A Tutorial in Connectome Analysis: Topological and Spatial Features of Brain Networks
arXiv:1105.4705 · doi:10.1016/j.neuroimage.2011.05.025
Abstract
High-throughput methods for yielding the set of connections in a neural system, the connectome, are now being developed. This tutorial describes ways to analyze the topological and spatial organization of the connectome at the macroscopic level of connectivity between brain regions as well as the microscopic level of connectivity between neurons. We will describe topological features at three different levels: the local scale of individual nodes, the regional scale of sets of nodes, and the global scale of the complete set of nodes in a network. Such features can be used to characterize components of a network and to compare different networks, e.g. the connectome of patients and control subjects for clinical studies. At the global scale, different types of networks can be distinguished and we will describe Erdös-Rényi random, scale-free, small-world, modular, and hierarchical archetypes of networks. Finally, the connectome also has a spatial organization and we describe methods for analyzing wiring lengths of neural systems. As an introduction for new researchers in the field of connectome analysis, we discuss the benefits and limitations of each analysis approach.
Neuroimage, in press
References in corpus (16)
- Modularity and community structure in networks
- Power-law distributions in empirical data
- Uncovering the overlapping community structure of complex networks in nature and society
- Hierarchical structure and the prediction of missing links in networks
- Scale-free brain functional networks
- Hierarchical modularity in human brain functional networks
- Nonoptimal Component Placement, but Short Processing Paths, due to Long-Distance Projections in Neural Systems
- Simulation of Robustness against Lesions of Cortical Networks
- Spatial Growth of Real-world Networks
- Optimal hierarchical modular topologies for producing limited sustained activation of neural networks
- Mean clustering coefficients: the role of isolated nodes and leafs on clustering measures for small-world networks
- Criticality of spreading dynamics in hierarchical cluster networks without inhibition
- Neural development features: Spatio-temporal development of the Caenorhabditis elegans neuronal network
- Developmental time windows for spatial growth generate multiple-cluster small-world networks
- Beyond the average: Detecting global singular nodes from local features in complex networks
- Automatic Network Fingerprinting through Single-Node Motifs
Cited by in corpus (39)
- Colloquium: Criticality and dynamical scaling in living systems
- Graph analysis of functional brain networks: practical issues in translational neuroscience
- Griffiths phases and the stretching of criticality in brain networks
- Model-free reconstruction of neuronal network connectivity from calcium imaging signals
- Metrics for Graph Comparison: A Practitioner's Guide
- Control of Dynamics in Brain Networks
- Preferential Detachment During Human Brain Development: Age- and Sex-Specific Structural Connectivity in Diffusion Tensor Imaging (DTI) Data
- Evolving networks in the human epileptic brain
- Clustering coefficients for correlation networks
- Resting-State Functional Connectivity in Late-Life Depression: Higher Global Connectivity and More Long Distance Connections
- Frustrated hierarchical synchronization and emergent complexity in the human connectome network
- Resolving structural variability in network models and the brain
- Resolving Structure in Human Brain Organization: Identifying Mesoscale Organization in Weighted Network Representations
- Evolution and development of Brain Networks: From Caenorhabditis elegans to Homo sapiens
- The Potential of the Human Connectome as a Biomarker of Brain Disease
- Griffiths phases and localization in hierarchical modular networks
- From Caenorhabditis elegans to the Human Connectome: A Specific Modular Organisation Increases Metabolic, Functional, and Developmental Efficiency
- Robustness and modular structure in networks
- Spreading dynamics on spatially constrained complex brain networks
- Integrating temporal and spatial scales: Human structural network motifs across age and region-of-interest size
- Developmental time windows for axon growth influence neuronal network topology
- Rips filtrations for quasi-metric spaces and asymmetric functions with stability results
- Network properties of healthy and Alzheimer's brains
- Predicting age of human subjects based on structural connectivity from diffusion tensor imaging
- Visualization in Connectomics
- Modelling on the very large-scale connectome
- Multi-view Graph Embedding with Hub Detection for Brain Network Analysis
- The Griffiths Phase on Hierarchical Modular Networks with Small-world Edges
- Ensemble learning with 3D convolutional neural networks for connectome-based prediction
- Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity
- Multiscale Comparative Connectomics
- Network biomarkers of schizophrenia by graph theoretical investigations of Brain Functional Networks
- A hierarchical network organization helps to retain comparable oscillation patterns in rats and human-sized brains
- Common Connectome Constraints: From C. elegans and Drosophila to Homo sapiens
- Strong connectivity and its applications
- Homomorphisms of connectome graphs
- Connectome graphs and maximum flow problems
- Scalable Algorithms for Generating and Analyzing Structural Brain Networks with a Varying Number of Nodes
- A Geometric Chung Lu model and the Drosophila Medulla connectome