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Related Experiment Video

Updated: Feb 2, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Spatial Embedding Imposes Constraints on Neuronal Network Architectures.

Jennifer Stiso¹, Danielle S Bassett²

¹Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

Trends in Cognitive Sciences

|November 20, 2018

Summary

This summary is machine-generated.

Physical constraints shape brain network development and function. Understanding these spatial rules reveals complex topologies and neural dynamics, informing disease mechanisms.

Keywords:

dynamics network neuroscience spatial embedding

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Area of Science:

Neuroscience
Network Science
Computational Biology

Background:

Network science tools offer simplified descriptions of neural system spatiotemporal architecture.
These tools often overlook the physical embedding of systems like the brain.
Physical laws critically influence the growth, development, and function of embedded neural networks.

Purpose of the Study:

To review the impact of brain space and volume constraints on neuronal network development.
To demonstrate how these spatial rules generate specific complex topologies.
To explore the influence of these rules on neural dynamics and network dysfunction in disease.

Main Methods:

Review of existing literature on network science and neurodevelopment.
Analysis of how physical constraints dictate network topology formation.
Examination of the relationship between spatial embedding and emergent neural dynamics.

Main Results:

Spatial and volume constraints impose specific rules on neuronal network development.
These rules lead to the emergence of complex, constrained network topologies.
The physical embedding influences the range of possible neural dynamics and disease-related network alterations.

Conclusions:

The physical space of the brain is a fundamental determinant of neural network structure and function.
Understanding these spatial embedding rules is crucial for deciphering neural dynamics and neurological disorders.
Future research should focus on advanced models to fully delineate the effects of spatial embedding on neural systems.