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Computational models of anterior cingulate cortex : at the crossroads between prediction and effort

Eliana Vassena (UGent) , Clay Holroyd (UGent) and William Alexander (UGent)
(2017) FRONTIERS IN NEUROSCIENCE. 11.
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Abstract
In the last two decades the anterior cingulate cortex (ACC) has become one of the most investigated areas of the brain. Extensive neuroimaging evidence suggests countless functions for this region, ranging from conflict and error coding, to social cognition, pain and effortful control. In response to this burgeoning amount of data, a proliferation of computational models has tried to characterize the neurocognitive architecture of ACC. Early seminal models provided a computational explanation for a relatively circumscribed set of empirical findings, mainly accounting for EEG and fMRI evidence. More recent models have focused on ACC's contribution to effortful control. In parallel to these developments, several proposals attempted to explain within a single computational framework a wider variety of empirical findings that span different cognitive processes and experimental modalities. Here we critically evaluate these modeling attempts, highlighting the continued need to reconcile the array of disparate ACC observations within a coherent, unifying framework.
Keywords
MEDIAL PREFRONTAL CORTEX, ROUTINE SEQUENTIAL ACTION, ERROR-RELATED, NEGATIVITY, COGNITIVE CONTROL, FRONTAL-CORTEX, DECISION-MAKING, REWARD, PREDICTION, NEURONAL-ACTIVITY, DISTINCT REGIONS, NEURAL BASIS, anterior cingulate cortex (ACC), effort, prediction error, computational, models of ACC, computational modeling, effortful control

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Citation

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MLA
Vassena, Eliana, et al. “Computational Models of Anterior Cingulate Cortex : At the Crossroads between Prediction and Effort.” FRONTIERS IN NEUROSCIENCE, vol. 11, 2017, doi:10.3389/fnins.2017.00316.
APA
Vassena, E., Holroyd, C., & Alexander, W. (2017). Computational models of anterior cingulate cortex : at the crossroads between prediction and effort. FRONTIERS IN NEUROSCIENCE, 11. https://doi.org/10.3389/fnins.2017.00316
Chicago author-date
Vassena, Eliana, Clay Holroyd, and William Alexander. 2017. “Computational Models of Anterior Cingulate Cortex : At the Crossroads between Prediction and Effort.” FRONTIERS IN NEUROSCIENCE 11. https://doi.org/10.3389/fnins.2017.00316.
Chicago author-date (all authors)
Vassena, Eliana, Clay Holroyd, and William Alexander. 2017. “Computational Models of Anterior Cingulate Cortex : At the Crossroads between Prediction and Effort.” FRONTIERS IN NEUROSCIENCE 11. doi:10.3389/fnins.2017.00316.
Vancouver
1.
Vassena E, Holroyd C, Alexander W. Computational models of anterior cingulate cortex : at the crossroads between prediction and effort. FRONTIERS IN NEUROSCIENCE. 2017;11.
IEEE
[1]
E. Vassena, C. Holroyd, and W. Alexander, “Computational models of anterior cingulate cortex : at the crossroads between prediction and effort,” FRONTIERS IN NEUROSCIENCE, vol. 11, 2017.
@article{8552708,
  abstract     = {{In the last two decades the anterior cingulate cortex (ACC) has become one of the most investigated areas of the brain. Extensive neuroimaging evidence suggests countless functions for this region, ranging from conflict and error coding, to social cognition, pain and effortful control. In response to this burgeoning amount of data, a proliferation of computational models has tried to characterize the neurocognitive architecture of ACC. Early seminal models provided a computational explanation for a relatively circumscribed set of empirical findings, mainly accounting for EEG and fMRI evidence. More recent models have focused on ACC's contribution to effortful control. In parallel to these developments, several proposals attempted to explain within a single computational framework a wider variety of empirical findings that span different cognitive processes and experimental modalities. Here we critically evaluate these modeling attempts, highlighting the continued need to reconcile the array of disparate ACC observations within a coherent, unifying framework.}},
  articleno    = {{316}},
  author       = {{Vassena, Eliana and Holroyd, Clay and Alexander, William}},
  issn         = {{1662-453X}},
  journal      = {{FRONTIERS IN NEUROSCIENCE}},
  keywords     = {{MEDIAL PREFRONTAL CORTEX,ROUTINE SEQUENTIAL ACTION,ERROR-RELATED,NEGATIVITY,COGNITIVE CONTROL,FRONTAL-CORTEX,DECISION-MAKING,REWARD,PREDICTION,NEURONAL-ACTIVITY,DISTINCT REGIONS,NEURAL BASIS,anterior cingulate cortex (ACC),effort,prediction error,computational,models of ACC,computational modeling,effortful control}},
  language     = {{eng}},
  pages        = {{9}},
  title        = {{Computational models of anterior cingulate cortex : at the crossroads between prediction and effort}},
  url          = {{http://doi.org/10.3389/fnins.2017.00316}},
  volume       = {{11}},
  year         = {{2017}},
}
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