A sequential processing model for adults in the auditory equiprobable Go/NoGo task has been developed in recent years. This used temporal principal components analysis (PCA) to decompose Go/NoGo event related potential (ERP) data into components that mark stages of perceptual and cognitive processing. The model has been found useful in frameworking several studies in young and older adults, and in children. Recently, it has been demonstrated that the common PCA approach of decomposing Go and NoGo ERP data together results in misallocation of variance between the conditions, distorting the timing, topography, and amplitudes of the resultant components in each condition. The present study thus reanalyses data from a child study, conducting separate PCAs on the data from each condition. Multiple regression was then used to seek links with behavioural measures from the task. In addition to confirming the previous NoGo N2b/inhibitory processing link, novel NoGo Negative Slow Wave/error evaluation and Go N1-1/RT variability links were obtained. Based on these outcomes, the recommended separate application of PCAs to Go and NoGo data was confirmed. The present data were used to develop a child-specific sequential processing schema for this paradigm, suggesting earlier separation of the Go and NoGo processing chains, and the need to include an additional inhibition and evaluation stage. The child schema should be useful in future studies involving this and other two-choice reaction tasks.
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BMC Med Inform Decis Mak
December 2024
Klinikum Stuttgart, Stuttgart Cancer Center - Tumorzentrum Eva Mayr-Stihl DE, Kriegsbergstraße 60, Stuttgart, D-70174, Germany.
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View Article and Find Full Text PDFHealth Care Transit
July 2024
Baylor College of Medicine and Texas Children's Hospital, Division of Adolescent Medicine and Sports Medicine, 6701 Fannin Street, Suite 1710, Houston, TX 77030, USA.
Aims: Health care transition (HCT) to adult care and young adult disease self-management is a multi-step process involving three major stakeholders - the adolescent, the caregiver, and the provider. Preparation gaps exist within each of these stakeholder groups. This paper presents the development of the Intervention to Promote Autonomy and Competence in Transition-aged Youth (IPACT), a multi-level (adolescent, caregiver, provider), multi-modal (interactive skill building sessions, educational materials, videos) intervention to address gaps in all three stakeholder groups simultaneously and help support achieving the three core elements of HCT planning.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
December 2024
Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Kasteelpark Arenberg 10, Leuven, 3001, Belgium.
Background: Modern machine learning and deep learning methods have been widely incorporated in decision making processes in healthcare in the form of decision support mechanisms. In healthcare, data are abundant but typically not centrally available and, therefore, require some form of aggregation to facilitate training procedures. Aggregating sensitive data poses a significant privacy risk, which is why, both in Europe and the United States, legal frameworks regulate the treatment of such data.
View Article and Find Full Text PDFNeuroimage Clin
December 2024
Division of Neurology, Department of Medicine, Prisma Health-Upstate, Greenville, SC, USA; School of Health Research, Clemson University, Clemson, SC, USA; Department of Health Sciences, University of South Carolina School of Medicine Greenville, Greenville, SC, USA. Electronic address:
Parkinson's Disease (PD) is the second most prevalent neurodegenerative disease worldwide due to loss of dopaminergic neurons projecting from the basal ganglia (BG). It is associated with various motor symptoms that are grouped into subtypes, each with different clinical presentations and disease progressions. Neuroimaging biomarkers focusing on regions a part of motor circuits projecting from the BG can distinguish and improve overall subtyping.
View Article and Find Full Text PDFNeural Netw
December 2024
College of Computer and Data Science, Fuzhou University, Fuzhou 350116, China; Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou University, Fuzhou 350116, China. Electronic address:
Recently, heterogeneous graphs have attracted widespread attention as a powerful and practical superclass of traditional homogeneous graphs, which reflect the multi-type node entities and edge relations in the real world. Most existing methods adopt meta-path construction as the mainstream to learn long-range heterogeneous semantic messages between nodes. However, such schema constructs the node-wise correlation by connecting nodes via pre-computed fixed paths, which neglects the diversities of meta-paths on the path type and path range.
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