Behavioural and Neural Variability in Childhood Cognitive Control and its Relationship to Learning

• In Event: Poster Session 03
  In Poster Session: PS 03 Topic - Attention, Learning, Memory

Abstract

Cognitive control supports goal-directed, flexible and adaptive responses to environmental changes. Childhood cognitive control is a reliable predictor for later life success and wellbeing, and as such it has also been linked to learning and academic performance (Blair & Razza, 2007; Moffitt et al., 2011). Previous studies investigating cognitive control and its underlying neural correlates have traditionally focused on mean measures, e.g. mean task performance and mean brain activity, but recent studies suggest that variability measures may be more sensitive to developmental differences than means (Tamnes, Fjell, Westlye, Ostby, & Walhovd, 2012). In particular, reduced behavioural variability and increased neural variability may reflect more flexibility in response to changing environmental demands (Garrett et al., 2013), and may be better predictors of learning outcomes. Here, we aim to investigate the relationship between variability in childhood cognitive control, variability in underlying brain activity, and academic performance. To test this, a sample of 153 6-11 year-old children completed a stop-signal task (measuring cognitive control) in the fMRI scanner. Information on academic performance was collected retrospectively via children’s schools. Our measures of interest are the following. First, cognitive control variability corresponds to the intra-individual variability in stop-signal response time (SSRT), and will be estimated using a Bayesian Parametric Approach implemented with the BEESTS software (Matzke et al., 2013). Second, neural variability corresponds to the intra-individual variability in task-driven BOLD signal in the inhibition network, and will be computed as the difference of residuals between a standard regression model and a condition-specific trial-by-trial regression model (Armbruster-Genç, Ueltzhöffer, & Fiebach, 2016). Finally, academic performance will be measured via standardised academic assessments available from the children’s schools. Note that at the time of the abstract submission, data collection was completed except for academic performance measures (to be collected retrospectively during October 2020), and data analysis was underway. We hypothesise that variability in cognitive control will decrease with age, whereas neural variability in the inhibition network will increase with age. Moreover, we expect that reduced variability in cognitive control and greater neural variability will be related to better academic performance. These findings will further our understanding of developmental differences in cognitive control during childhood and its relation to learning. Most importantly, they will help identify potential intervention targets to improve learning and later life outcomes.

Authors

• Roser Canigueral, University College London (UCL)
  Presenting Author

• Keertana Ganesan, University College London
  Non-Presenting Author

• Abigail Thompson, University College London
  Non-Presenting Author

• Claire Smid, University College London
  Non-Presenting Author

• Vanessa Puetz, University College London
  Non-Presenting Author

• Nikolaus Steinbeis, University College London (UCL)
  Non-Presenting Author