Anterior Cingulate Cortex: Contributions to Social Cognition. / Apps, Matthew.

2012. 286 p.

Research output: ThesisDoctoral Thesis

Unpublished

Documents

Abstract

It has been suggested that the Anterior Cingulate Cortex (ACC) plays an important role in decision-making. Activity in this area reflects processing related to two principles of Reinforcement Learning Theory (RLT): (i) signalling the predicted value of actions at the time they are instructed and (ii) signalling prediction errors at the time of the outcomes of actions. It has been suggested that neurons in the gyrus of the ACC (ACCg) process information about others’ decisions and not one’s own. An important aim of this thesis is to investigate whether the ACCg processes others’ decisions in a manner that conforms to the principles of RLT. Four fMRI experiments investigate activity in the ACCg at the time of cues that signal either the predicted value of others’ actions or that signal another’s predictions are erroneous.
• Experiment 1: Activity in the ACCg occurred when the outcome of another’s decision was unexpectedly positive.
• Experiment 2: Activity in the ACCg varied parametrically with the discrepancy between another’s prediction of an outcome and the actual outcome known by the subject, in a manner that conformed to the computational principles of RLT.
• Experiment 3: Activity in the ACCg varied with the predicted value of a reward, discounted by the amount of effort required to obtain it.
• Experiment 4: Activity in the ACCg varied with the value of delayed rewards that were discounted in a manner that conformed to a social norm.
These results support the hypothesis that the ACCg processes the predicted value of others’ actions and also signals when others’ predictions about the value of their actions are erroneous, in a manner that conforms to the principles of RLT.
Original languageEnglish
QualificationPh.D.
Awarding Institution
Supervisors/Advisors
Award date1 Apr 2012
Publication statusUnpublished - 2012
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 4739892