Organization, development and function of complex brain networks.

By Olaf Sporns, Dante R. Chialvo, Marcus Kaiser, Claus C. Hilgetag. 2004

2,061 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Molecular Biology, Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

In Molecular Biology

In Evaluation & Benchmarks

Citations in the corpus

Local Aggregation for Unsupervised Learning of Visual Embeddings (2019, background): “In contrast to the inefficiency of unsupervised learning in artificial neural networks, humans and non-human primates develop powerful and domain-general visual systems with very few labels [46, 6, 70, 1, 24, 5, 65].”
Network-based statistic: Identifying differences in brain networks (2010, methodology): “…test the structure-function hypothesis (Honey et al., 2009, 2010; Ramani et al., 2004; Skudlarski et al., 2008; Sporns et al., 2000) and as a methodological tool to examine brain network organization, topology and complex dynamics (Bullmore et al., 2009; Hagmann et al., 2008; Sporns et al., 2004).”
Multisensory Stimulation in Stroke Rehabilitation (2012, background): “Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization (Sporns et al., 2004, 2007; Bullmore and Sporns, 2009; Honey et al., 2009; Sporns, 2011).”
Partial correlation for functional brain interactivity investigation in functional MRI (2006, background): “By contrast, it is now believed that processing of a functional task by the brain can only be performed through interaction of segregated regions within a complex network (Hebb, 1949; Tononi et al., 1998; Frackowiak et al., 2004; Sporns et al., 2004).”
Integration of enzyme activities into metabolic flux distributions by elementary mode analysis (2007, neutral): “Graph-theoretical representation The connections between cortical regions can be represented and understood as a graph, eg, [10,24], or complex network, eg, [1].”
Colloquium: Criticality and dynamical scaling in living systems (2017, background): “28 The resulting human connectome turns out to be a network organized in hierarchical modular way (Betzel et al., 2013; Breakspear, 2017; Hagmann et al., 2008; Kaiser, 2011; Meunier et al., 2010; Sporns, 2010; Sporns et al., 2004, 2005).”
The Importance of Neurophysiological Constraints for Modelling the Emergence of Modularity (neutral): “(2004), and Sporns, et al.”
The Metastable Brain (2014, neutral): “…of segregation (tendencies for neural ensembles to diverge and function independently) and integration (tendencies for neural ensembles to converge and work together) (Tononi et al., 1994; Kelso, 1991, 1992, 1995; Friston, 1997; Sporns et al., 2004; Kelso and Tognoli, 2007; Pitti et al., 2008).”
Shape shifting pain: chronification of back pain shifts brain representation from nociceptive to emotional circuits. (2013, background): “, 2013)], with neurobiological theories (McIntosh, 2000; Sporns et al., 2004) that emphasize the importance of the interaction between brain regions in explaining brain function, and with accumulating evidence that distinct emotions cannot be spatially mapped to specific brain regions, and instead t”
Role of Mechanical Factors in the Morphology of the Primate Cerebral Cortex (2006, background): “This observation is explained by the axonal tension model of cortical folding [5], which suggests that the characteristic landscape of convolutions is produced by the nonrandom organization of cortical connection networks [55].”
A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs (2006, background): “It seems likely a priori (Laughlin and Sejnowski, 2003; Sporns et al., 2004; Sporns and Zwi, 2004; Kaiser and Hilgetag, 2004a,b) that similar physical constraints (aging or connection costs) might apply to the formation of whole-brain functional networks and thus account for the empirical form of…”
Hemisphere- and gender-related differences in small-world brain networks: A resting-state functional MRI study (2011, background): “The coexistence of functional segregation and functional integration ensures the effective integration of multiple segregated sources of information in the brain (Tononi et al., 1994; Sporns et al., 2004; Sporns and Zwi, 2004).”
Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer's Disease (2008, background): “and short path length linking individual network nodes (Watts and Strogatz, 1998), is an attractive model for the description of complex brain networks because it not only supports both specialized and integrated information processing (Sporns et al., 2004) but also minimizes wiring costs while maxi”
Graph analysis of the human connectome: Promise, progress, and pitfalls (2013, positive): “Excellent introductions to the basic concepts of graph theory and their application to neuroscience have been provided elsewhere (Albert and Barabasi, 2002; Bullmore and Bassett, 2011; Bullmore and Sporns, 2009; Newman, 2003; Sporns, 2011b, 2012; Sporns et al., 2004; Stam and Reijneveld, 2007).”
Towards the utilization of EEG as a brain imaging tool (2012, background): “Such self-similarity, also called criticality or fractality, appears to be a general key feature of the brain resting-state network, allowing fast adaptations to the quickly changing environment (Sporns et al., 2004).”