For years the Wisconsin card sorting test (WCST) has been used as a test of frontal lobe function. Recent event-related potential (ERP) research has shown large differences in the amplitude of P3b responses evoked by early and late trials within each WCST series ([8]: Barceló F., Sanz M., Molina V., Rubia FJ. The Wisconsin Card Sorting Test and the assessment of frontal function: A validation study with event-related potentials. Neuropsychologia 1997;35:399-408). In this study, 16 normal subjects performed a WCST adaptation to investigate the role of attentional set shifting in these WCST P3b effects. Two control tasks were designed to examine whether early-late WCST P3b changes reflect category selection (attention) or category storage (memory) operations. Results suggest both a sharp P3b attenuation during shift WCST trials, followed by a gradual P3b build-up during post-shift trials. This P3b modulation could not be attributed to selection or storage of simple sensory stimulus dimensions, nor was it observed when the new rule was externally prompted by the first card in the WCST series. Instead, WCST P3b changes seem related to the endogenously generated shift in the perceptual rule used to sort the cards (i.e., the shift in set). The gradual build-up in P3b amplitude paralleled a progressive improvement in sorting efficiency over several post-shift WCST trials. A model based on formal theories of visual attention and attentional set shifting is proposed to account for these effects. The model offers firm grounds for prediction and bridges the gap between related clinical and experimental evidence.

Download full-text PDF

Source
http://dx.doi.org/10.1016/s0028-3932(00)00046-4DOI Listing

Publication Analysis

Top Keywords

attentional set
12
set shifting
12
wisconsin card
12
card sorting
12
sorting test
12
wcst p3b
12
p3b
9
wcst
9
wcst series
8
p3b changes
8

Similar Publications

Globally, the effects of climate change are becoming more pronounced. Simultaneously, concerns associated with climate change effects have garnered widespread attention. The motive of this study is to know about the prominent antecedents of climate abnormalities in Pakistan, which may lead to economic abnormality and instability.

View Article and Find Full Text PDF

Motivation: Much evidence suggests that the subcellular localization of long-stranded noncoding RNAs (LncRNAs) provides key insights for the study of their biological function.

Results: This study proposes a novel deep learning framework, LncLSTA, designed for predicting the subcellular localization of LncRNAs. It firstly exploits LncRNA sequence, electron-ion interaction pseudopotentials, and nucleotide chemical property as feature inputs.

View Article and Find Full Text PDF

Dietary Factors Associated with Depressive Symptoms in Midlife Women 40-50 Years of Age Living in the United States.

Womens Health Rep (New Rochelle)

December 2024

Department of Family Health Care Nursing, School of Nursing, University of California, San Francisco, California, USA.

Purpose: Women in the decade before menopause are at risk for depression. This study describes dietary factors associated with depression risk in late premenopausal women that could be modifiable with targeted interventions.

Methods: Descriptive cross-sectional study comparing a community-based sample of 342 healthy premenopausal women categorized as low-risk and high-risk for depression in a secondary analysis of dietary variables.

View Article and Find Full Text PDF

Early detection of subjective cognitive decline from self-reported symptoms: An interpretable attention-cost fusion approach.

J Biomed Inform

January 2025

Department of Information Management and Business Analytics, Montclair State University, Feliciano School of Business, NJ, USA. Electronic address:

Background And Objective: Subjective cognitive decline (SCD) refers to self-reported difficulties in concentration, memory, and decision-making. Since SCD is based on subjective experiences, no specific medical test can definitively confirm its presence, making early detection challenging. Thus, it is advantageous to develop an AI model to capitalize on self-reported health complications, personality traits, and sociodemographic factors for early detection of SCD.

View Article and Find Full Text PDF

This study presents a novel approach to identifying meters and their pointers in modern industrial scenarios using deep learning. We developed a neural network model that can detect gauges and one or more of their pointers on low-quality images. We use an encoder network, jump connections, and a modified Convolutional Block Attention Module (CBAM) to detect gauge panels and pointer keypoints in images.

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!