HNN-core A Python software for cellular and circuit-level interpretation of human MEG/EEG

HNN-core : A Python software for cellular and circuit-level interpretation of human MEG/EEG

HNN-core is a library for circuit and cellular level interpretation of non-invasive human magneto-/electro-encephalography (MEG/EEG) data. It is based on the Human Neocortical Neurosolver (HNN) software (Neymotin et al., 2020), a modeling tool designed to simulate multiscale neural mechanisms genera...

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Veröffentlicht in:Journal of open source software. - 2017. - 8(2023), 92 vom: 01.
1. Verfasser: Jas, Mainak (VerfasserIn)
Weitere Verfasser: Thorpe, Ryan, Tolley, Nicholas, Bailey, Christopher, Brandt, Steven, Caldwell, Blake, Cheng, Huzi, Daniels, Dylan, Pujol, Carolina Fernandez, Khalil, Mostafa, Kanekar, Samika, Kohl, Carmen, Kolozsvári, Orsolya, Lankinen, Kaisu, Loi, Kenneth, Neymotin, Sam, Partani, Rajat, Pelah, Mattan, Rockhill, Alex, Sherif, Mohamed, Hamalainen, Matti, Jones, Stephanie
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2023
Zugriff auf das übergeordnete Werk:Journal of open source software
Schlagworte:Journal Article
Beschreibung
Zusammenfassung:HNN-core is a library for circuit and cellular level interpretation of non-invasive human magneto-/electro-encephalography (MEG/EEG) data. It is based on the Human Neocortical Neurosolver (HNN) software (Neymotin et al., 2020), a modeling tool designed to simulate multiscale neural mechanisms generating current dipoles in a localized patch of neocortex. HNN's foundation is a biophysically detailed neural network representing a canonical neocortical column containing populations of pyramidal and inhibitory neurons together with layer-specific exogenous synaptic drive (Figure 1 left). In addition to simulating network-level interactions, HNN produces the intracellular currents in the long apical dendrites of pyramidal cells across the cortical layers known to be responsible for macroscopic current dipole generation
Beschreibung:Date Revised 01.10.2024
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:2475-9066
DOI:10.21105/joss.05848