Table of Contents

A Note on Shapley Ratings in Brain Networks

Marieke Musegaas, Tilburg University - Center for Economic Research (CentER)
Bas Dietzenbacher, Tilburg University - Center for Economic Research (CentER), Tilburg University - Department of Econometrics & Operations Research
Peter Borm, Tilburg University - Center for Economic Research (CentER), Tilburg University - Department of Econometrics & Operations Research

The Neural Schema for Big Data

Suraj Kumar, Government of India


"A Note on Shapley Ratings in Brain Networks" Free Download
CentER Discussion Paper Series No. 2016-025

MARIEKE MUSEGAAS, Tilburg University - Center for Economic Research (CentER)
BAS DIETZENBACHER, Tilburg University - Center for Economic Research (CentER), Tilburg University - Department of Econometrics & Operations Research
PETER BORM, Tilburg University - Center for Economic Research (CentER), Tilburg University - Department of Econometrics & Operations Research

We consider the problem of computing the influence of a neuronal structure in a brain network. Abraham, Kotter, Krumnack, and Wanke (2006) computed this influence by using the Shapley value of a coalitional game corresponding to a directed network as a rating. Kotter, Reid, Krumnack, Wanke, and Sporns (2007) applied this rating to large-scale brain networks, in particular to the macaque visual cortex and the macaque prefrontal cortex. We introduce an alternative coalitional game that is more intuitive from a game theoretical point of view. We use the Shapley value of this game as an alternative rating to analyze the macaque brain networks and corroborate the findings of Kotter et al. (2007). Moreover, we show how missing information on the existence of certain connections can readily be incorporated into this game and the corresponding Shapley rating.

"The Neural Schema for Big Data" Free Download

SURAJ KUMAR, Government of India

The paper tries to resolve the complexity encountered in processing of Big Data through various methodology which includes Reverse Geometric Data Perturbation to estimate the spectral flow of data through new learning methods for underlying neural networks. It also has insights into the Banach-Tarsky Paradox to separate the different zones of spectrum, which helps in preventing the analysis of overlapping. The MapReduce implementation can have multiple p-values separation at sublevels to sample out the data and demarcate the different levels of spectrum along with inspecting out the uncertainty in each step as in Monty Hall Problem. It uses the statistical reference to the processing of data in Large Hadrons Collider which extracts out data in ratio 1:6000 for interesting to non-interesting physics which is further reduced in next step cumulating to 1:6000000. It also uses the data processing mechanism of Universe defined through Spiral Hashed Information Vessel.


About this eJournal

This eJournal distributes working and accepted paper abstracts focused on research where economic outcomes are the product of many individual decisions, constrained by scarcity, and equilibrium forces that simultaneously shape a person's social networks and the institutionally defined rules of the game. Decisions are made by computations in the brain which produce action-choices that directly affect the homeostatic wellbeing of the individual and choices that indirectly change wellbeing by changing an individual's future constraints, the scope of their social networks, and their message sending rights within the institutions they participate. Neuroeconomics broadly speaking is interested in the study of these computations and the resulting choices they produce. This includes experiments that attempt to understand the mechanisms of neuronal computations that produce action-choices, theories which predict how neuronal computations in socio-economic environments produce decisions, outcomes and wellbeing, and policy which use our understanding of neuoroeconomic behavior to either build or defend better solutions to societal problems.

Editors: Michael C. Jensen, Harvard University, and Kevin A. McCabe, George Mason University


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Neuroeconomics eJournal

Harris & Harris Group Professor, Massachusetts Institute of Technology (MIT) - Sloan School of Management, National Bureau of Economic Research (NBER)

Professor, Baylor University - Department of Neuroscience

Professor of Economics and Law, Chapman University - Economic Science Institute, Chapman University School of Law