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不确定选项任务的多重选择神经动力学模型。

Multiple Choice Neurodynamical Model of the Uncertain Option Task.

作者信息

Insabato Andrea, Pannunzi Mario, Deco Gustavo

机构信息

Universitat Pompeu Fabra, Center for Brain and Cognition, Barcelona, Spain.

Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.

出版信息

PLoS Comput Biol. 2017 Jan 11;13(1):e1005250. doi: 10.1371/journal.pcbi.1005250. eCollection 2017 Jan.

Abstract

The uncertain option task has been recently adopted to investigate the neural systems underlying the decision confidence. Latterly single neurons activity has been recorded in lateral intraparietal cortex of monkeys performing an uncertain option task, where the subject is allowed to opt for a small but sure reward instead of making a risky perceptual decision. We propose a multiple choice model implemented in a discrete attractors network. This model is able to reproduce both behavioral and neurophysiological experimental data and therefore provides support to the numerous perspectives that interpret the uncertain option task as a sensory-motor association. The model explains the behavioral and neural data recorded in monkeys as the result of the multistable attractor landscape and produces several testable predictions. One of these predictions may help distinguish our model from a recently proposed continuous attractor model.

摘要

最近,不确定选项任务已被用于研究决策信心背后的神经系统。最近,在执行不确定选项任务的猴子的外侧顶内皮层中记录了单个神经元的活动,在该任务中,受试者可以选择一个小的但确定的奖励,而不是做出有风险的感知决策。我们提出了一种在离散吸引子网络中实现的多项选择模型。该模型能够重现行为和神经生理学实验数据,因此为将不确定选项任务解释为感觉运动关联的众多观点提供了支持。该模型将猴子身上记录的行为和神经数据解释为多稳态吸引子格局的结果,并产生了几个可测试的预测。这些预测之一可能有助于将我们的模型与最近提出的连续吸引子模型区分开来。

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