dc.contributor.author |
Chicharro Raventós, Daniel |
dc.contributor.author |
Ledberg, Anders |
dc.date |
2012 |
dc.identifier.citation |
Chicharro D, Ledberg A. When two become one: the limits of causality analysis of brain dynamics. PLoS ONE. 2012;7(3):1-16. DOI: 10.1371/journal.pone.0032466. |
dc.identifier.citation |
1932-6203 |
dc.identifier.citation |
http://dx.doi.org/10.1371/journal.pone.0032466 |
dc.identifier.uri |
http://hdl.handle.net/10230/25845 |
dc.format |
application/pdf |
dc.language.iso |
eng |
dc.publisher |
Public Library of Science |
dc.relation |
PLoS ONE. 2012;7(3):1-16 |
dc.relation |
info:eu-repo/grantAgreement/EC/FP7/269921 |
dc.rights |
@ 2012 Chicharro, Ledberg. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits/nunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.rights |
http://creativecommons.org/licenses/by/4.0/ |
dc.title |
When two become one: the limits of causality analysis of brain dynamics |
dc.type |
info:eu-repo/semantics/article |
dc.type |
info:eu-repo/semantics/publishedVersion |
dc.description.abstract |
Biological systems often consist of multiple interacting subsystems, the brain being a prominent example. To understand/nthe functions of such systems it is important to analyze if and how the subsystems interact and to describe the effect of/nthese interactions. In this work we investigate the extent to which the cause-and-effect framework is applicable to such/ninteracting subsystems. We base our work on a standard notion of causal effects and define a new concept called natural/ncausal effect. This new concept takes into account that when studying interactions in biological systems, one is often not/ninterested in the effect of perturbations that alter the dynamics. The interest is instead in how the causal connections/nparticipate in the generation of the observed natural dynamics. We identify the constraints on the structure of the causal/nconnections that determine the existence of natural causal effects. In particular, we show that the influence of the causal/nconnections on the natural dynamics of the system often cannot be analyzed in terms of the causal effect of one subsystem/non another. Only when the causing subsystem is autonomous with respect to the rest can this interpretation be made. We/nnote that subsystems in the brain are often bidirectionally connected, which means that interactions rarely should be/nquantified in terms of cause-and-effect. We furthermore introduce a framework for how natural causal effects can be/ncharacterized when they exist. Our work also has important consequences for the interpretation of other approaches/ncommonly applied to study causality in the brain. Specifically, we discuss how the notion of natural causal effects can be/ncombined with Granger causality and Dynamic Causal Modeling (DCM). Our results are generic and the concept of natural/ncausal effects is relevant in all areas where the effects of interactions between subsystems are of interest. |
dc.description.abstract |
The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007- 2013) under grant agreement no. 269921 (BrainScaleS). AL is supported by the Ramon y Cajal program from the Spanish government. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. |