[EEG Study] Voluntary Decision-Making and Sense of Agency

Background

The neural mechanisms underlying voluntary (i.e., free) decisions and sense of agency, and the relationship between them have been extensively researched through one-off voluntary decision tasks, whereby participants freely make single, abstract choices between two options (e.g. Bode et al., 2011; Soon et al., 2008). However, in real life, we often make voluntary decisions in dynamic decision environments that evolve over time. In order words, changes within our external environment may require us to re-evaluate initial decisions, which may lead to a change of mind (Brass & Haggard, 2008; Löffler et al., 2020, Rens et al., 2018). This project aims to better understand the neural mechanisms of voluntary decisions and changes of mind, along with the relationship between voluntary decisions, changes of mind, and SoA through two experiments.

Research Questions / Hypotheses

1. What are the neural representations of voluntary decisions in comparison to forced decisions? Additionally, how do these neural representations change from when an initial voluntary decision changes to a forced decision, and conversely, when an initial forced decision changes to a voluntary decision?
2. Can we detect differences in neural patterns between voluntary decisions and forced (i.e., stimulus-driven) decisions?
3. Can we detect differences in neural patterns between high SoA decisions and low SoA decisions?

Participants

41 participants completed the study. Inclusion criteria: between ages 18-65; no history of psychiatric or neurological disorders; correct-to-normal vision

Methods

Methods: (1) Non-invasive scalp electroencephalography (EEG) recordings of brain activity (2) Behavioural data (response times and choices) from computer-based experiments requiring participants to make decisions between options, and subsequent metacognitive judgments (e.g., sense of agency, experienced freedom, desire to switch options). Participants will complete computer-based experiments in a well-controlled laboratory setting designed for EEG acquisition. During the experiment, participants will be presented with stimuli on the screen and will make keypresses on a response device (e.g., keyboard) to register their decisions or choices. EEG will be simultaneously recorded.

Results

Behavioural data (response times and choices) will be fit to various models to best account for how voluntary decisions are made. EEG data will be pre-processed and analysed using multivariate pattern analyses and regression modelling.

Implications

If neural processes underlying voluntary change-of-mind decisions are indeed distinct from single (one-off) voluntary decisions, we expect to be able to decode differences between patterns of neural activity between the two types of decisions. For example, the trained machine learning classifier used in the multivariate pattern analysis should be able to decode between the same free initial/single decisions and change-of-mind decisions. The results of this study will be presented at conferences such as the Australasian Cognitive Neuroscience Society (ACNS) conference and the Association for the Scientific Study of Consciousness (ASSC) conference, and will be published in a journal once the manuscript is ready.