Individual Research Projects

The role of sleep in early cognitive development

Supervisors: Frank Wiesemann (Procter & Gamble). Additional mentors may include Clare Elwell (CBCD), Tim Smith (CBCD) and Emily Jones (CBCD).

Sleep plays a critical role in early cognitive development, but we know little about the mechanisms that mediate these effects, or how to promote effective sleep in early development. This project combines the expertise of Procter & Gamble in understanding early sleep and how it can be optimised through product design, and the expertise of the Centre for Brain and Cognitive Development in using multimodal behavioural, cognitive and neural methods to understand early brain development. The student will spend the first part of the PhD working at Procter & Gamble’s Innovation Centre in Germany. During this phase, the student will conduct a large longitudinal study of sleep in young infants in the first year of life. This will include low-intensity methods such as actigraphy and questionnaires to measure day and night time sleep, and measures of socio-emotional and cognitive development. Data from this phase will be used to determine which sleep profiles are associated with positive versus negative cognitive development, taking into account potentially confounding factors. This information will be used to guide generation of hypotheses and selection of target groups in the second phase. The second phase will take place at the Centre for Brain and Cognitive Development in the UK. In this phase, the student will generate and test hypotheses about the mechanisms underpinning the role of sleep in cognitive development. For example, the student might use neuroimaging methods (like NIRS and EEG) to examine functional connectivity and brain activity during sleep, and how that relates to learning in good and poor sleepers. The student might test whether better sleepers use executive functioning skills (e.g. frontal connectivity) to self-soothe after arousals; which features of brain activity during sleep predict better learning post-nap; and/or how effects of sleep in development are mediated through effects on parent-child interaction. The student may also test the effects of brief interventions on sleep quality. Taken together, this project will produce fundamental new knowledge of the role of sleep in early development.

 

How touch mediates infant happiness and learning

Supervisors: Frank Wiesemann (P&G), Denis Mareschal and Teea Gliga (CBCD). Additional supervisors may include: Matt Longo (CBCD), Atsushi Senju (CBCD) & Mark Johnson (CBCD).

Touch is one of the earliest senses through which infants learn about their physical and social environment; it continues to serve these functions throughout life. Its importance in early development is highlighted by studies showing positive long-term effects of skin-to-skin or massage touch during the neonatal period on cognitive and emotional development 10 years later. However, unlike learning through vision and hearing, whose mechanisms are heavily studied, the mechanisms through which touch affects learning remain largely unexplored. This research project combines P&G’s longstanding interest in understanding infant and child skin physiology and parent and child well-being with the CBCD’s expertise in using multimodal behavioural, cognitive and neural methods to understand early brain development. This project will test the hypothesis that learning occurs in optimal states of arousal and affect and that one way by which touch promotes learning is by modulating child’s arousal and affective states. The student will spend the first half of the PhD at P&G, carrying out observational and questionnaire studies to understand the what type of touch is most commonly used in parent child interaction and whether touch is use to regulate particular infant states. The ESR will build on this work to develop experimental studies investigating the effects of different types of tactile stimulation (e.g. stroking, massaging, touch with different materials) have on infants’ arousal, affective states and learning. These studies will be carried out at P&G and CBCD, in the second half of the PhD. Measures of arousal (e.g., heart rate, skin conductance, EEG, hormone levels), behavioural affective responses (e.g. smiling), brain function (e.g., NIRS, EEG) and learning will be taken while or after the child experiences tactile stimulation.

 

The neural dynamics of motivated learning

Supervisors: TeeaGliga (BBK) & Raul Muresan (RIST). Additional supervisors may include: Tim Smith (CBCD), Mark Johnson (CBCD), Atsushi Senju (CBCD) and Fred Dick (CBCD).

Educators have long known that children learn better when they are motivated and attentive. However, despite substantial effort and creativity driving the design of teaching tools, they rarely succeed with every child, and at every instance of learning. At the moment, we have at best a fragmentary understanding of how motivation and attention change as learning unfolds, how this depends on developmental stage, and what type of interventions best succeed at increasing motivation for learning. This project builds on findings that particular electrophysiological markers such as low frequency cortical-subcortical loops (measured by EEG) or pupil dilation reflect information seeking, and predict subsequent learning success. It also builds on the Romanian Institute of Science and Technology’s (RIST) expertise in advanced data analysis methods that can enable estimation of brain oscillations in various frequency bands and reveal neural information transfer between different brain regions. The project will use neuroimaging methods (EEG, eye tracking) and state-of-the-art data analysis to unveil the underlying moment-to-moment dynamics of information seeking, how they relate to learning and are modulated by external rewards. For this purpose, the ESR will use and develop cutting-edge analytical methods based on transfer entropy, scaled correlation, oscillation score, cross-frequency coupling, coherence and phase-locking. The ESR will take advantage of existing data sets collected in infants, children and adults with typical and atypical development (e.g. ADHD risk) at CBCD and RIST. These findings will advance our understanding of the neural mechanisms of motivated learning while also providing important pointers for increasing learning success. Furthermore, the project will act both as a testbed and improvement platform for the tools and analysis software at RIST, and will help develop valuable new methods to investigate the processes associated with learning in the brain. The ESR will spend time at RIST developing advanced data analysis methods and applying them to existing/new neurophysiological datasets as well at the CBCD, developing paradigms and carrying out imaging studies with developmental populations.

 

Tailoring the learning experience to individual students

Supervisors: Han van der Maas and Maartje Raijmakers (Oefenweb), Natasha Kirkham and Iroise Dumontheil (CBCD).

To succeed in school, children must not only be motivated to learn, but must also be able to learn quickly from instruction and feedback. Personalisation of all phases of the learning process requires detailed analyses of the individual learning as it takes place in an individual. Many learning systems nowadays adapt exercises and instruction to the general ability level of the student. There are two important extensions to this approach. One step is to adapt exercises and instruction to individual differences in students’ learning (e.g. ability to learn from negative feedback, confidence, motivation).

A second step is it to adapt feedback and instruction to the task-specific strategies used, and types or errors made by children. Online learning systems allow, in principle, advanced data-analysis of strategies and errors. Experimental (neuro-) psychological methods (e.g., with eye-tracking) will be used to validate and extend these data-analytic approaches.

The project will investigate new ways to personalise instruction and feedback for learning in children. Specifically, the project will investigate how individual differences (e.g., executive function skills, personality characteristics, learning attitudes) impact on the learning cycle, and will address questions on how better to tailor the learning environment based on task-specific error and strategy analysis. The project will develop novel approaches to personalised learning in children in collaboration with Amsterdam-based company Oefenweb, making use of their over 100,000 active participants within and outside schools. Students’ learning characteristics will be accessed using questionnaires. While at the CBCD, the student will develop and test paradigms that can measure learning in primary-school children, using a variety of experimental methods. Advanced statistical methods will also be applied to interpret these ‘big data’. In parallel studies, big data from the online learning environment will be paired with age-appropriate experimental measurements of learning and engagement (e.g. eye tracking, heart rate monitoring, and change in pupil dilation).

 

Representational change in intensive language intervention

Supervisors: Jurgen Tijms (IWAL), Anniek Vaessen & Patty Gerretsen (RID), Milene Bonte (IWAL/RID), Fred Dick and Adam Tierney (CBCD).

Many otherwise typically developing children have severe difficulties in learning to read. To help remedy these reading problems, specialised institutions for dyslexia health care in the Netherlands (RID and IWAL) have designed and implemented research-driven, intensive intervention programmes. These interventions lead to significant improvements in reading, but there is still considerable variability in outcomes. Understanding individual differences in the neurocognitive processes underlying this variability is crucial for tailoring dyslexia treatment to each individual. This project investigates how interindividual differences in the learning trajectory and intervention outcome relate to changes in each individual’s neural representations. This project combines the strengths of IWAL & RID’s large-scale behavioural interventions with developmental neuroimaging (EEG/fMRI) and analytic innovations from IWAL/RID and CBCD-affiliated researchers.