Literature DB >> 12452582

A computational account of altered error processing in older age: dopamine and the error-related negativity.

Sander Nieuwenhuis1, K Richard Ridderinkhof, Durk Talsma, Michael G H Coles, Clay B Holroyd, Albert Kok, Maurits W van der Molen.   

Abstract

When participants commit errors or receive feedback signaling that they have made an error, a negative brain potential is elicited. According to Holroyd and Coles's (in press) neurocomputational model of error processing, this error-related negativity (ERN) is elicited when the brain first detects that the consequences of an action are worse than expected. To study age-related changes in error processing, we obtained performance and ERN measures of younger and high-functioning older adults. Experiment 1 demonstrated reduced ERN amplitudes in older adults in the context of otherwise intact brain potentials. This result could not be attributed to uncertainty about the required response in older adults. Experiment 2 revealed impaired performance and reduced response- and feedback-related ERNs of older adults in a probabilistic learning task. These age changes could be simulated by manipulation of a single parameter of the neurocomputational model, this manipulation corresponding to weakened phasic activity of the mesencephalic dopamine system.

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Year:  2002        PMID: 12452582     DOI: 10.3758/cabn.2.1.19

Source DB:  PubMed          Journal:  Cogn Affect Behav Neurosci        ISSN: 1530-7026            Impact factor:   3.282


  35 in total

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6.  Anterior cingulate cortex, error detection, and the online monitoring of performance.

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7.  Self-efficacy effects on neuroelectric and behavioral indices of action monitoring in older adults.

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Review 8.  Individual differences and developmental change in the ERN response: implications for models of ACC function.

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9.  When is an error not a prediction error? An electrophysiological investigation.

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Journal:  Cogn Affect Behav Neurosci       Date:  2009-03       Impact factor: 3.282

10.  Frontal theta links prediction errors to behavioral adaptation in reinforcement learning.

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