Some ideas for project topics and research questions.

Publicly available data sets

My motto: if you can answer a question with existing data, why collect it anew?

• Here is a link to a large database of behavioral datasets.
• Here is a paper describing a database of >145 confidence datasets.
• This paper describes a perceptual decision making task with psychopathology questionnaires, dataset here.

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 models 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.

Neuroscience

• 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.
• Do mice show ‘handedness’, i.e. a preference to respond with ‘rightward’ choices? Based on observation by Sebastian Bruijns, early on in the IBL task. Combine with literature review on handedness across decision-making tasks (especially in mice) with different response modalities.
• Using data from Ni et al, link changes in motivation under methylphenidate (Ritalin) to the Expected Value of Control theory. With Bryant Jongkees. Apply a DDM to go beyond simple P(correct).
• Murray et al. 2014 found that cortical neurons display intrinsic timescales which become longer along the cortical hierarchy, and probably play an important role in longer-timescale functions like information maintenance. Has this finding been replicated in mice (beyond visual areas, see Siegle et al.), and extended to subcortical areas (using the IBL dataset)? Does longer-timescale prior encoding (tracking of the block) mostly depend on neurons with long timescales in the IBL dataset? See also Imani et al. 2023.
  • Related: Cortical neurons display different degrees of intrinsic timescales, with longer timescales towards anterior cortical regions in primates (https://www.nature.com/articles/nn.3862). How do these timescales arise, and what are their roles in computation? One hypothesis is that these gradients arise from the genetic profile of different areas. As we’re collecting the first brain-wide map of mouse neural activity during rest, this idea proposes to decompose the intrinsic timescale structure throughout the brain to different profiles of gene expression (from the Allen Atlas). See also here, here.

Resources

the abstract of Richard Gao at COSYNE 2019: III-89 http://cosyne.org/cosyne19/Cosyne2019_program_book.pdf in humans, the spatial structure of intrinsic fluctuations correlates with the spatial distribution of catecholaminergic receptors

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.

Literature review

• 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.

Climate action

• 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.
• What is the effect of CO2 levels on cognitive function? Collaboration with Francesco Walker, using driving simulator. See https://doi.org/10.1038/s41370-018-0055-8, https://doi.org/10.1029/2019GH000237, 10.1289/ehp.1510037

Random

• Replicate academic family tree clustering using Neurotree.