Networks of the BrainAn integrative overview of network approaches to neuroscience, exploring the origins of brain complexity and the link between brain structure and function “This is where we should be looking for solutions to the great mysteries of life and the mind.” —American Scientist Over the last decade, the study of complex networks has expanded across diverse scientific fields. Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. In Networks of the Brain, Olaf Sporns describes how the integrative nature of brain function can be illuminated from a complex network perspective. Highlighting the many emerging points of contact between neuroscience and network science, the book serves to introduce network theory to neuroscientists and neuroscience to those working on theoretical network models. Sporns emphasizes how networks connect levels of organization in the brain and how they link structure to function, offering an informal and nonmathematical treatment of the subject. Networks of the Brain provides a synthesis of the sciences of complex networks and the brain that will be an essential foundation for future research. |
From inside the book
Page vii
... Motifs, Modules, and Hubs 101 7 Economy, Efficiency, and Evolution 127 8 Dynamic Patterns in Spontaneous Neural Activity 149 9 Networks for Cognition 179 Brain Network Disease 207 Network Growth and Development 233 Dynamics: Stability ...
... Motifs, Modules, and Hubs 101 7 Economy, Efficiency, and Evolution 127 8 Dynamic Patterns in Spontaneous Neural Activity 149 9 Networks for Cognition 179 Brain Network Disease 207 Network Growth and Development 233 Dynamics: Stability ...
Page 11
... motifs, and the number and distribution of individual motifs reflect some functional characteristics of the network. In order to assess the significance of a given motif distribution, it is important to compare motifs derived from an ...
... motifs, and the number and distribution of individual motifs reflect some functional characteristics of the network. In order to assess the significance of a given motif distribution, it is important to compare motifs derived from an ...
Page 12
... motif classes. This is because, in its simplest formulation, the clustering coefficient is equivalent to the fraction of fully connected three-node motifs, which are simply triangles. Highly modular graphs often consist of densely ...
... motif classes. This is because, in its simplest formulation, the clustering coefficient is equivalent to the fraction of fully connected three-node motifs, which are simply triangles. Highly modular graphs often consist of densely ...
Page 13
... motifs, and modularity evaluate local connectivity and the segregation of the network into communities, another set of measures captures the capacity of the network to engage in more global interactions that transcend the boundaries of ...
... motifs, and modularity evaluate local connectivity and the segregation of the network into communities, another set of measures captures the capacity of the network to engage in more global interactions that transcend the boundaries of ...
Page 63
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Contents
| 1 | |
| 5 | |
| 31 | |
4 A Network Perspective on Neuroanatomy | 51 |
5 Mapping Cells Circuits and Systems | 75 |
6 The Brains Small World | 101 |
7 Economy Efficiency and Evolution | 127 |
8 Dynamic Patterns in Spontaneous Neural Activity | 149 |
11 Network Growth and Development | 233 |
12 Dynamics | 255 |
13 Neural Complexity | 277 |
14 Brain and Body | 305 |
Network Glossary | 327 |
Notes | 331 |
References | 347 |
Index | 389 |
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Common terms and phrases
analysis anatomical architecture areas axonal behavior brain connectivity brain function brain regions causal cells cellular central cerebral cortex chapter cingulate cortex clustering coefficient cognitive coherence components computational connection matrix connection topology connectiv connectivity patterns connectome correlations cortical regions cytoarchitectonic data sets default mode network defined degree distribution effective connectivity environment example figure fMRI Friston frontal func functional connectivity functional networks global graph graph theory hierarchical highly human brain imaging individual interactions large number large-scale lesions linked macaque cortex mapping measures medial models modularity modules motifs nervous system neural activity neural complexity neural dynamics neuroimaging neurons Neurosci optimal organization path length pathways perturbations physiological power law precuneus prefrontal cortex processes responses resting-state result revealed role scale-free scale-free networks scales schizophrenia short path signals small-world networks spatial specific Sporns statistical structural and functional structural connectivity structural network studies synaptic synchronization temporal tion tional Tononi topology tractography variability visual cortex voxels wiring