Characterizing how Misinformation Influences Decision-making: choice heuristics and neural correlates
- Supervisors: Dr Lucie Charles and Dr Rani Moran
- Funding: QMUL Principal's Studentship
- Deadline: 31st January 2024
- Expected Start Date: Sept 2024
Research environment
The School of Biological and Behavioural Sciences at Queen Mary is one of the UK’s elite research centres, according to the 2021 Research Excellence Framework (REF). We offer a multi-disciplinary research environment and have approximately 180 PhD students working on projects in the biological and psychological sciences. Our students have access to a variety of research facilities supported by experienced staff, as well as a range of student support services.
Dr Charles' lab studies the cognitive processes allowing humans to introspect and evaluate their own thoughts and action. Research in the lab uses neuroimaging (fRMI & EEG), online and lab-based behavioural studies to understand the cognitive processes underlying decision-making and metacognition, with a particular focus on confidence, freedom of choice and action awareness.
Training and development
Our PhD students become part of Queen Mary’s Doctoral College which provides training and development opportunities, advice on funding, and financial support for research. Our students also have access to a Researcher Development Programme designed to help recognise and develop key skills and attributes needed to effectively manage research, and to prepare and plan for the next stages of their career.
During the PhD, the student will learn a diverse set of skills including behaviroual and electrography data collection (EEG), EEG analysis, bayesian reasonning, complex statistical analysis, machine learning, computational modelling, coding in several languages (Matlab, Javascript, Python), project management and academic writing.
Project description
The question of fake news and choice manipulation has emerged as a topical issue in recent years, following reports of inappropriate political influence and the rise of conspiracy theories through social media. An important component of this issue is how people use the reliability of the information presented to them to make choices. Importantly, despite clear mathematical models of how reliability of information should inform choice (Tenenbaum et al., 2006) and the wide use of reliability indicators to inform consumer behaviour(Hoffart et al., 2019), there remains a lack of understanding on how humans use explicit cues about reliability of information to make choices.
This project will capitalize on ongoing research by Dr Charles on how people sample information flagged with different levels of reliability (Jiwa et al., n.d.; Kummen et al., 2023). First, it will explore the heuristics people use to integrate information of different reliability levels (Tenenbaum et al., 2006), using optimal Bayesian reasoning as a benchmark of optimality. Electro-encephalography (EEG) will be used to uncover the related neural markers of such process. It will then test whether reliably wrong information might be integrated less optimally in choice, despite being equally informative. It will also investigate how data visualization can help people use reliability cues optimally. Finally, we will explore how reliability weighting is influenced by social contexts, exploring how the trustworthiness of an agent influences decision making.
This PhD studentship will produce fundamental and applied research on cognitive neuroscience, neuroeconomics, behaviour change and social psychology. We will use ecologically valid tasks simulating online content such as social media thread and search results to understand how people sample information in everyday life. Stimuli will reproduce realistic examples of online content to help inform governments and policy maker and maximize research impact.
Funding
The studentship is funded by Queen Mary and will cover Home tuition fees, and provide an annual tax-free maintenance allowance for 3 years at the UKRI rate (£20,622 in 2023/24).
Eligibility and applying
Applications are invited from outstanding candidates with or expecting to receive a first or upper-second class honours degree [and a masters degree] in an area relevant to the project such as Psychology, Cognitive Sciences and Neuroscience. Candidates with a degree in Biology, Economics, Mathematics, Statistics, Competer Sciences or Engineering are also encouraged to apply. A masters degree is desirable, but not essential.
Prior experience with behavioural and EEG data collection, data analysis, statistics, coding and academic writing are desirable.
Applicants from outside of the UK are required to provide evidence of their English Language ability. Please see our English Language requirements page for details: https://www.qmul.ac.uk/international-students/englishlanguagerequirements/postgraduateresearch/
Informal enquiries about the project can be sent to to Lucie Charles at l.charles@qmul.ac.uk
Formal applications must be submitted through our online form by 31st January 2024 for consideration, including a CV, personal statement and qualifications.
References
- Hoffart, J. C., Olschewski, S., & Rieskamp, J. (2019). Reaching for the star ratings: A Bayesian-inspired account of how people use consumer ratings. Journal of Economic Psychology, 72, 99–116. https://doi.org/10.1016/j.joep.2019.02.008
- Jiwa, M., Yu, Y., Boonyaratvej, J., Ciston, A., Haggard, P., Charles, L., & Bode, S. (n.d.). Exposure to misleading and unreliable information reduces active information-seeking. https://doi.org/10.31234/OSF.IO/4ZKXW
- Kummen, Å., Haggard, P., Williams, G., & Charles, L. (2023). Mistaking opposition for autonomy: psychophysical studies on detecting choice bias. Proceedings of the Royal Society B: Biological Sciences, 290(1996). https://doi.org/10.1098/rspb.2022.1785
- Tenenbaum, J. B., Griffiths, T. L., & Kemp, C. (2006). Theory-based Bayesian models of inductive learning and reasoning. Trends in Cognitive Sciences, 10(7), 309–318. https://doi.org/10.1016/j.tics.2006.05.009