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The quest for multiscale brain modeling.

Egidio D'Angelo¹, Viktor Jirsa²

¹Department of Brain and Behavioral Sciences, University of Pavia, and Brain Connectivity Center, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Mondino Foundation, Pavia, Italy.

Trends in Neurosciences

|July 29, 2022

Summary

This summary is machine-generated.

Understanding the brain

Keywords:

brain scales closed-loop controllers digital twins neuronal biophysics virtual brains

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Area of Science:

Neuroscience
Computational Neuroscience
Biophysics

Background:

The brain's multiscale organization is key to its function but remains challenging to model.
Connecting detailed neuronal and synaptic models to large-scale brain functions and behavior is complex.
Inferring neuronal functions from ensemble measurements (e.g., brain activity recordings) is difficult.

Purpose of the Study:

To explore theories and strategies for integrating bottom-up and top-down modeling approaches for the brain.
To facilitate multiscale simulations in virtual brains and neurorobots.
To advance future applications in medicine and information technologies.

Main Methods:

Combining bottom-up models derived from neuronal biophysics principles.
Integrating top-down models based on ensemble network activity and functional principles.
Developing integrative approaches for multiscale brain simulations.

Main Results:

The study considers theoretical frameworks for integrating diverse modeling strategies.
It outlines approaches to bridge microscopic neuronal details with macroscopic brain functions.
The proposed integration aims to enhance the fidelity of virtual brain models.

Conclusions:

Integrative multiscale modeling offers a promising path to understanding brain organization.
These approaches can lead to more effective virtual brain simulations.
This research has implications for advancing neuroscience, medicine, and information technology.