We are organizing a one-day symposium to foster exchange between researchers working in the fields of ecological momentary assessment (EMA) and computational psychiatry, with a special focus on mental health. This symposium is a collaboration between the Radboud Ecological Momentary Assessment Center (REMAC) and the Computational Neuropsychiatry Network (CNP), and is funded by a Catapult grant of the Radboud Young Academy.
In this symposium, Prof. Michael Browning, psychiatrist and PI at Oxford University, will link laboratory measures of uncertainty and motivational biases with real-world variability in mood and behavior in clinical populations. He will argue that computational psychiatry and EMA research often tackle remarkably similar questions. Next, Dr. Olivia Kirtley, Assistant Professor and Co-Director of the Center for Contextual Psychiatry at KU Leuven, will present her work using EMA to investigate dynamic daily-life processes involved in suicidal thoughts and behaviors.
Following each of the keynote speakers, we will shine the spotlight on exciting new work from two of our local researchers, highlighting ongoing EMA and computational psychiatry work from Nijmegen. We will end the day inviting you to participate in two workshops on the basics of computational modeling (Prof. Browning) and on good open science practice in EMA research (Dr. Kirtley).
Programme:
10:00-10:15 Welcome and Opening Remarks
10:15-11:15 Prof. Michael Browning, MD: EMA as uncertain communication
11:15-12:00 Local research: Iliana Liakea (BSI/REMAC) and Dr. Bertalan Polner (DCC/CNP/REMAC)
12:00-13:30 Lunch by Betty & Morra and networking opportunity
13:30-14:30 Dr. Olivia Kirtley: EMA in suicide research & prevention
14:30-15:15 Local research: Rares Radulescu (BSI/CNP) and Dr. Jessica Schaaf (DCMN/REMAC)
15:15-15:30 Closing remarks
15:30-16:00 Coffee break
16:00-17:00 Workshops 1 (fully reserved) and workshop 2
- Workshop 1: EMA and Open Science by Dr. Olivia Kirtley.
Open science practices are a suite of practices, methods, and principles that can be used and followed to increase transparency, reproducibility, and replicability in scientific research. Although still the exception rather than the rule, the use of open science practices in experience sampling method (ESM), ecological momentary assessment (EMA), and ambulatory assessment (AA) research is growing; summarized as ‘EMA’ below. Given the complexity of EMA research and the number of decisions that researchers must make during the study design, data collection, and data analysis phases of this type of research, this makes the “garden of forking paths” in EMA research especially dense. In this workshop, expert in EMA and open science, Dr. Olivia Kirtley will provide a hands-on guide to getting started with using open science in your EMA research and further developing your open science practices for those already familiar with some aspects of open science. The workshop will touch upon different open science practices, including transparent reporting, open materials, open code and dynamic reporting, data documentation and sharing, and pre- and post-registration and Registered Reports. The workshop will be tailored to the needs of attending researchers. No prior experience with open science is necessary, and the workshop is suited to researchers of all career stages (masters, PhD, postdoc, faculty). - Workshop 2: Basic Concepts in Model Fitting by Prof. Michael Browning.
Information will follow
Abstracts
- Talk: Prof. Michael Browning, MD: EMA as uncertain communication
In this talk, I will describe research using a Bayesian Observer Model to examine how people estimate and respond to different types of uncertainty during learning (https://elifesciences.org/articles/103734). I will then present research applying this same model to explain variability in ecological momentary assessment (EMA) data from clinical populations, revealing distinct variability patterns for Bipolar Disorder and Borderline Personality Disorder, along with insights into lithium's potential mechanism of action (https://www.pnas.org/doi/10.1073/pnas.2202983119). I will try and convince you that computational psychiatry and EMA research often tackle remarkably similar questions.
- Pitch 1: Iliana Liakea: Capturing Positivity: An EMA-Based App to Modify Memory Biases
This mobile intervention prompts participants to photograph neutral objects during positive experiences and guides them in vividly recalling these events each evening. Using Ecological Momentary Assessment, the app targets negative memory biases commonly linked to depression. We are currently testing its impact on memory biases, mood, and depressive symptoms in students with subclinical depressive symptoms. - Pitch 2: Dr. Bertalan Polner: Pavlovian biases predict daily life coupling of subjective valuation with action and thought
- Pitch 3: Rares Radulescu: Computational phenotyping of motivation: From foraging behaviour to real-life affect.
Through computational modeling of motivated behaviour and decision-making, we establish markers that are predictive of well-being in real-life measured with Ecological Momentary Assessment. We propose a cross-task computational modeling approach - applied to effort-based decision-making and foraging behaviour - that can be leveraged for phenotyping and personalized prediction. - Pitch 4: Dr. Jessica Schaaf: The signal in the noise: Ambulatory assessment of classroom noise and cognitive performance
Doing cognitive tasks in noisy environments is at best annoying and could lower performance. I will show how fluctuations in classroom noise relate to fluctuations in children’s cognitive performance across five cognitive domains and will discuss why some children may be more affected by noise than others.
Organiser
Computational Neuropsychiatry Network: Hanneke den Ouden, Eliana Vassena, Roshan Cools; REMAC: Janna Vrijsen, Rogier Kievit, Michele Schmitter, Anika Poppe