Professor Adam Sanborn

Supervisor Details

Contact Details

Department of Psychology, University of Warwick

Scientific Background

Research Interests

Computational models are key to understanding the mind and the brain. However, there is no standard model that allows knowledge to be synthesised, organised, and shared widely across tasks. Bayesian models have the scope to be standard models, but do not specify a process, and mismatch key details of human data. AI models are black boxes. Instead, researchers commonly use task-specific process models because they match the details of human data, but they have limited scope, with different approaches being used in different tasks and even for different response modes (e.g., binary choices vs. estimates) within the same task.

My group has explored how Markov Chain Monte Carlo sampling offers a route toward building a standard model of human cognition. Sampling is used in statistics to make complex probabilistic models tractable, internal sampling is a common motif in psychological process models, and it has been used to describe neural activity. While past work has made different assumptions about what is sampled, how samples are processed, etc., for different tasks, our work aims to identify a consistent process that applies to a wide range of tasks and response modes, using it to explain human biases.

Research Groups

Behavioural Science Group

Behaviour Spotlight

Supervision Style

In three words or phrases: Supportive and understanding, detail-oriented, and goal driven.

Provision of Training

We have developed a standard set of techniques used by PhD students and post docs in the lab: https://sampling.warwick.ac.uk/#Materials. You would learn to use these and expand on them as part of your projects, and I and other lab members would help with technical challenges.

Progression Monitoring and Management

We discuss progression together in individual meetings, aiming to make steady progress though with the understanding that some challenges are inherently difficult.

Communication

The team has a Slack channel with which we regularly communicate, normally during working hours during the week. Individuals of course have their own working hours, and there is flexibility as long as you are engaged with the project.

Meetings

PhD Students can expect scheduled meetings with me at least once per week. These meetings will be a mixture of face-to-face and via video chat or telephone. I have an open door policy, but my pattern of being contactable for an instant response is not predictable.

Work Patterns

The timing of work in my lab is completely flexible, and (other than attending pre-arranged meetings) I expect students to manage their own time.

Notice Period for Feedback

I need at least 1 week's notice to provide feedback on written work of up to 5,000 words.

MIBTP Project Details

Primary supervisor for:

Opening up the decision-making process in the mind and the brain

See the PhD Opportunities section to see if this project is currently open for applications via MIBTP.

Please Note: The main page lists projects via BBSRC Research Theme(s) quoted and then relevant Topic(s).

Opening up the decision-making process in the mind and the brain

Secondary Supervisor(s): Professor Nick Chater, Dr Alexander Zhigalov

University of Registration: University of Warwick

BBSRC Research Themes:

Understanding the Rules of Life (Neuroscience and Behaviour)

Project Outline

Imagine seeing a face and trying to describe it. How do you decide whether they are older or younger than you are, and estimate their actual age? Alternatively, imagine making a credit card repayment. How do you decide whether to make the minimum required repayment or repay a higher amount that will reduce interest charges, and then work out exactly what to repay?

In both uncertain situations, Bayesian models prescribe the beliefs people should hold for complex sensory information (e.g., how old a face appears) or complex preferences (e.g., credit card repayments). But while these models predict people’s responses to environmental manipulations, they poorly match people’s decision-making processes. People display biases in both their perceptual and preferential decisions, such estimating a person’s age from their face as too close to their own (Watson, et al, 2016) and making credit card repayments that are too close to the minimum required (and thus are more expensive long-term; Stewart, 2009).

A research group led by Prof. Adam Sanborn and Prof. Nick Chater have developed a new approach that accurately describes this behaviour. This approach qualitatively works both for perceptual tasks like face-age estimation and for cognitive tasks like betting (Zhu, et al., 2024; Psych Review). The sampling process is complex, with sudden large changes and long-range dependencies (Zhu et al., 2022; PLoS Comp Bio; Spicer et al., 2024, Psych Review). Separately, Dr. Alex Zhigalov and colleagues have shown that neural activity contains similar long-range dependencies, which correlate with the dependencies in human behaviour (Palva, et al., 2013, PNAS).

However, the link between the sampling algorithms that describe behaviour and neural activity is unknown. This project will capture this process using behavioural think-aloud procedures and neural decoding. Critical empirical data will be collected, and computational modelling will identify the sampling process and its neural substrate.