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. 2016 Jun 27;10:276. doi: 10.3389/fnhum.2016.00276

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Copyright © 2016 Limongi, Pérez, Modroño and González-Mora.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Parameter estimates and PPs (yielded by Bayesian parameter averaging) of the winning model. Tables within the figure show parameter estimates (PPs in parentheses); dynamic causal modeling (DCM) DCM.A, matrix of endogenous connections; DCM.B, matrix of modulatory inputs; DCM.C, matrix of driving inputs. Parameters are not exponentiated. The winning model (top left). Contrast between strengths of rSMG→rAI and rAI→rPreSMA connections (A). Contrast between strengths of rSTR→rAI and rAI→rPreSMA connections (B). Contrast between modulatory effects of absolute TEEs on rAI→rSTR and on rPreSMA→rSTR connections (C). Arrow thickness depicts the relative parameter value or relative connection-strength value. Density plot represents the posterior density yielded by the contrast of interest.