METHODS article
Front. Comput. Neurosci.
Volume 19 - 2025 | doi: 10.3389/fncom.2025.1607239
System-Level Brain Modeling
Provisionally accepted
- Lund University, Lund, Sweden
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System-level brain modeling is a powerful method for building computational models of the brain and allows biologically motivated models to produce measurable behavior that can be tested against empirical data. System-level brain models occupy an intermediate position between detailed neuronal circuit models and abstract cognitive models. They are distinguished by their structural and functional resemblance to the brain, while also allowing for thorough testing and evaluation. In designing system-level brain models, several questions need to be addressed.What are the components of the system? At what level should these components be modeled?How are the components connected-that is, what is the structure of the system? What is the function of each component? What kind of information flows between the components, and how is that information coded? We mainly address models of cognitive abilities or subsystems that produce measurable behavior rather than models that to reproduce internal states, signals or activation patterns. In this method paper, we argue that system-level modeling is an excellent method for addressing complex cognitive and behavioral phenomena.
Keywords: computational brain models, System-level, Real-time, Robotics, modeling
Received: 07 Apr 2025; Accepted: 25 Jun 2025.
Copyright: © 2025 Johansson, Tjøstheim and Balkenius. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Birger Johansson, Lund University, Lund, Sweden
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