This paper, published with colleagues from Warwick University and Cambridge University: Petra Vertes, Ruth Nicol, Sandra Chapman, Nicholas Watkins, and Edward Bullmore was the result of inter-disciplinary work funded by the EPSRC – the Engineering and Physical Sciences Research Council (Grant number EP/H02395X/1). We investigated the similarities in the network structure financial markets and brain networks.
Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets – the time series of 90 stocks from the New York stock exchange over a 3-year period, and the fMRI-derived time series acquired from 90 brain regions over the course of a 10-min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties.
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