CNS*2025 Florence

This tutorial introduces o²S²PARC and Sim4Life.web, two powerful, cloud-based platforms for advanced problem solving in computational life sciences and it targets researchers interested in applying computational neuroscience to real-world biomedical and engineering challenges. Participants will learn how Sim4Life enables image-based and regulatory-grade simulations featuring nerve and brain network models embedded within anatomically detailed representations of the human body. They will also discover how to create, execute, and automate computational pipelines to study realistic neuromodulation scenarios with a high degree of realism, ranging from network responses to non-invasive brain stimulation (NIBS) to the interactions between medical devices and the human body for bioelectronic medicine applications.

o²S²PARC is an open-source, web-accessible platform for collaborative computational modeling, with a focus on neurosciences. It enables seamless integration of diverse computational modeling and data analysis services into pipelines, adhering to FAIR (Findable, Accessible, Interoperable, and Reusable) principles and supporting reproducibility and sustainability. Participants will explore how to use its browser-based GUI, Python API to construct modular and reusable workflows.

Sim4Life.web is a computational life sciences platform with strengths in modeling physical exposure and the resulting physiological responses in complex anatomical environments. It provides advanced multiphysics simulation capabilities, including electromagnetic (EM) and ultrasound solvers, as well as neuronal dynamics modeling. Participants will utilize Sim4Life.web to simulate and analyze the effects of neuromodulation.

Objectives
Participants in this tutorial will:

1. Understand the basics of the o²S²PARC and Sim4Life.web platforms: how to  build and execute shareable computational pipelines for neuromodulation studies with the community and how to expand the computational services/functionalities for user-defined applications.
2. Discover how these tools have been applied in cutting-edge applications including:
   1. Modeling the effects of neuromodulation on large scale brain dynamics
   2. Spinal cord stimulation for injury rehabilitation
   3. Peripheral nerve stimulation for cardiac health
3. Explore realistic and advanced neurostimulation-related projects related to EM-neuro interactions in both the CNS and PNS directly within Sim4Life and o²S²PARC.

Tutorial Program
09:00 AM        Intro to Image- & Cloud-Based Modeling for Real-World Applications
09:15 AM        Getting Started with o²S²PARC & Sim4Life.web
09:45 AM        Electromagnetic-Neuro Interactions Across Spatio-Temporal Scales (Brain, Spine, Peripheral Nervous System)
10:25 AM        Coffee Break  
10:45 AM        Hands-On Exercises:
                         - Modeling the Brain Response to Non-Invasive Brain Stimulation
                         - Modeling Vagus Nerve Stimulation for Cardiac Health
11:45 AM        Q&A and Closing Remarks

Note:
Login details to Sim4Life and o²S²PARC will be provided to all registered participants. Both platforms can be accessed directly through web browser no installation required.

Citations
[1] https://sim4life.swiss/ https://s4l-lite.io/
[2] https://osparc.io/ github
[3] https://tip-lite.science/, user manual
[4] Karimi, F., Steiner, M., Newton, T., Lloyd, B.A., Cassara, A.M., de Fontenay, P., Farcito, S., Triebkorn, J.P., Beanato, E., Wang, H. and Iavarone, E., 2025. Precision non-invasive brain stimulation: an in silico pipeline for personalized control of brain dynamics. Journal of Neural Engineering, 22(2), p.026061. DIO: https://doi.org/10.1088/1741-2552/adb88f

TL;DR
This tutorial demonstrates how to simulate a navigating agent (RatInABox), collect its visual data (Blender), build a Recurrent Neural Network (RNN) to model hippocampal-like spatial representations (Pytorch), and analyze its latent representations.

INTRODUCTION
The intricate interplay between sensory perception and the "cognitive map" of space (O'Keefe & Nadel, 1979) allows animals to navigate complex environments, interact with them in purposeful ways, and adapt to new situations. In the hippocampal formation, various classes of spatially modulated neurons support navigation by integrating sensory inputs to construct flexible internal models of the world (Behrens et al., 2018). Vision, in particular, plays a crucial role in guiding movement and shaping neural representations of space. However, since time is linear and irreversible, animals must rely on sequential observations to infer environmental structure. These experiences are then transformed into internal models that capture the relationships between elements in the world (Buzsáki & Tingley, 2018; Stachenfeld et al., 2017).

DESCRIPTION
This tutorial introduces computational methods for studying these processes. First, we demonstrate how to simulate the trajectories of virtual agents resembling animals (such as rodents and ferrets) with RatInABox and how to automatically collect visual information while agents navigate a highly customisable virtual environment using the Blender Python API. Next, we explore how shallow RNNs can be trained (using Pytroch) to develop biologically-plausible allocentric tuning curves in their latent space representations, resembling the activity of spatially selective neurons in the hippocampal formation. These models enable us to predict how specific experiences or stimuli may facilitate or hinder the emergence of spatial neurons in the hippocampus, for example in the context of development. Moreover, they can serve as surrogate models for evaluating navigational performance under different sensory conditions or targeted neuronal lesions.

Brain-inspired computing looks to mimic how the human brain works to improve artificial intelligence (AI) systems. This area has gained a lot of interest recently because it helps us create stronger and more efficient AI models while tackling challenges faced by current artificial neural networks.

This workshop will cover a range of topics, including biological neural networks, cognitive computing, and biologically-inspired algorithms. We will discuss how learning from the brain's structure and operations can lead to new solutions for complex issues in AI, machine learning, and data processing.

The workshop will include talks from experts in the field and interactive panel discussions. Participants will have the chance to collaborate, share ideas, and connect with others who are excited about using biological principles to advance technology.

Full program in this link.

Schedule
9:00 AM - 9:30 AM Speaker: Rui Ponte Costa, University of Oxford
A theory of self-supervised learning in cortical layers
9:30 AM - 10:00 AM Speaker: Guillaume Bellec, Vienna University of Technology
Validating biological mechanisms in deep brain models with optogenetic perturbation testing
10:00 AM - 10:30 AM Speaker: Guozhang Chen, Peking University
Characteristic differences between computationally relevant features of cortical microcircuits and artificial neural networks
10:30 AM - 11:00 AM Coffee Break
11:00 AM - 11:30 AM Speaker: Robert Legenstein, Graz University of Technology
Rapid learning with phase-change memory-based neuromorphic hardware through learning-to-learn
11:30 AM - 12:00 PM Speaker: Shogo Ohmae, Chinese Institute for Brain Researc
World-model-based versatile computations in the neocortex and the cerebellum
12:00 PM - 12:30 PM Speaker: Yuliang Zang, Tianjin University
Biological strategies for efficient learning in cerebellum-like circuits
12:30 End of Workshop and Lunch Break

Full program in this link.

Please visit the dedicated website for full details: https://nicolomeneghetti.github.io/ECP_CNS2025_Wshop/

Simulating large-scale neural activity is essential for understanding brain dynamics and linking in silico models to experimentally measurable signals like LFP, EEG, and MEG. These simulations, ranging from detailed biophysical models to simplified proxies, bridge microscale neural dynamics with meso- and macro-scale recordings, offering powerful tools to interpret data, refine analyses, and explore brain function. Recent advances have demonstrated the clinical and theoretical value of such models, shedding light on oscillations, excitation-inhibition balance, and biomarkers of neurological disorders like epilepsy, Alzheimer's, and Parkinson’s disease. This workshop will cover the latest methodologies, hybrid modeling approaches, and applications of brain signal simulations.


09:15 – 09:50
Dominik Peter Koller, Berlin Institute of Health (BIH) at Charité – Universitätsmedizin Berlin, Berlin, Germany
Title: "How structural connectivity directs cortical traveling waves and shapes frequency gradients"

09:50 – 10:25
Gaute T. Einevoll, Department of Physics, University of Oslo, Oslo, Norway
Title: "Modeling electric brain signals and stimulation"

10:30 – 11:00
Coffee Break

11:00 – 11:35
Johanna Senk, Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany
Title: "Large-scale modeling of mesoscopic networks at single-neuron resolution"

11:35 – 12:10
Pablo Martínez Cañada, Research Centre for Information and Communications Technologies (CITIC), University of Granada, Granada
Title: "Inverse Modelling of Field Potentials from Simulations of Spiking Network Models: Applications in Neuroscience Research and Clinical Settings"

12:10 – 12:40
Nicolò Meneghetti, The Biorobotics Institute, Sant’Anna School of Advanced Studies, Pisa, Italy
Title: "From microcircuits to mesoscopic signals: a kernel approach to efficient and interpretable LFP estimation"

12:45 - 14.00
Lunch Break

14:15 – 14:50
Emily Patricia Stephen, Department of Math and Statistics, Boston University, Boston, MA, United States of America
Title: "Connecting biophysical models to empirical power spectra using Filtered Point Processes"

14:50 - 15:25
Madeleine Lowery, School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland
Title: "Modelling Neural Activity During Adaptive Deep Brain Stimulation for Parkinson’s Disease"

15:30 - 16:00
Coffee Break 

16:00 – 16:35
Meysam Hashemi, Aix Marseille University INSERM, INS, Institute for Systems Neuroscience, Marseille, France
Title: "Principles and Operation of Virtual Brain Twins"

16:35 - 17:10
Katharina Duecker, Brown University and University of Birmingham,  USA/UK
Title: "The Human Neocortical Neurosolver as an interactive modeling tool to study the multi-scale mechanisms of human EEG/MEG signals"