Literature DB >> 23973408

The feedback-related negativity (FRN) revisited: new insights into the localization, meaning and network organization.

Tobias U Hauser1, Reto Iannaccone, Philipp Stämpfli, Renate Drechsler, Daniel Brandeis, Susanne Walitza, Silvia Brem.   

Abstract

Changes in response contingencies require adjusting ones assumptions about outcomes of behaviors. Such adaptation processes are driven by reward prediction error (RPE) signals which reflect the inadequacy of expectations. Signals resembling RPEs are known to be encoded by mesencephalic dopamine neurons projecting to the striatum and frontal regions. Although regions that process RPEs, such as the dorsal anterior cingulate cortex (dACC), have been identified, only indirect evidence links timing and network organization of RPE processing in humans. In electroencephalography (EEG), which is well known for its high temporal resolution, the feedback-related negativity (FRN) has been suggested to reflect RPE processing. Recent studies, however, suggested that the FRN might reflect surprise, which would correspond to the absolute, rather than the signed RPE signals. Furthermore, the localization of the FRN remains a matter of debate. In this simultaneous EEG-functional magnetic resonance imaging (fMRI) study, we localized the FRN directly using the superior spatial resolution of fMRI without relying on any spatial constraint or other assumption. Using two different single-trial approaches, we consistently found a cluster within the dACC. One analysis revealed additional activations of the salience network. Furthermore, we evaluated the effect of signed RPEs and surprise signals on the FRN amplitude. We considered that both signals are usually correlated and found that only surprise signals modulate the FRN amplitude. Last, we explored the pathway of RPE signals using dynamic causal modeling (DCM). We found that the surprise signals are directly projected to the source region of the FRN. This finding contradicts earlier theories about the network organization of the FRN, but is in line with a recent theory stating that dopamine neurons also encode surprise-like saliency signals. Our findings crucially advance the understanding of the FRN. We found compelling evidence that the FRN originates from the dACC. Furthermore, we clarified the functional role of the FRN, and determined the role of the dACC within the RPE network. These findings should enable us to study the processing of surprise and adjustment signals in the dACC in healthy and also in psychiatric patients.
© 2013.

Entities:  

Keywords:  Dorsal anterior cingulate cortex (dACC); Dynamic causal modeling (DCM); Feedback-related negativity (FRN); Probabilistic reversal learning; Reward prediction error (RPE); Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI); Surprise

Mesh:

Year:  2013        PMID: 23973408     DOI: 10.1016/j.neuroimage.2013.08.028

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  100 in total

1.  Impulsive personality dimensions are associated with altered behavioral performance and neural responses in the monetary incentive delay task.

Authors:  Ruolei Gu; Yang Jiang; Seth Kiser; Chelsea L Black; Lucas S Broster; Yue-Jia Luo; Thomas H Kelly
Journal:  Neuropsychologia       Date:  2017-07-15       Impact factor: 3.139

2.  Genetic influences on functional connectivity associated with feedback processing and prediction error: Phase coupling of theta-band oscillations in twins.

Authors:  Şükrü Barış Demiral; Simon Golosheykin; Andrey P Anokhin
Journal:  Int J Psychophysiol       Date:  2016-12-31       Impact factor: 2.997

3.  Impaired neural response to negative prediction errors in cocaine addiction.

Authors:  Muhammad A Parvaz; Anna B Konova; Greg H Proudfit; Jonathan P Dunning; Pias Malaker; Scott J Moeller; Tom Maloney; Nelly Alia-Klein; Rita Z Goldstein
Journal:  J Neurosci       Date:  2015-02-04       Impact factor: 6.167

4.  Separate mesocortical and mesolimbic pathways encode effort and reward learning signals.

Authors:  Tobias U Hauser; Eran Eldar; Raymond J Dolan
Journal:  Proc Natl Acad Sci U S A       Date:  2017-08-14       Impact factor: 11.205

5.  Event-related potentials reflect impaired temporal interval learning following haloperidol administration.

Authors:  Sarah E Forster; Patrick Zirnheld; Anantha Shekhar; Stuart R Steinhauer; Brian F O'Donnell; William P Hetrick
Journal:  Psychopharmacology (Berl)       Date:  2017-06-10       Impact factor: 4.530

6.  Towards robust biomarkers of psychosocial interventions.

Authors:  Nadia Micali; Cristina Berchio
Journal:  Eur Child Adolesc Psychiatry       Date:  2019-02       Impact factor: 4.785

7.  Common mechanisms in error monitoring and action effect monitoring.

Authors:  Robert Steinhauser; Robert Wirth; Wilfried Kunde; Markus Janczyk; Marco Steinhauser
Journal:  Cogn Affect Behav Neurosci       Date:  2018-12       Impact factor: 3.282

8.  Does the processing of sensory and reward-prediction errors involve common neural resources? Evidence from a frontocentral negative potential modulated by movement execution errors.

Authors:  Flavie Torrecillos; Philippe Albouy; Thomas Brochier; Nicole Malfait
Journal:  J Neurosci       Date:  2014-04-02       Impact factor: 6.167

9.  Expectancy effects in feedback processing are explained primarily by time-frequency delta not theta.

Authors:  Adreanna T M Watts; Matthew D Bachman; Edward M Bernat
Journal:  Biol Psychol       Date:  2017-09-01       Impact factor: 3.251

10.  Exposure to money modulates neural responses to outcome evaluations involving social reward.

Authors:  Jin Li; Lei Liu; Yu Sun; Wei Fan; Mei Li; Yiping Zhong
Journal:  Soc Cogn Affect Neurosci       Date:  2020-01-30       Impact factor: 3.436

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.