Understanding the brain requires studying its multiscale interactions, from molecules to cells to circuits and networks. Although vast experimental datasets are being generated across scales and modalities, integrating and interpreting this data remains a daunting challenge. This tutorial will highlight recent advances in mechanistic multiscale modeling and how it offers an unparalleled approach to integrate these data and provide insights into brain function and disease. Multiscale models facilitate the interpretation of experimental findings across different brain regions, brain scales (molecular, cellular, circuit, system), brain function (sensory perception, motor behavior, learning, etc), recording/imaging modalities (intracellular voltage, LFP, EEG, fMRI, etc) and disease/disorders (e.g., schizophrenia, epilepsy, ischemia, Parkinson's, etc). As such, it has a broad appeal to experimental, clinical and computational neuroscientists, as well as students and educators.
This tutorial will introduce multiscale modeling using two NIH-funded tools: the NEURON 9.0 simulator (
https://www.neuronsimulator.org), including the Reaction-Diffusion (RxD) module, and the NetPyNE tool (
https://netpyne.org). The tutorial will combine background, examples and hands on exercises covering the implementation of models at four key scales:
(1) intracellular dynamics (e.g. calcium buffering, protein interactions),
(2) single neuron electrophysiology (e.g. action potential propagation),
(3) neurons in extracellular space (e.g. spreading depression), and
(4) neuronal circuits, including dynamics such as oscillations and simulation of recordings such as local field potentials (LFP) and electroencephalography (EEG).
For circuit simulations, we will use NetPyNE, a high-level interface to NEURON supporting both programmatic and GUI specification that facilitates the development, parallel simulation, and analysis of biophysically detailed neuronal circuits. We conclude with an example combining all three tools that link intracellular/extracellular molecular dynamics with network spiking activity and LFP/EEG. The tutorial will incorporate the recent substantial developments and new features in both the NEURON and NetPyNE tools.
Relevant Publications: Awile O, Kumbhar P, Cornu N, Dura-Bernal S, King JG, Lupton O, Magkanaris I, McDougal RA,
Newton AJH, Pereira F, Savulescu A, Carnevale NT, Lytton WW, Hines ML, Schürmann F.
Modernizing the NEURON Simulator for Sustainability, Portability, and Performance. Frontiers in
Neuroinformatics
10.3389/fninf.2022.884046.
McDougal RA, Hines ML, Lytton WW. (2013)
Reaction-diffusion in the NEURON simulator. https://doi.org/10.3389/fninf.2013.00028 Dura-Bernal S, Suter B, Gleeson P, Cantarelli M, Quintana A, Rodriguez F, Kedziora DJ, Chadderdon
GL, Kerr CC, Neymotin SA, McDougal R, Hines M, Shepherd GMG, Lytton WW. (2019)
NetPyNE: a tool for data-driven multiscale modeling of brain circuits. eLife 2019;8:
e44494.
Dura-Bernal S, Herrera B, Lupascu C, Marsh BM, Gandolfi D, Marasco A, Neymotin SA, Romani A,
Solinas S, Bazhenov M, Hay E, Migliore M, Reinmann M, Arkhipov A (2024)
Large-scale mechanistic models of brain circuits with biophysically- and morphologically-detailed neurons. Journal of Neuroscience 2 October 2024, 44 (40) e1236242024; DOI:
10.1523/JNEUROSCI.1236-24.2024.
