Learning to be yourself: Disentangling the mechanisms of agency attribution

DOI

There are great similarities between the actions of our self and others, not only in terms of movement characteristics, but also in the way those movements are processed in the brain. It is this similarity that allows humans to interpret the actions, intentions and desires of other people. Before we can begin to do this, however, we must be aware whether the source of a perceived action is our self or someone else. The ability to correctly identify our own actions from those of others (agency attribution) is a fundamental component of normal human social interaction and self-awareness. Disentangling the various conscious and unconscious brain mechanisms involved in agency attribution has proved problematic. By varying the accuracy of information regarding the seen and felt position of the hand during motion, using a variety of techniques, including robotic arms, virtual reality and transcranial magnetic stimulation of the brain, this research aims to investigate the contribution of different brain mechanisms in order to provide a greater understanding of how agency is attributed in normal and abnormal populations.

Opportunity sample, Student population, observation units = groups. Collected data was either in the form of yes/no (or self/other) verbal or keypress responses stored electronically during experiments or in the form of kinematic profiles of upper limb movements recorded electronically as x,y,z coordinates of the index finger over time. All data was original and not derived in any part from any other source.

Identifier
DOI https://doi.org/10.5255/UKDA-SN-850405
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=8301abd878b4aeb436be8b528c6d2ea6e682d6340a27ab8d1bc99a87f79dab14
Provenance
Creator Newport, R
Publisher UK Data Service
Publication Year 2010
Funding Reference Economic and Social Research Council
Rights Roger Newport; The Data Collection only consists of metadata and documentation as the data could not be archived due to legal, ethical or commercial constraints. For further information, please contact the contact person for this data collection.
OpenAccess true
Representation
Language English
Resource Type Numeric
Discipline Psychology; Social and Behavioural Sciences
Spatial Coverage United Kingdom