Some ideas for project topics and research questions.
Decision-making: data analysis
See here for some examples on getting started with existing IBL data.
- Does choice history bias correlate with psychopathology? Reanalyse data from Rouault et al. 2019 by fitting models of choice history bias (e.g. logistic m odels or drift diffusion models).
- How do decision-making strategies (such as perseverance) change with ageing? Fit behavioral models (e.g. Ashwood et al. 2022, Findling et al. 2019) to decision-making data across the lifespan (both mice and humans).
- Do learning and decision-making vary with the biological clock, and is it easier to learn when consistently practicing at the same time of day? Potential collaboration with Christian Tudorache.
- How can we disentangle choice updating from slow drifts in decision criterion? Apply method proposed by Gupta and Brody.
- Test prediction: does inactivation of PPC (LIP inactivation in monkeys or TMS to IPS0/1 or IPS 2/3 in humans) during the ITI reduce choice history bias? Find data or run a TMS experiment.
Decision-making: data collection
- How do decision-making strategies differ across mammalian species? Build and run a human version of the IBL decision task, online and/or in the lab with EEG.
- Are choice history biases consistent across different decision-making tasks, and over time?
- Can zebrafish learn the same decision-making tasks as mice and humans? Collaboration with Christian Tudorache.
- How do different types of neural noise (measured with fMRI, EEG or cellular recordings) change with ageing?
- The role of posterior parietal cortex in history-dependent choice biases.
- What type of messaging is most effective to mobilize people into climate actions?
- How can we improve virtual conferences and meetings to make them a better replacement for in-person events?
- What is the carbon footprint of neuroscience data? Potential collaboration with Charlotte Rae.
- How can we best visualize uncertainty and risk to communicate the urgency of the climate crisis? Data visualization and UX design.
- Analyze flight/travel data from university employees to see where the biggest improvements can be made. What kind of behavioral interventions (policy, messaging, transparency) may help reduce aviation-related CO2 emissions?
- Visualize and describe the impacts of climate change on our city, university, faculty - and ways to adapt to sea-level rise, hotter summers, extreme weather.