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奖赏驱动的纹状体通路竞争变化塑造了决策中的证据评估。

Reward-driven changes in striatal pathway competition shape evidence evaluation in decision-making.

机构信息

Dept. of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.

Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America.

出版信息

PLoS Comput Biol. 2019 May 6;15(5):e1006998. doi: 10.1371/journal.pcbi.1006998. eCollection 2019 May.

DOI:10.1371/journal.pcbi.1006998
PMID:31060045
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6534331/
Abstract

Cortico-basal-ganglia-thalamic (CBGT) networks are critical for adaptive decision-making, yet how changes to circuit-level properties impact cognitive algorithms remains unclear. Here we explore how dopaminergic plasticity at corticostriatal synapses alters competition between striatal pathways, impacting the evidence accumulation process during decision-making. Spike-timing dependent plasticity simulations showed that dopaminergic feedback based on rewards modified the ratio of direct and indirect corticostriatal weights within opposing action channels. Using the learned weight ratios in a full spiking CBGT network model, we simulated neural dynamics and decision outcomes in a reward-driven decision task and fit them with a drift diffusion model. Fits revealed that the rate of evidence accumulation varied with inter-channel differences in direct pathway activity while boundary height varied with overall indirect pathway activity. This multi-level modeling approach demonstrates how complementary learning and decision computations can emerge from corticostriatal plasticity.

摘要

皮质基底节丘脑（CBGT）网络对于适应性决策至关重要，但电路水平性质的变化如何影响认知算法尚不清楚。在这里，我们探讨了皮质纹状体突触的多巴胺能可塑性如何改变纹状体通路之间的竞争，从而影响决策过程中的证据积累过程。基于奖励的尖峰时间依赖性可塑性模拟表明，多巴胺能反馈根据奖励修改了相反动作通道内直接和间接皮质纹状体权重的比例。在一个完整的尖峰 CBGT 网络模型中使用学习到的权重比，我们模拟了奖励驱动决策任务中的神经动力学和决策结果，并使用漂移扩散模型对其进行拟合。拟合结果表明，证据积累的速度随直接通路活动中通道间差异的变化而变化，而边界高度随间接通路整体活动的变化而变化。这种多层次建模方法表明了皮质纹状体可塑性如何产生互补的学习和决策计算。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/dc27dd383102/pcbi.1006998.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/64a4e4578ebb/pcbi.1006998.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/7f617d892ee3/pcbi.1006998.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/13d8a6b03e74/pcbi.1006998.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/d99146da52fb/pcbi.1006998.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/6ca78cf0f3fc/pcbi.1006998.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/bb44b0ef7bea/pcbi.1006998.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/dc27dd383102/pcbi.1006998.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/64a4e4578ebb/pcbi.1006998.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/7f617d892ee3/pcbi.1006998.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/13d8a6b03e74/pcbi.1006998.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/d99146da52fb/pcbi.1006998.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/6ca78cf0f3fc/pcbi.1006998.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/bb44b0ef7bea/pcbi.1006998.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be55/6534331/dc27dd383102/pcbi.1006998.g007.jpg

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