Periodic Reporting for period 1 - CODEC (COgnitive Dynamics in Early Childhood)
Période du rapport: 2023-01-01 au 2025-06-30
Cognitive ability, measured through standardized tests, provides a highly predictive measure of lifespan outcomes including academic achievement, job success, as well as mental and physical health. However, these cognitive ‘snapshots’ omit a crucial aspect of cognitive ability: Short term variability in cognitive performance. Individuals with more variable performance are more likely to be mis-stratified into schools or careers with potential lifelong consequences, and more likely to perform at levels that necessitate intervention for periods of time. Moreover, variability reflects a promising early warning marker of adverse outcomes, above and beyond mean performance. However, the challenges involved in measuring variability have left crucial questions unanswered: Is variability a single trait, or does it have distinct factors? What are the neural and behavioural determinants of cognitive variability? What is the association between short term variability and long-term outcomes? In this unique longitudinal design using gamified versions of classic cognitive domains I will measure variability across a range of tasks at multiple levels of temporal resolution: months, days, occasions and trials. 600 children (200 in the neuroimaging arm) will be measured for period of three years. Once per year they will take part in a burst: A week where they will be measured three times a day. I will use using cutting edge methodology to understand the behavioural, neural and environmental mechanisms of variability, as well as the longitudinal consequences of variability on cognitive development and the emergence of mental health symptomatology such as ADHD. By combining the strengths of deep phenotyping with cutting edge quantitative modeling, I will be able to test and develop theories of cognitive development, demonstrate the role of brain structure and function in supporting cognitive dynamics and determine the effect of cognitive variability on developmental outcomes.
Our major achievement is the successful development and initiation of the largest study yet focused on cognitive variability. This process has encompassed a range of activities and achievements, including recruitment and training of team members and the application for ethical approval. In parallel, we worked on the development of a battery of five cognitive tasks, to be implemented on a secure platform (m-Path, Mestdagh et al., 2023). The full set up of the study was then described in our, now published, protocol paper (Coolen et al., 2024). This protocol paper not only describes the rationale and study design in detail, but translates the core hypotheses from our study proposal (Annex 1 GA) into a series of directional hypotheses, effectively functioning as a public preregistration document for our analyses to come, maximizing rigour, transparency and accountability.
Starting right after ethical approval was received, recruitment of schools and classes was initiated. As of February 2025, a total of 96 children have already taken part, a further 130 are currently scheduled to be tested in March and April of 2025, and we are liaising with other schools to initiate testing weeks in May and June. The initial testing sessions were very successful - We have seen very high completion rates (with a considerable number of children participating in every single session in a school week, yielding 15 distinct testing occasions). Above all, both the children and teachers report that they enjoy taking part in the study, enjoy the tasks we have developed and tailored for them, and understand the instructions provided.
Furthermore, work has started on a fully reproducible pipeline that takes the (very) large raw dataset and translates it into a tractable format for visualisation and analysis. Inspection of data collected so far suggests high data quality. Figure 1 shows a visual representation of our recruitment and data collection so far. Panel A shows the testing occasions so far - Testing weeks are clustered within classrooms within schools. The testing occasion within each day is shown in Panel B, with most testing occasions happening in the morning, but many classes and individuals also participating later in the day. Panel C shows the successful collection of a covariate of interest, namely background noise measured in decibels. Panel D shows response time data for each of the 5 tasks for a random sample of participants. Finally, panel E shows how two covariates of central interest, self-reported sleep quality and mood, covary over time within a random selection of individuals.
To facilitate the imaging arm we have developed, piloted and implemented a neuroimaging pipeline specialised for children. This has included tailoring MRI sequences to a childhood population, having an artist create a wooden ‘space rocket’ to make the imaging chamber feel more welcoming and less intimidating, and discussing with other child population studies how to maximize enjoyment during the session. We implemented concurrent MRI-eye tracking using the Eyelink 1000 plus system. Third, we developed a new matrix reasoning task for implementation in the scanner, integrated with our fMRI sequence and eye tracker. Finally, we have included in the mock scanner a so- called MoTrak protocol (MoTrak Head Motion Tracking System, Psychology Software Tools, Inc.). This gives children feedback on their head motion and teaches them in a non- invasive, gentle manner how to minimize head motion during MRI scanning (Gao et al., 2023). This technological progress sets the stage for the work proposed in Work Package 2.
Leadership
While working on the CODEC project, we have succeeded in establishing (inter)national recognition of our expertise in cognitive variability, with considerable interest in the CODEC project. Since the initiation of the project, the group has delivered approximately 20 (invited) lectures, symposium talks and posters (acknowledging ERC funding) in multiple countries to present what is the largest and most ambitious study of variability to date. The PI was invited to contribute to a publication in a flagship journal on the topic of cognitive variability (Mansouri et al., 2024), and to write the ‘Open Encyclopedia of Cognitive Science’ entry on cognitive variability. We are currently planning a conference on cognitive variability in the autumn of 2026.
Starting right after ethical approval was received, recruitment of schools and classes was initiated. As of February 2025, a total of 96 children have already taken part, a further 130 are currently scheduled to be tested in March and April of 2025, and we are liaising with other schools to initiate testing weeks in May and June. The initial testing sessions were very successful - We have seen very high completion rates (with a considerable number of children participating in every single session in a school week, yielding 15 distinct testing occasions). Above all, both the children and teachers report that they enjoy taking part in the study, enjoy the tasks we have developed and tailored for them, and understand the instructions provided.
Furthermore, work has started on a fully reproducible pipeline that takes the (very) large raw dataset and translates it into a tractable format for visualisation and analysis. Inspection of data collected so far suggests high data quality. Figure 1 shows a visual representation of our recruitment and data collection so far. Panel A shows the testing occasions so far - Testing weeks are clustered within classrooms within schools. The testing occasion within each day is shown in Panel B, with most testing occasions happening in the morning, but many classes and individuals also participating later in the day. Panel C shows the successful collection of a covariate of interest, namely background noise measured in decibels. Panel D shows response time data for each of the 5 tasks for a random sample of participants. Finally, panel E shows how two covariates of central interest, self-reported sleep quality and mood, covary over time within a random selection of individuals.
To facilitate the imaging arm we have developed, piloted and implemented a neuroimaging pipeline specialised for children. This has included tailoring MRI sequences to a childhood population, having an artist create a wooden ‘space rocket’ to make the imaging chamber feel more welcoming and less intimidating, and discussing with other child population studies how to maximize enjoyment during the session. We implemented concurrent MRI-eye tracking using the Eyelink 1000 plus system. Third, we developed a new matrix reasoning task for implementation in the scanner, integrated with our fMRI sequence and eye tracker. Finally, we have included in the mock scanner a so- called MoTrak protocol (MoTrak Head Motion Tracking System, Psychology Software Tools, Inc.). This gives children feedback on their head motion and teaches them in a non- invasive, gentle manner how to minimize head motion during MRI scanning (Gao et al., 2023). This technological progress sets the stage for the work proposed in Work Package 2.
Leadership
While working on the CODEC project, we have succeeded in establishing (inter)national recognition of our expertise in cognitive variability, with considerable interest in the CODEC project. Since the initiation of the project, the group has delivered approximately 20 (invited) lectures, symposium talks and posters (acknowledging ERC funding) in multiple countries to present what is the largest and most ambitious study of variability to date. The PI was invited to contribute to a publication in a flagship journal on the topic of cognitive variability (Mansouri et al., 2024), and to write the ‘Open Encyclopedia of Cognitive Science’ entry on cognitive variability. We are currently planning a conference on cognitive variability in the autumn of 2026.
In terms of methodology, we have developed a new framework to analyse intensive longitudinal data (Schaaf et al., 2025). Our DYNASTI (‘Dynamics of Asymmetric Timeseries’) approach allows for dynamic parameters to vary depending on whether a person is currently performing (or behaving) above, or below, their own mean. This allows us to tease apart, for instance, what happens when children are performing especially well, or poorly, compared to their own average. Or, it allows us to study whether less sleep than normal hurts performance (likely), but also whether sleeping more than normal benefits performance (not known at present). We have shown in both simulations and empirical data that we can isolate, for example, when children show periods of prolonged focus (where their reaction time is consistently below their own average), interspersed by occasional attentional lapses (slow responses). Moreover, we find that children show these patterns in differing degrees, demonstrating that our methodological innovation captures something psychologically meaningful.