Does the President of the United States control the world?

Not really the economic world. As I am coming off a week that included lots of Presidential face time with the State of the Union on Tuesday and the POTUS visiting my current home town, Decatur, GA, I of course have the POTUS on my mind. As I was doing some productive procrastination, I came across the talk above on TED. In this talk former physicists turned economic modeler, James Glattfelder discusses a paper he and some colleagues publish last year.  Generally the paper concerns using a particular kind of modeling, graph theory (a way simplifying complex systems by examining their interactions with a set of established network rules), to explore who controls the world. In particular, this question is posed in the context of the corporate world and by extension that means the economic world, which in turn means the world.  So what did they find?  They found that an extremely small group of (<1%) corporate decision makers ultimately control a vast network of 600, 000 corporations around the world.  This is important because of what we know about complex systems from other models like eco systems and soon brains. That is small clusters of controlling entities in ANY system lead to a very fragile system, so loss or calamity in one of those super powerful decision makers rapidly affects the entire system (ahem, 2008 great recession). Interestingly the data they are analyzing are from 2007. The thought of the POTUS infiltrated my thoughts while watching the talk because I was thinking about how my 18 year old self would answer the question of ‘Who controls the world’. Then all of my past experiences would have suggested the President of the United States.  Now I realize that while the POTUS is arguably the most powerful person in the world (as I witnessed this week from the incredible security he is provided when he goes ANYWHERE), he surely doesn’t control the world.

So why did this particular talk strike my fancy?  Besides the fact that it is economically interesting, I am actually using graph theory in my dissertation, but instead of analyzing corporations and economic decision makers I’m exploring how regions involved in retrieving autobiographical memories (self-related memories) interact when I cue people with personal memories in an fMRI scanner. The brain also happens to be a complex system that can be simplified by exploring the interactions. Most fMRI studies to date can tell us what and when brain regions are activated, but we have not yet deeply explored how the regions interact with one another during certain processes. The analysis of how regions interact with one another is known as either functional connectivity or effective connectivity. Functional connectivity is how well the signal of a set of regions are correlated and effective connectivity uses various mathematical techniques to explore the direction and strength of connections in a brain network.  Graph theory is an extension of both functional and effective connectivity that is used in studies of structural and functional connections between brain regions to compose large scale brain networks (100s of regions). My dissertation particular concerns trying to distinguish and map the spatiotemporal dynamics of brain networks involved in constructing an autobiographical memory and then elaborating or adding detail to that memory. I’m using graph theory to establish how regions are connected with one another and how those networks change depending on earlier (construction) parts of the retrieval period or late (elaboration) parts of the retrieval period. We expect to find that particular networks are predominant earlier and later in retrieval. I’ll likely be posting more about this, so hopefully that is some sufficient background.

Take home point:  we are constantly embedded in extremely complex situations that can be extremely confusing without the right tools. We now have tools that can at least show us the tangles in the web of interactions and from those tangles we can start to understand the rules of interaction that govern such systems


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