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Wijeakumar, S.

Publications and source records attributed to Wijeakumar, S..

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Disentangling Age and Schooling Effects on Inhibitory Control Development: An fNIRS Investigation

Children show marked improvements in executive functioning (EF) between 4 and 7 years of age. In many societies, this time period coincides with the start of formal school education, in which children are required to follow rules in a structured environment, drawing heavily on EF processes such as inhibitory control. This study aimed to investigate the longitudinal development of two aspects of inhibitory control, namely response inhibition and response monitoring and their neural correlates. Specifically, we examined how their longitudinal development may differ by schooling experience, and their potential significance in predicting academic outcomes. Longitudinal data was collected in two groups of children at their homes. At T1, all children were roughly 4.5 years of age and neither group had attended formal schooling. One year later at T2, one group (P1, n = 40) had completed one full year of schooling while the other group (KG, n = 40) had stayed in kindergarten. Behavioural and brain activation data (measured with functional near-infrared spectroscopy, fNIRS) in response to a Go/No-Go task and measures of academic achievement were collected. We found that P1 children, compared to KG children, showed a greater change over time in activation related to response monitoring in the bilateral frontal cortex. The change in left frontal activation difference showed a small positive association with mathematical ability, suggesting certain functional relevance of response monitoring for academic performance. Overall, the school environment is important in shaping the development of the neural network underlying monitoring of one owns performance. Research HighlightsO_LIUsing a school cut-off design, we collected longitudinal home assessments of two aspects of inhibitory control, namely response inhibition and response monitoring, and their neural correlates. C_LIO_LIFor response monitoring, P1 children showed a greater difference over time in activation between correct and incorrect responses in the bilateral frontal cortex. C_LIO_LIThe left frontal activation difference in P1 children showed a small association with mathematical ability, suggesting some functional relevance of response monitoring for academic performance. C_LIO_LIThe school environment plays an important role in shaping the development of the neural network underlying monitoring of one owns performance. C_LI

neuroscience

A processing pipeline for image reconstructed fNIRS analysis using both MRI templates and individual anatomy

AimWe demonstrate a pipeline with accompanying code to allow users to clean and prepare optode location information, prepare and standardize individual anatomical images, create the light model, run the 3D image reconstruction, and analyze data in group space. ApproachWe synthesize a combination of new and existing software packages to create a complete pipeline, from raw data to analysis. ResultsThis pipeline has been tested using both templates and individual anatomy, and on data from different fNIRS data collection systems. We show high temporal correlations between channel-based and image-based fNIRS data. In addition, we demonstrate the reliability of this pipeline with a sample dataset that included 74 children as part of a longitudinal study taking place in Scotland. We demonstrate good correspondence between data in channel space and image reconstructed data. ConclusionsThe pipeline presented here makes a unique contribution by integrating multiple tools to assemble a complete pipeline for image reconstruction in fNIRS. We highlight further issues that may be of interest to future software developers in the field. SignificanceImage reconstruction of fNIRS data is a useful technique for transforming channel-based fNIRS into a volumetric representation and managing spatial variance based on optode location. We present a novel integrated pipeline for image reconstruction of fNIRS data using either MRI templates or individual anatomy.

neuroscience