Year: 2015
Type: dissertation
Abstract: Humans are limited in their capacity to process information about the environment; to choose the most salient details to process, we have to make rapid value appraisals and prioritize our attentional resources. In this proposed study, it is expected that attention is required to learn from affective information. Learning is measured by the difference between update (the difference between the first and second estimation) and the estimation error (the difference between the average likelihood and the first estimation). Using a belief-updating paradigm, participants will be asked to estimate their likelihood of encountering a negative event, once before and once after they receive the average likelihood information. By comparing the difference in estimations after being exposed to desirable or undesirable information and a positive or negative reinforcer across three levels of attentional load, the effects of attention on learning from affective reinforcement can be examined. It is proposed that attention mediates learning from affective information. This is demonstrated by the failure to learn differentially from affective information under high attentional load, while in a no load condition participants will learn differentially according to the type of news and affective reinforcer that they receive. The expected result would indicate that attention is a necessity for optimal learning outcomes, especially when learning from affective information. This has implications in the effectiveness of communicating affective information, such as in the health care field.
Author: Chia Mun Foo
Institution: Claremont Colleges
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2471952272