Dr Romy Froemer

Supervisor Details

Contact Details

School of Psychology, University of Birmingham

Scientific Background

Research Interests

Dr Froemer studies the switches by which people flexibly adjust how they learn and make decisions, and how they set these switches according to their momentary goals and motivational states. To address these questions, she combines behavioural measures, computational modelling, eye-tracking, psychophysiological recordings and/or neuroimaging techniques. The long-term goal of her work is to identify levers that empower people to improve not only their learning and decision-making, but also how they feel about it.

Learning
Decision-making
Motivation
Metacognition
Cognitive Control

Scientific Inspiration

My research is inspired by a range of people, out of the box thinkers like Rasha Abdel Rahman and Amitai Shenhav, curious lifelong learners like Matthew Nassar and knowledge beasts like Michael J Frank. In terms of scientific overlap, I believe I am most inspired by Nick Yeung. All of these people are not only fantastic researchers, but also kind and supportive mentors who know how to instil the same curiosity in their mentees and pass on their knowledge. This is another reason I find them inspiring.

Supervision Style

In three words or phrases: In my supervision, I aim to support students in growing into curious, learning-oriented and independent researchers. How exactly I achieve this will depend on the student, their needs and their style. I will make sure that on that path, the student will generate products and reach milestones that allow them to continue on the academic path if they so choose.

Provision of Teaching

I aim to first set the foundation for independent growth by providing structure, knowledge and skills training that you can build on as your grow more independent.

I am – at least initially what one would call a hand-on mentor and rather closely involved in the work until you have acquired a level of skill that allows you to move forward independently and likely beyond what I am able to teach. When I consider this point reached will likely vary across tasks and it does not mean that at that point your development in this domain is complete.

In my lab we always strive to improve, and that includes my mentoring. If the way I am training you is not working for you, it is our shared responsibility to find a way that does work. If it could be better, let’s make it better.

Progression Monitoring and Management

We will set goals together for different timelines (PhD, year, month, week), and regularly assess progress towards these goals and whether these goals are still appropriate. This is a dynamic, collaborative process intended to help you make the best out of your PhD experience.

For day-to-day research activities, I expect a certain level of effort to independently solve problems. However, ultimately progress is more important than independence. If you have tried solving a problem independently and are stuck, we want to catch that early and try getting you through the bottleneck together so that you can continue on your path.

I will clearly communicate preferences for organization and administration of research that I have developed to help reliable and reproducible implementation of research and progress tracking when you start. I prefer that you use these tools. If they are not working for you and you have suggestions for better approaches, we can test these and potentially move towards a better system as a group. Otherwise, I will need you to comply with the labs standard operating procedures to assure quality.

Communication

The lab has 2 main communication channels: Slack and Notion. You can slack me any time. I try to check regularly, but I have notifications snoozed to not get distracted during the day, so it might sometimes take an hour or even longer until I respond. If things are really urgent, you can always stop by my office. Longer term project related activities are coordinated through notion. We have a project tracker where goals are set and monitored, and where you can tag me if you need help with anything or want to show me the latest cool results.

You can always send me research updates! Every PI loves that and I am no exception. Give the relevant context for the things your sending me, so I remember what this is about and so that I can properly celebrate your progress!

I might send you things at random times, but that does not mean that you have to respond around the clock. If something really is urgent – I will let you know.

PhD Students can expect scheduled meetings with me:

In a group meeting

At least once a week

In year 1 of PhD study

At least once a week

In year 2 of PhD study

At least once a week

In year 3 of PhD study

At least once a week

These meetings will be mainly face to face, and I am have an open door policy but my pattern of being contactable for an instant response is not predictable.

Working Pattern

The timing of work in my lab is 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 5000 words.

MIBTP Project Details

Current Projects (2025-26)

Primary supervisor for:

Dynamic, cognitive, computational and neural underpinnings of flexible decision-making

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).

Dynamic, cognitive, computational and neural underpinnings of flexible decision-making

Secondary Supervisor(s): Dr Clayton Hickey

University of Registration: University of Birmingham

BBSRC Research Themes: Understanding the Rules of Life (Neuroscience and Behaviour)

Project Outline

Humans are incredibly flexible in their decision-making. Faced with the same information, the same set of options, we can come to select entirely different actions depending on our current goals, what we know about our environment, how certain we are about different aspects of our knowledge or our environment, and situational constraints. While the cognitive and computational mechanisms of simple choice have been widely studied and formalized in successful computational models that in turn guided neuroscientific discoveries, these choices are limited in their scope and the mechanisms thus don’t scale up to the flexible behavior that humans are able to show in daily life. We have recently begun to incorporate insights from research into cognitive control, metacognition, and planning to better understand how this flexibility can be achieved (Frömer & Shenhav, 2022, Frömer et al., 2019, Frömer et al, 2022).

Objective

A core aim of this project is to extend this work to identify how active information sampling is guided by metacognitive and control mechanisms, how it shapes decision-making dynamics, and to dissect the dynamic neural mechanism that implement these processes (Frömer et al 2021, Frömer et al 2024). The project further aims to identify how core determinants of active information sampling are learned and how learning interacts with decision-making.

Method

The research will involve a range of methods including computational modelling, behavioural experiments, simultaneous EEG and eye-tracking, and potentially fMRI and brain stimulation (transcranial ultrasound stimulation). The research will take place within an international collaborative research network including researchers from University of California Berkeley, Brown University, University of Hamburg, NYU and University of Oxford. Research visits to one of these labs will be possible as part of the PhD.

References

Frömer, R., Nassar, M. R., Ehinger, B. V., & Shenhav, A. (2024). Common neural choice signals can emerge artefactually amid multiple distinct value signals. Nature Human Behaviour. doi:10.1038/s41562-024-01971-z.

Frömer, R., & Shenhav, A. (2022). Filling the gaps: Cognitive control as a critical lens for understanding mechanisms of value-based decision-making. Neuroscience & Biobehavioral Reviews, 134, 104483. doi:https://doi.org/10.1016/j.neubiorev.2021.12.006.

Frömer, R., Callaway, F., Griffiths, T., & Shenhav, A. (2022). Considering what we know and what we don't know: Expectations and Confidence guide value integration in value-based decision-making. PsyArXiv. doi:10.31234/osf.io/2sqyt.

Frömer, R., Nassar, M. R., Bruckner, R., Stürmer, B., Sommer, W., & Yeung, N. (2021). Response-based outcome predictions and confidence regulate feedback processing and learning. Elife, 10, e62825. doi:10.7554/eLife.62825.

Frömer, R., Dean Wolf, C. K., & Shenhav, A. (2019). Goal congruency dominates reward value in accounting for behavioral and neural correlates of value-based decision-making. Nature Communications, 10(1), 4926. doi:10.1038/s41467-019-12931-x.

Co-supervisor on a project with Dr Matthew Apps.

Previous Projects (2024-25)

Primary supervisor for:

Dynamic, cognitive, computational and neural underpinnings of flexible decision-making