Overview of network properties and analysis.

<p>(a) Histogram of correlation coefficients (i.e. edge weights) for each group. (b) Schematic diagram of a simple network with a semi-metric connection between nodes 1 and 2 (dashed edge) due to a shorter indirect path comprising edges between nodes 2 and 3 and 3 and 1 (solid edges). (c) The distribution of number of edges for semi-metric paths for each group. (d) Proximity matrices averaged across participants, for each group. (e) Axial projections of metric and semi-metric backbones for the control group. The thickness of the edges represents the percentage of participants within each group with a semi-metric edge at that location, with percentages > 90% omitted.</p

Semi-metric percentages and backbones.

<p>(a) Sagittal, axial and coronal projections of nodes coloured according to the modules in which they are contained. (b) Between-group comparisons (patient groups relative to controls) for whole brain, left and right hemisphere SMP displayed as box-and-whisker plots identifying the median by the central line, the 25^th and 75^th percentile ranges by the limits of the box, and the minimum and maximum range (excluding outliers) by the limits of the whiskers. Outliers are individually displayed and defined as values >1.5 the interquartile range from the 25% and 75% quartiles. (c) Sagittal projections of the left and right hemispheres of the semi-metric backbones for each group. The thickness of the edges represents the percentage of participants within each group with a semi-metric edge at that location, with percentages > 90% omitted.</p

Demographic characteristics of the participants.

<p>SD = standard deviation</p><p>Demographic characteristics of the participants.</p

Node degree and node disruption indices.

<p>Sagittal, axial and coronal projections (left-to-right) of nodes for comparisons of node degree in the semi-metric network for each between-group comparisons: (a) ASC vs. controls; (b) MDD vs controls. The radius of the node is proportional to the average degree difference and the colour denotes the direction of the effect; red indicating increases and green decreases, relative to controls. Plots of the difference in mean degree between (c) ASC and (d) MDD, and controls against mean degree for controls, for the semi-metric network. Node disruption indices are defined as the slope of the regression lines, plotted on each graph.</p

Illustration of a subset of cognitive tasks used in the CLIC adult characterization study.

For key constructs of interest, such as cognitive flexibility and creativity, we administer multiple tasks to improve measurement validity. See Appendix D in S1 File for the full task list and details.</p

Appendices A to G for “Study protocol: How does cognitive flexibility relate to other executive functions and learning in healthy young adults?”.

Appendices A to G for “Study protocol: How does cognitive flexibility relate to other executive functions and learning in healthy young adults?”.</p

Overall workflow of the CLIC Phase 1 adult study.

Detailed documentations of all tasks and questionnaires can be found in Appendices A to F in S1 File.</p

Main socio-cognitive questionnaires and decision-making tasks administered in the CLIC Phase 1 study (Part I), summarized by construct.

Main socio-cognitive questionnaires and decision-making tasks administered in the CLIC Phase 1 study (Part I), summarized by construct.</p

Study administration Part I and Part II summary.

BackgroundCognitive flexibility (CF) enables individuals to readily shift from one concept or mode of practice/thoughts to another in response to changes in the environment and feedback, making CF vital to optimise success in obtaining goals. However, how CF relates to other executive functions (e.g., working memory, response inhibition), mental abilities (e.g., creativity, literacy, numeracy, intelligence, structure learning), and social factors (e.g., multilingualism, tolerance of uncertainty, perceived social support, social decision-making) is less well understood. The current study aims to (1) establish the construct validity of CF in relation to other executive function skills and intelligence, and (2) elucidate specific relationships between CF, structure learning, creativity, career decision making and planning, and other life skills.MethodsThis study will recruit up to 400 healthy Singaporean young adults (age 18–30) to complete a wide range of cognitive tasks and social questionnaires/tasks. The richness of the task/questionnaire battery and within-participant administration enables us to use computational modelling and structural equation modelling to examine connections between the latent constructs of interest.Significance and ImpactThe current study is the first systematic investigation into the construct validity of CF and its interrelationship with other important cognitive skills such as learning and creativity, within an Asian context. The study will further explore the concept of CF as a non-unitary construct, a novel theoretical proposition in the field. The inclusion of a structure learning paradigm is intended to inform future development of a novel intervention paradigm to enhance CF. Finally, the results of the study will be useful for informing classroom pedagogy and the design of lifelong learning policies and curricula, as part of the wider remit of the Cambridge-NTU Centre for Lifelong Learning and Individualised Cognition (CLIC).</div

Cognitive tasks administered in the CLIC adult study (Part II), summarised by construct.

Appendix D in S1 File documents the full task details.</p