Complex Systems and X-Events
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Rescooped by Roger D. Jones, PhD from Talks!

Dead stuff: The secret ingredient in our food chain - John C. Moore

Dead stuff: The secret ingredient in our food chain - John C. Moore | Complex Systems and X-Events |
When you picture the lowest levels of the food chain, you might imagine
herbivores happily munching on lush, living green plants. But this
idyllic image leaves out a huge (and slightly less appetizing) source of
nourishment: dead stuff. John C. Moore details the "brown food chain,"
explaining how such unlikely delicacies as pond scum and animal poop
contribute enormous amounts of energy to our ecosystems.

Via Eric L Berlow, Complexity Digest
Eric L Berlow's curator insight, August 31, 2014 12:20 PM

This is the first lesson in our Ecology Series in collaboration with TED Ed . The series focuses on networks in ecology. This one by John Moore explores the wonderful world of detritus. Most of us know that nature 'recycles' dead parts - but this lesson highlights that when you scale this process to the entire ecosystem, dead stuff, and 'brown' food chains, are an unexpectedly huge source of energy that fuels most ecosystems. 

Rescooped by Roger D. Jones, PhD from Complejidad en Blogs!

Networked for complexity

Networked for complexity | Complex Systems and X-Events |

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, Christophe Bredillet, Bernard Ryefield, Complejidady Economía
Kenneth Mikkelsen's curator insight, November 25, 2013 5:39 PM

Terrific blog post by Richard Martin. You should follow Richard on [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.

Rescooped by Roger D. Jones, PhD from Papers!

Contributions and challenges for network models in cognitive neuroscience

Contributions and challenges for network models in cognitive neuroscience | Complex Systems and X-Events |

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)

Via Complexity Digest
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