A processing schema for children in the auditory equiprobable Go/NoGo task: ERP components and behaviour.

Int J Psychophysiol

Brain & Behaviour Research Institute, and School of Psychology, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia.

Published: January 2018

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.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ijpsycho.2017.10.014DOI Listing

Publication Analysis

Top Keywords

processing schema
8
auditory equiprobable
8
equiprobable go/nogo
8
go/nogo task
8
sequential processing
8
processing model
8
erp data
8
processing
6
data
6
nogo
5

Similar Publications

Background: Medical narratives are fundamental to the correct identification of a patient's health condition. This is not only because it describes the patient's situation. It also contains relevant information about the patient's context and health state evolution.

View Article and Find Full Text PDF

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 PDF

Target informed client recruitment for efficient federated learning in healthcare.

BMC 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 PDF

Grey matter volume differences across Parkinson's disease motor subtypes in the supplementary motor cortex.

Neuroimage 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 PDF

Heterogeneous Graph Embedding with Dual Edge Differentiation.

Neural 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.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!