology simulation testbed.bioRxiv : the preprint server for biology · 2025Article
- Neurophysiological Progression in Alzheimer's Disease: Insights From Dynamic Causal Modelling of Longitudinal Magnetoencephalography.Human brain mapping · 2025Article
- BlueRecording: A pipeline for the efficient calculation of extracellular recordings in large-scale neural circuit models.PLoS computational biology · 2025Article
- Effects of dendritic CaJournal of computational neuroscience · 2025Article
10 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
10 authors.
Funding
Abstract
Magneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states. Relating these macroscopic signals to underlying cellular- and circuit-level generators is a limitation that constrains using MEG/EEG to reveal novel principles of information processing or to translate findings into new therapies for neuropathology. To address this problem, we built Human Neocortical Neurosolver (HNN, https://hnn.brown.edu) software. HNN has a graphical user interface designed to help researchers and clinicians interpret the neural origins of MEG/EEG. HNN's core is a neocortical circuit model that accounts for biophysical origins of electrical currents generating MEG/EEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signal's origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms. HNN's ability to associate signals across scales makes it a unique tool for translational neuroscience research.
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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.