CNS*2026 Halifax

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.

The detailed agenda for this workshop, along with abstracts for each talk, can be found here.

As high-throughput single-cell experimental workflows become standard in the field of neuroscience, the immense heterogeneity of neurons in the human brain has become increasingly apparent. While this heterogeneity is in part reflected in the historical pursuit of canonical “cell types,” contemporary data highlights variability in key intrinsic cellular properties, even within classical cell types. Whether this heterogeneity serves a functional purpose in the human brain, or is merely a byproduct of biological noise, remains an open question. Computational and mathematical techniques are particularly well suited to address this question considering the experimental challenges involved in varying heterogeneity in vitro or in vivo—indeed, most common experimental manipulations inherently reduce heterogeneity by grossly up or down-regulating a particular neuronal characteristic.

In this workshop, we will highlight the growing interest within the field of computational neuroscience to leverage in silico tools to study the functional role of neuronal heterogeneity. This research addresses a wide variety of neuroscientific questions of interest to OCNS attendees, ranging from mechanisms underlying neuronal synchronization (e.g. epileptic seizures) to memory formation in neural networks. Talks will cover a diverse set of approaches, ranging from foundational mathematical theory to biophysically detailed models reflecting experimentally observed neuronal heterogeneities.

Confirmed speakers include:
Dr. Richard Gast
Postdoc; Dorris Center for Neuroscience, Scripps Research
 
Sanjna Kumari
Graduate Student; Indian Institute of Science
 
Dr. Jeremie Lefebvre
Associate Professor; University of Ottawa; Department of Biology

Dr. Andre Longtin
Professor; University of Ottawa; Department of Physics

Dr. Laura Medlock
Postdoc; Krembil Research Institute, University Health Network

Dr. Scott Rich 
Assistant Professor; University of Connecticut; Departments of Physiology and Neurobiology, Biomedical Engineering, Mathematics, and Institute for Brain and Cognitive Sciences

Marco Zenari (filling in for Dr. Luca Mazzucato)
Padova Neuroscience Center, University of Padova, Italy

Brain function is mediated by neuronal microcircuits with specific connectivity between neuron types, and it is increasingly evident that altered microcircuitry underlies deficits in brain disorders such as depression and schizophrenia, and in aging and Alzheimer’s. However, our ability to monitor the microcircuitry in living humans is limited, meriting the use of detailed computational simulations to overcome experimental limitations in linking the microcircuit mechanisms with altered cortical activity, functional deficits and biomarkers in clinically-relevant brain signals.
This workshop will showcase the latest efforts from leading groups in large-scale neuronal microcircuit modeling of spiking activity and signals such as EEG and MEG. The workshop will present diverse data-driven microcircuit modeling approaches that integrate neuronal, synaptic and functional data, and the different simulation tools used to generate activity and brain signals from the models. The workshop will highlight clinical applications of the models in establishing target mechanisms for treatment, and estimating microcircuit mechanisms from clinical signals in patient data with machine learning to improve diagnosis. This workshop aims to foster the exchange of methods and ideas, and offer new insights on clinical applications of simulated large-scale cortical microcircuits.

Speakers:
Etay Hay
Assistant Professor, Centre for Addiction and Mental Health, University of Toronto

Heng Kan Yao
Postdoc, Centre for Addiction and Mental Health, University of Toronto

Salvador Dura-Bernal
Associate Professor, State University of New York (SUNY) Downstate

Katharina Duecker
Postdoc, Brown University

Alexandre Guet-McCreight
Postdoc, Centre for Addiction and Mental Health, University of Toronto