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2014-07-17Buch DOI: 10.18452/4523
Portfolio Decisions andBrain Reactions via theCEAD method
dc.contributor.authorMajer, Piotr
dc.contributor.authorMohr, Peter N.C.
dc.contributor.authorHeekeren, Hauke R.
dc.contributor.authorHärdle, Wolfgang Karl
dc.date.accessioned2017-06-16T01:03:00Z
dc.date.available2017-06-16T01:03:00Z
dc.date.created2014-09-11
dc.date.issued2014-07-17
dc.date.submitted2014-07-17
dc.identifier.issn1860-5664
dc.identifier.urihttp://edoc.hu-berlin.de/18452/5175
dc.description.abstractDecision making can be a complex process requiring the integration of several attributes of choice options. Understanding the neural processes underlying (uncertain) investment decisions is an important topic in neuroeconomics. We analyzed functional magnetic resonance imaging (fMRI) data from an investment decision (ID) study for ID-related effects. We propose a new technique for identifying activated brain regions: Cluster, Estimation, Activation and Decision (CEAD) method. Our analysis is focused on clusters of voxels rather than voxel units. Thus, we achieve a higher signal to noise ratio within the unit tested and a smaller number of hypothesis tests compared with the often used General Linear Model (GLM). We propose to first conduct the brain parcellation by applying spatially constrained NCUT spectral clustering. The information within each cluster can then be extracted by the flexible DSFM dimension reduction technique and finally be tested for differences in activation between conditions. This sequence of Cluster, Estimation, Activation and Decision admits a model-free analysis of the local BOLD signal. Applying a GLM on the DSFM-based time series resulted in a significant correlation between the risk of choice options and changes in fMRI signal in the anterior insula (aINS) and DMPFC. Additionally, individual differences in decision-related reactions within the DSFM time series predicted individual differences in risk attitudes as modeled with the framework of the mean-variance model.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectriskeng
dc.subjectfMRIeng
dc.subjectsemiparametric modeleng
dc.subjectdecision makingeng
dc.subjectfactor structureeng
dc.subjectrisk attitudeeng
dc.subjectneuroeconomicseng
dc.subjectbrain imagingeng
dc.subjectspatial clusteringeng
dc.subjectinference on clusterseng
dc.subjectCEAD methodeng
dc.subject.ddc310 Statistik
dc.subject.ddc330 Wirtschaft
dc.titlePortfolio Decisions andBrain Reactions via theCEAD method
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-100220141
dc.identifier.doihttp://dx.doi.org/10.18452/4523
local.edoc.container-titleSonderforschungsbereich 649: Ökonomisches Risiko
local.edoc.pages40
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2014
local.edoc.container-issue36
local.edoc.container-year2014
local.edoc.container-erstkatid2195055-6

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