Our brain is a network of functionally connected brain regions. Functional network integrity may disrupt in the cascade of events leading to dementia before anatomical or cognitive changes become apparent. Increasing sensitivity to identify network alterations therefore may enhance the early detection of dementia. To this end, we propose a technique for multi-subject fMRI data that clusters subjects based on within-cluster similarities and between-cluster differences in functional networks. As such, networks sensitive to early changes may be discovered in a data-driven way. We also study how anatomical MRI information can be incorporated into the technique.

The project will investigate the following research questions: 1. Can certain negative effects of age on cognitive ability be reduced with appropriate training? Brain training has seen a tremendous rise in the past decade. Yet, the general effects of the type of exercises that are typically offered on cognitive health are probably very small. In this project, the focus will therefore be on two areas of training in which previous research indicates that more general effects can be expected: cognitive control and memory strategies. 2. What is the role of individual differences in the neurocognitive mechanisms underlying the effects of training? and 3. How can we elucidate the neural and cognitive mechanisms using covariance-based functional magnetic resonance imaging, diffusion tensor imaging and model-based adaptive training of cognitive functions? Older adults differ as much from each other as they differ from young adults. These individual differences are typically reflected in error variance, working against interpretable research outcomes. Covariance-based fMRI, by contrast, capitalizes on individual differences, utilizing them to establish the extent to which brain structures covary in their activation with the efficiency of specific cognitive processes. Combined DTI and covariance-based fMRI techniques will allow us to address the hitherto overpowering problem of heterogeneity among older adults.

Suicide is notoriously difficult to predict and suicidal thoughts greatly fluctuate in daily life. Using real time assessments, we can capture the factors that lead to increased suicidal ideation or reduced risk. In our study we aim to assess day and night variability in suicidal ideation and its risk factors (mood, cognitions, stressful events, social interactions, coping), by using real time ecological momentary assessments and sleep/activity monitoring, in order to establish high and low risk conditions. This will greatly assist both patients and clinicians in developing personalized safety plans and treatments.

The central aim of this project is to create an inclusive school setting with and for adolescents with autism during their unstructured leisure time at school, thus increasing the quality and quantity of social participation with their peers. School leisure time is where ‘it happens’ for most adolescents: at the schoolyard, in the cafeteria, in the hallway. During their breaks in school, teenagers meet, have friendships, fall in love. This break time is most important to learn the skills that also prepare them for later life. Thus, adolescents need to make the necessary (social) strides to become emotionally and socially competent. Most adolescents with autism miss this important learning opportunity, because they have difficulties joining their peers during their leisure time at school. In this project, we will focus on creating and implementing an inclusive environment, by analysing and adapting the physical (built), social, and cultural environment at schools outside the classroom. New means of unobtrusive data collection (e.g., sensory data from Radio Frequency Identification Devices) will be utilised to measure social participation of secondary school students with autism in a pre- and post-test measures design, establishing the effectiveness of a newly developed intervention. High school students with autism and alumni will be involved in the development and implementation of this project from start to finish. This project involves a multidisciplinary collaboration (psychology, computer science, architecture) combining scientists (Leiden, Delft and Groningen University), professional organisations for autism (INTER-PSY & Rivierduinen), and patient associations (NVA).