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Rescooped by Vasileios Basios from Papers
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Contributions and challenges for network models in cognitive neuroscience

Contributions and challenges for network models in cognitive neuroscience | collectibles from scoop.it | Scoop.it

The confluence of new approaches in recording patterns of brain connectivity and quantitative analytic tools from network science has opened new avenues toward understanding the organization and function of brain networks. Descriptive network models of brain structural and functional connectivity have made several important contributions; for example, in the mapping of putative network hubs and network communities. Building on the importance of anatomical and functional interactions, network models have provided insight into the basic structures and mechanisms that enable integrative neural processes. Network models have also been instrumental in understanding the role of structural brain networks in generating spatially and temporally organized brain activity. Despite these contributions, network models are subject to limitations in methodology and interpretation, and they face many challenges as brain connectivity data sets continue to increase in detail and complexity.

 

Contributions and challenges for network models in cognitive neuroscience
• Olaf Sporns
Nature Neuroscience (2014) http://dx.doi.org/10.1038/nn.3690


Via Complexity Digest
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Rescooped by Vasileios Basios from Complexity & Systems
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Dynamical Systems on Networks: A Tutorial

We give a tutorial for the study of dynamical systems on networks, and we focus in particular on ``simple" situations that are tractable analytically. We briefly motivate why examining dynamical systems on networks is interesting and important. We then give several fascinating examples and discuss some theoretical results. We also discuss dynamical systems on dynamical (i.e., time-dependent) networks, overview software implementations, and give our outlook on the field.


Via Bernard Ryefield
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Rescooped by Vasileios Basios from Complexity & Systems
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Dynamical Systems on Networks: A Tutorial

We give a tutorial for the study of dynamical systems on networks, and we focus in particular on ``simple" situations that are tractable analytically. We briefly motivate why examining dynamical systems on networks is interesting and important. We then give several fascinating examples and discuss some theoretical results. We also discuss dynamical systems on dynamical (i.e., time-dependent) networks, overview software implementations, and give our outlook on the field.


Via Bernard Ryefield
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Rescooped by Vasileios Basios from Work Futures
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Networked for complexity

Networked for complexity | collectibles from scoop.it | Scoop.it

In the 21st century, then, the industrial era has given way to the social era, and it is time to rethink both how we work and how we organise ourselves to do so. 


Via Kenneth Mikkelsen
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Kenneth Mikkelsen's curator insight, November 25, 2013 5:39 PM

Terrific blog post by Richard Martin. You should follow Richard on Scoop.it [url=/u/2565370 x-already-notified=1]Richard Martin[/url] and on Twitter here

Stephen Dale's curator insight, November 27, 2013 5:01 AM

I picked out this abstract which resonated with me..." a company is like ‘a social network of productive relationships in which stakeholders are deployed where they are of greatest use. It is designed as a flow of input that can come from anywhere in the network. The work is asynchronous in time and place, and people contribute whatever expertise they have, irrespective of rank or experience." 


Great post.