Error detection failures in schizophrenia: ERPs and FMRI.

Int J Psychophysiol

Psychiatry Service, San Francisco VA Medical Center, and Department of Psychiatry, University of California-San Francisco, 4150 Clement Street, San Francisco, CA 94121, USA.

Published: August 2009

Self-monitoring of actions, critical for guiding goal-directed behavior, is deficient in schizophrenia. Defective error-monitoring may reflect more general self-monitoring deficiencies. Prior studies have shown that the error-related negativity (ERN) component of the event-related potential (ERP) is smaller in patients with schizophrenia. Other studies using functional magnetic resonance imaging (FMRI) have shown the anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLPFC), both critical for error detection, to be less responsive to errors in patients with schizophrenia. In the present study, both ERP and FMRI data were collected while 11 patients with schizophrenia and 10 healthy controls performed a Go-NoGo task requiring a button press to Xs (p=.88) while withholding responses to Ks (p=.12). We measured the ERN and ACC and DLPFC activations to false alarms. The task elicited a robust ERN and modest activations in ACC and DLPFC to false alarms. As expected, ERN was larger in controls than patients. However, ACC and DLPFC activations were not greater in controls than patients. Surprisingly, DLPFC was more activated by errors in patients than controls. ERPs may be superior to fMRI for assessing error processing abnormalities in schizophrenia because (1) ERNs can be measured precisely without needing to control for the multiple comparisons of FMRI, and (2) ERPs have the temporal precision to detect transient activity necessary for error detection and on-the-fly behavioral adjustments.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4005823PMC
http://dx.doi.org/10.1016/j.ijpsycho.2009.02.005DOI Listing

Publication Analysis

Top Keywords

error detection
12
patients schizophrenia
12
acc dlpfc
12
errors patients
8
dlpfc activations
8
false alarms
8
controls patients
8
schizophrenia
6
patients
6
fmri
5

Similar Publications

Highly sensitive split ring resonator-based sensor for quality monitoring of edible oils.

Sci Rep

January 2025

Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (UKM), 43600, Bangi, Selangor, Malaysia.

This research presents the design and analysis of a compact metamaterial (MTM)-based star-shaped split-ring resonator (SRR) enclosed in a square, constructed on a cost-effective substrate for liquid chemical sensing applications. The designed structure has dimensions of 10 × 10 mm and is optimized for detecting adulteration in edible oils. When the sample holder is filled with different percentages of oil samples, the resonance frequency of the MTM-based SRR sensor shift significantly.

View Article and Find Full Text PDF

Energy feature extraction and visualization of voltage sags using wavelet packet analysis for enhanced power quality monitoring.

Sci Rep

January 2025

Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.

Power quality (PQ) disturbances, such as voltage sags, are significant issues that can lead to damage in electrical equipment and system downtime. Detecting and classifying these disturbances accurately is essential for maintaining reliable power systems. This paper introduces a novel approach to voltage sag analysis by employing wavelet packet analysis combined with energy-based feature extraction to enhance PQ monitoring.

View Article and Find Full Text PDF

Automatic detection and prediction of COVID-19 in cough audio signals using coronavirus herd immunity optimizer algorithm.

Sci Rep

January 2025

Department of Electronics and Communication Engineering, Sri Ramakrishna Institute of Technology, Coimbatore, Tamilnadu, India, 641010.

The global spread of COVID-19, particularly through cough symptoms, necessitates efficient diagnostic tools. COVID-19 patients exhibit unique cough sound patterns distinguishable from other respiratory conditions. This study proposes an advanced framework to detect and predict COVID-19 using deep learning from cough audio signals.

View Article and Find Full Text PDF

An online segmented continuous flow analysis system for rapid determining chemical oxygen demand in seawater to assess organic pollution levels.

Mar Pollut Bull

January 2025

Coastal Zone Ecological Environment Monitoring Technology and Equipment Shandong Engineering Research Center, CAS Key Laboratory of Coastal Zone Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, Shandong 264003, China; University of Chinese Academy of Sciences, Beijing 100049, China; Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, Shandong 266071, China; Shandong Key Laboratory of Coastal Environmental Processes, Yantai, Shandong 264003, China. Electronic address:

By integrating ultraviolet (UV) photocatalytic oxidation digestion with segmented continuous flow analysis technology, an online measurement method and analysis system for the alkaline chemical oxygen demand (COD) in seawater, based on the color-change reaction of potassium permanganate, has been established. This represents the first application of UV photocatalytic oxidation technology in the measurement of COD in seawater. The system effectively overcomes the limitations of high-temperature and high-pressure digestion methods employed in traditional COD analysis.

View Article and Find Full Text PDF

In order to address many issues, such as the inconsistent and unreliable seeding process in traditional mechanical garlic seed metering systems (SMS), as well as the lack of ability to monitor the effectiveness of the seeding, a highly accurate electric-driven metering system (EDMS) was developed and created specifically for garlic seed planters. This study provided a description of the overall structure and functioning principle, as well as an analysis of the mechanism for smooth transit and delivery. A combination of an infrared (IR) sensor, Arduino Mega board, stepper motor, speed sensor, and a Wi-Fi module was employed to operate the EDMS, as well as monitor and count the quantity of garlic seeds during the planting process and determine the qualified rate (QR) and missing rate (MR).

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!