Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Decision confidence: EEG correlates of confidence in different phases of a decision task

View through CrossRef
Abstract Decision making is an essential part of daily life, in which balancing reasons and calculating risks to reach a certain confidence are important to make reasonable choices. To investigate the EEG correlates of confidence during decision making a study involving a forced choice recognition memory task was implemented. Subjects were asked to distinguish old from new pictures and rate their decision with either high or low confidence. Event-related potential (ERP) analysis was performed in four different phases covering all stages of decision making, including the information encoding, retrieval, decision formation, and feedback processing during the recognition task. Additionally, a single trial support-vector machine (SVM) classification was performed on the ERPs of each phase to get a measure of differentiability of the two levels of confidence on a single subject level. It could be shown that the level of decision confidence is significantly reflected in all stages of decision making but most prominently during feedback presentation. The main differences between high and low confidence can be found in the ERPs during feedback presentation after a correct answer, whereas almost no differences can be found in ERPs from feedback to wrong answers. In the feedback phase the two levels of confidence can be separated with a classification accuracy of up to 70 % on average over all subjects, therefore showing potential as a control state in a brain-computer Interface (BCI) application.
Title: Decision confidence: EEG correlates of confidence in different phases of a decision task
Description:
Abstract Decision making is an essential part of daily life, in which balancing reasons and calculating risks to reach a certain confidence are important to make reasonable choices.
To investigate the EEG correlates of confidence during decision making a study involving a forced choice recognition memory task was implemented.
Subjects were asked to distinguish old from new pictures and rate their decision with either high or low confidence.
Event-related potential (ERP) analysis was performed in four different phases covering all stages of decision making, including the information encoding, retrieval, decision formation, and feedback processing during the recognition task.
Additionally, a single trial support-vector machine (SVM) classification was performed on the ERPs of each phase to get a measure of differentiability of the two levels of confidence on a single subject level.
It could be shown that the level of decision confidence is significantly reflected in all stages of decision making but most prominently during feedback presentation.
The main differences between high and low confidence can be found in the ERPs during feedback presentation after a correct answer, whereas almost no differences can be found in ERPs from feedback to wrong answers.
In the feedback phase the two levels of confidence can be separated with a classification accuracy of up to 70 % on average over all subjects, therefore showing potential as a control state in a brain-computer Interface (BCI) application.

Related Results

THE EFFECT OF PETHIDINE ON THE NEONATAL EEG
THE EFFECT OF PETHIDINE ON THE NEONATAL EEG
SUMMARYThirty‐two preterm infants were monitored with an on‐line cotside EEG system for periods of up to nine days. Changes in the normal pattern of discontinuity of the EEG were s...
Computation of the electroencephalogram (EEG) from network models of point neurons
Computation of the electroencephalogram (EEG) from network models of point neurons
Abstract The electroencephalogram (EEG) is one of the main tools for non-invasively studying brain function and dysfunction. To better interpret EEGs in terms of ne...
Hybrid AI-Based Approach Utilizing EEG-Facial Expression fusion for Human-Machine Interaction
Hybrid AI-Based Approach Utilizing EEG-Facial Expression fusion for Human-Machine Interaction
Approche Hybride Basée sur l'IA, par fusion EEG-Expression Faciale pour l'Interaction Humain-Machine La reconnaissance des émotions par électroencéphalogramme (EEG)...
Evaluation of Mathematical Cognitive Functions with the Use of EEG Brain Imaging
Evaluation of Mathematical Cognitive Functions with the Use of EEG Brain Imaging
During the last decades, the interest displayed in neurocognitive and brain science research is relatively high. In this chapter, the cognitive neuroscience field approach focuses ...
Motion robustness validation of a Phase-Locked Loop for EEG phase tracking in Brain-Computer Interfaces
Motion robustness validation of a Phase-Locked Loop for EEG phase tracking in Brain-Computer Interfaces
Background. Closed loop brain-computer interfaces dynamically adjust stimulation settings and/or timings based upon concurrently measured data. EEG (electroencephalography) is a wi...
Human Factors Evaluation in Maritime Virtual Simulators Using Mobile EEG-Based Neuroimaging
Human Factors Evaluation in Maritime Virtual Simulators Using Mobile EEG-Based Neuroimaging
Neuro-ergonomics using mobile electroencephalogram (EEG)-based neuroimaging is a new area of Brain-Computer Interaction (BCI) applications. We propose and develop an EEG-based syst...
Comparing resting state and task-based EEG using machine learning to predict vulnerability to depression
Comparing resting state and task-based EEG using machine learning to predict vulnerability to depression
Major depressive disorder affects a large portion of the population and levies a huge societal burden. It has serious consequences like decreased productivity and reduced quality o...
Physiopathologie des comas isoélectriques : de l’EEG au neurone
Physiopathologie des comas isoélectriques : de l’EEG au neurone
Le cerveau génère de façon continue et endogène des activités électriques qui peuvent être enregistrées en surface grâce à un électroencéphalogramme (EEG). La fréquence et l’amplit...

Back to Top