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一种关于序列经济选择的神经元理论。

A neuronal theory of sequential economic choice.

作者信息

Hayden Benjamin Y, Moreno-Bote Rubén

机构信息

Department of Neuroscience and Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA.

Department of Information and Communications Technologies, Pompeu Fabra University, Barcelona, Spain.

出版信息

Brain Neurosci Adv. 2018 Apr 13;2:2398212818766675. doi: 10.1177/2398212818766675. eCollection 2018 Jan-Dec.

Abstract

Results of recent studies point towards a new framework for the neural bases of economic choice. The principles of this framework include the idea that evaluation is limited to a single option within the focus of attention and that we accept or reject that option relative to the entire set of alternatives. Rejection leads attention to a new option, although it can later switch back to a previously rejected one. The option to which a neuron's firing rate refers is determined dynamically by attention and not stably by labelled lines. Value is always computed relative to the value of rejection. Comparison results not from explicit competition between discrete populations of neurons, but indirectly, as in a horse race, from the fact that the first option whose value crosses a threshold is selected. Consequently, comparison can occur within a single pool of neurons rather than by competition between two or more neuronal populations. The computations that constitute comparison thus occur at multiple levels, including premotor levels, simultaneously (i.e. the brain uses a distributed consensus), and not in discrete stages. This framework suggests a solution to a set of otherwise unresolved neuronal binding problems that result from the need to link options to values, comparisons to actions, and choices to outcomes.

摘要

近期研究结果指向了一个关于经济选择神经基础的新框架。该框架的原则包括:评估仅限于注意力焦点内的单个选项,并且我们相对于整个备选方案集接受或拒绝该选项。拒绝会使注意力转向新选项,尽管之后注意力可能会转回之前被拒绝的选项。神经元放电率所指的选项是由注意力动态决定的,而非由标记线路稳定决定。价值总是相对于拒绝的价值来计算。比较并非源于离散神经元群体之间的明确竞争,而是像赛马一样间接产生,即第一个价值超过阈值的选项被选中。因此,比较可以在单个神经元池中进行,而不是通过两个或更多神经元群体之间的竞争。构成比较的计算因此在多个层面同时进行(即大脑使用分布式共识),而不是在离散阶段进行。该框架为一组原本未解决的神经元绑定问题提供了一个解决方案,这些问题源于将选项与价值、比较与行动以及选择与结果联系起来的需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b093/7058205/415c9c78ea88/10.1177_2398212818766675-fig1.jpg

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