Temporal prediction errors modulate cingulate-insular coupling

被引:28
作者
Limongi, Roberto [1 ,2 ]
Sutherland, Steven C. [1 ]
Zhu, Jian [1 ]
Young, Michael E. [3 ]
Habib, Reza [1 ]
机构
[1] So Illinois Univ, Carbondale, IL 62901 USA
[2] Venezuelan Inst Sci Res, Merida, Venezuela
[3] Kansas State Univ, Manhattan, KS 66506 USA
关键词
Dynamic causal models; Prediction error; Cingulate cortex; Insular cortex; Predictive behavior; MEDIAL PREFRONTAL CORTEX; NEURAL-NETWORK MODEL; OLD-WORLD MONKEY; COMPUTATIONAL MODELS; DOPAMINE NEURONS; DECISION-MAKING; FRONTAL-CORTEX; REWARD; CONFLICT; TASK;
D O I
10.1016/j.neuroimage.2012.12.078
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Prediction error (i.e., the difference between the expected and the actual event's outcome) mediates adaptive behavior. Activity in the anterior mid-cingulate cortex (aMCC) and in the anterior insula (aINS) is associated with the commission of prediction errors under uncertainty. We propose a dynamic causal model of effective connectivity (i.e., neuronal coupling) between the aMCC, the aINS, and the striatum in which the task context drives activity in the aINS and the temporal prediction errors modulate extrinsic cingulate-insular connections. With functional magnetic resonance imaging, we scanned 15 participants when they performed a temporal prediction task. They observed visual animations and predicted when a stationary ball began moving after being contacted by another moving ball. To induced uncertainty-driven prediction errors, we introduced spatial gaps and temporal delays between the balls. Classical and Bayesian fMRI analyses provided evidence to support that the aMCC-aINS system along with the striatum not only responds when humans predict whether a dynamic event occurs but also when it occurs. Our results reveal that the insula is the entry port of a three-region pathway involved in the processing of temporal predictions. Moreover, prediction errors rather than attentional demands, task difficulty, or task duration exert an influence in the aMCC-aINS system. Prediction errors debilitate the effect of the aMCC on the aINS. Finally, our computational model provides a way forward to characterize the physiological parallel of temporal prediction errors elicited in dynamic tasks. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:147 / 157
页数:11
相关论文
共 78 条
  • [51] O'Doherty JP, 2011, CONT TOP COGN NEUROS, P173
  • [52] Temporal difference models and reward-related learning in the human brain
    O'Doherty, JP
    Dayan, P
    Friston, KJ
    Critchley, H
    Dolan, RJ
    [J]. NEURON, 2003, 38 (02) : 329 - 337
  • [53] Controlling Uncertainty: A Review of Human Behavior in Complex Dynamic Environments
    Osman, Magda
    [J]. PSYCHOLOGICAL BULLETIN, 2010, 136 (01) : 65 - 86
  • [54] Comparing Families of Dynamic Causal Models
    Penny, Will D.
    Stephan, Klaas E.
    Daunizeau, Jean
    Rosa, Maria J.
    Friston, Karl J.
    Schofield, Thomas M.
    Leff, Alex P.
    [J]. PLOS COMPUTATIONAL BIOLOGY, 2010, 6 (03)
  • [55] Toward a method of selecting among computational models of cognition
    Pitt, MA
    Myung, IJ
    Zhang, SB
    [J]. PSYCHOLOGICAL REVIEW, 2002, 109 (03) : 472 - 491
  • [56] Risky business: the neuroeconomics of decision making under uncertainty
    Platt, Michael L.
    Huettel, Scott A.
    [J]. NATURE NEUROSCIENCE, 2008, 11 (04) : 398 - 403
  • [57] The diffusion decision model: Theory and data for two-choice decision tasks
    Ratcliff, Roger
    McKoon, Gail
    [J]. NEURAL COMPUTATION, 2008, 20 (04) : 873 - 922
  • [58] Rescorla R.A., 1972, Class. Cond. II: Curr. Res. Theory, V2, P64, DOI DOI 10.1101/GR.110528.110
  • [59] Bayesian model selection maps for group studies
    Rosa, M. J.
    Bestmann, S.
    Harrison, L.
    Penny, W.
    [J]. NEUROIMAGE, 2010, 49 (01) : 217 - 224
  • [60] A neural substrate of prediction and reward
    Schultz, W
    Dayan, P
    Montague, PR
    [J]. SCIENCE, 1997, 275 (5306) : 1593 - 1599