Altered Performance Monitoring in Psychopathy: A Review of Studies on Action Selection, Error, and Feedback Processing

2016 ◽  
Vol 3 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Stefan Schulreich
2014 ◽  
Vol 94 (1) ◽  
pp. 35-79 ◽  
Author(s):  
Markus Ullsperger ◽  
Claudia Danielmeier ◽  
Gerhard Jocham

Successful goal-directed behavior requires not only correct action selection, planning, and execution but also the ability to flexibly adapt behavior when performance problems occur or the environment changes. A prerequisite for determining the necessity, type, and magnitude of adjustments is to continuously monitor the course and outcome of one's actions. Feedback-control loops correcting deviations from intended states constitute a basic functional principle of adaptation at all levels of the nervous system. Here, we review the neurophysiology of evaluating action course and outcome with respect to their valence, i.e., reward and punishment, and initiating short- and long-term adaptations, learning, and decisions. Based on studies in humans and other mammals, we outline the physiological principles of performance monitoring and subsequent cognitive, motivational, autonomic, and behavioral adaptation and link them to the underlying neuroanatomy, neurochemistry, psychological theories, and computational models. We provide an overview of invasive and noninvasive systemic measures, such as electrophysiological, neuroimaging, and lesion data. We describe how a wide network of brain areas encompassing frontal cortices, basal ganglia, thalamus, and monoaminergic brain stem nuclei detects and evaluates deviations of actual from predicted states indicating changed action costs or outcomes. This information is used to learn and update stimulus and action values, guide action selection, and recruit adaptive mechanisms that compensate errors and optimize goal achievement.


2011 ◽  
Vol 42 (8) ◽  
pp. 1637-1647 ◽  
Author(s):  
W. P. Horan ◽  
D. Foti ◽  
G. Hajcak ◽  
J. K. Wynn ◽  
M. F. Green

BackgroundAccurate monitoring and integration of both internal and external feedback is crucial for guiding current and future behavior. These aspects of performance monitoring are commonly indexed by two event-related potential (ERP) components: error-related negativity (ERN) and feedback negativity (FN). The ERN indexes internal response monitoring and is sensitive to the commission of erroneous versus correct responses, and the FN indexes external feedback monitoring of positive versus negative outcomes. Although individuals with schizophrenia consistently demonstrate a diminished ERN, the integrity of the FN has received minimal consideration.MethodThe current research sought to clarify the scope of feedback processing impairments in schizophrenia in two studies: study 1 examined the ERN elicited in a flanker task in 16 out-patients and 14 healthy controls; study 2 examined the FN on a simple monetary gambling task in expanded samples of 35 out-patients and 33 healthy controls.ResultsStudy 1 replicated prior reports of an impaired ERN in schizophrenia. By contrast, patients and controls demonstrated comparable FN differentiation between reward and non-reward feedback in study 2.ConclusionsThe differential pattern across tasks suggests that basic sensitivity to external feedback indicating reward versus non-reward is intact in schizophrenia, at least under the relatively simple task conditions used in this study. Further efforts to specify intact and impaired reward-processing subcomponents in schizophrenia may help to shed light on the diminished motivation and goal-seeking behavior that are commonly seen in this disorder.


2017 ◽  
Vol 128 (11) ◽  
pp. 2110-2121 ◽  
Author(s):  
Séverine Lannoy ◽  
Fabien D'Hondt ◽  
Valérie Dormal ◽  
Joël Billieux ◽  
Pierre Maurage

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Romy Frömer ◽  
Matthew R Nassar ◽  
Rasmus Bruckner ◽  
Birgit Stürmer ◽  
Werner Sommer ◽  
...  

Influential theories emphasize the importance of predictions in learning: we learn from feedback to the extent that it is surprising, and thus conveys new information. Here we explore the hypothesis that surprise depends not only on comparing current events to past experience, but also on online evaluation of performance via internal monitoring. Specifically, we propose that people leverage insights from response-based performance monitoring – outcome predictions and confidence – to control learning from feedback. In line with predictions from a Bayesian inference model, we find that people who are better at calibrating their confidence to the precision of their outcome predictions learn more quickly. Further in line with our proposal, EEG signatures of feedback processing are sensitive to the accuracy of, and confidence in, post-response outcome predictions. Taken together, our results suggest that online predictions and confidence serve to calibrate neural error signals to improve the efficiency of learning.


2018 ◽  
Author(s):  
R. Frömer ◽  
M.R. Nassar ◽  
R. Bruckner ◽  
B. Stürmer ◽  
W. Sommer ◽  
...  

AbstractInfluential theories emphasize the importance of predictions in learning: we learn from feedback to the extent that it is surprising, and thus conveys new information. Here we explore the hypothesis that surprise depends not only on comparing current events to past experience, but also on online evaluation of performance via internal monitoring. Specifically, we propose that people leverage insights from response-based performance monitoring – outcome predictions and confidence – to control learning from feedback. In line with predictions from a Bayesian inference model, we find that people who are better at calibrating their confidence to the precision of their outcome predictions learn more quickly. Further in line with our proposal, EEG signatures of feedback processing were sensitive to the accuracy of, and confidence in, post-response outcome predictions. Taken together, our results suggest that online predictions and confidence serve to calibrate neural error signals to improve the efficiency of learning.


2018 ◽  
Vol 132 ◽  
pp. 365-378 ◽  
Author(s):  
Elizabeth A. Martin ◽  
Amanda McCleery ◽  
Melody M. Moore ◽  
Jonathan K. Wynn ◽  
Michael F. Green ◽  
...  

Author(s):  
Walter W. Wierwille ◽  
Mark G. Lewin ◽  
Rollin J. Fairbanks

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