Decision-making during action
Year: 2022
Type: dissertation
Abstract: Decision making requires coordinating motor actions that are necessary to report the choices and sample relevant information from the environment. For instance, when riding a bike on a busy road, rider must both pedal while deliberating over the upcoming sensory information in order to make subsequent decisions about when to make a turn. Embodied decision making is a recent framework that aims to investigate such situations and understand the links between our actions and decisions. This doctoral thesis takes embodied decision accounts as a central theoretical stance and studies various important aspects of decision making during motor action. The main locus of this research is to understand how actions that are needed for evidence accumulation influence and interact with the decision making process. To this end, we present here three experimental works and their results. In the first study, we found that sampling movements and response related movements are subject to online interaction during a categorical decision making task. In the second study, we delved into how physical effort of actions that are required to sustain stimuli influence the speed and accuracy of responses. The results showed that effort induced faster and less accurate decisions similar to strict time constraints. We concluded that effort induces urgency over decision making. In the final study, our goal was to test whether physical effort induce higher arousal levels which might have a role in updating speed and accuracy trade-off under effortful actions. The data showed that tonic pupil sizes (an index for arousal) was significantly modulated by effort and correlated with speed and accuracy of responses. Overall, these findings contributed novel evidences on the links between action and decision, especially in cases when evidence accumulation is bound to motor actions.
Author: Ozbagci, Duygu
Language: English
Topic: Motor Control and Adaptation
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7046331008