Degenerate boundaries for multiple-alternative decisions.
Degenerate boundaries for multiple-alternative decisions.
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DOI：
10.1038/s41467-022-32741-y
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发表时间：
2022-08-29
影响因子：
16.6
通讯作者：
中科院分区：
文献类型：
--
作者：
两种选择知觉决策的整合阈值模型指导了我们对人类和动物行为以及神经处理的理解。虽然这样的模型似乎自然延伸到多项选择决策，规范性框架的共识尚未出现，因此，多项选择的阈值特性的影响只进行了部分探讨。在这里，我们考虑顺序贝叶斯推理和决策的概念化作为一个粒子扩散的n维。我们通过模拟表明，在一个参数化的子集的时间无关的边界，最佳决策边界包括一个退化的家庭的非线性结构，共同依赖于多个的状态和速度-精度的权衡。这种简并性与当前的2选择结果相反，其中存在单个最优阈值。这样的边界支持静态和崩溃阈值作为决策的最佳策略，这两个结果从非线性边界的静态表示。我们的研究结果指向多项选择决策的规范理论，在此框架下提供了最佳决策阈值的表征，并为最佳决策的静态和动态决策边界之间的辩论提供了信息。动物如何在三个或更多的选择中做出多项选择的决定还没有得到很好的理解。在这里，作者使用模拟来揭示，在多项选择阈值边界的奖励景观上，不存在一个而是多个最佳参数值配置。
Integration-to-threshold models of two-choice perceptual decision making have guided our understanding of human and animal behavior and neural processing. Although such models seem to extend naturally to multiple-choice decision making, consensus on a normative framework has yet to emerge, and hence the implications of threshold characteristics for multiple choices have only been partially explored. Here we consider sequential Bayesian inference and a conceptualisation of decision making as a particle diffusing in n-dimensions. We show by simulation that, within a parameterised subset of time-independent boundaries, the optimal decision boundaries comprise a degenerate family of nonlinear structures that jointly depend on the state of multiple accumulators and speed-accuracy trade-offs. This degeneracy is contrary to current 2-choice results where there is a single optimal threshold. Such boundaries support both stationary and collapsing thresholds as optimal strategies for decision-making, both of which result from stationary representations of nonlinear boundaries. Our findings point towards a normative theory of multiple-choice decision making, provide a characterisation of optimal decision thresholds under this framework, and inform the debate between stationary and dynamic decision boundaries for optimal decision making. How animals make multiple-choice decisions over three or more alternatives is not well understood. Here the authors use simulations to uncover that there is not one but many optimal parameter value configurations on the reward landscape of the multiple-choice threshold boundaries.
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影响因子：
5.7
作者：
Churchland AK;Ditterich J
通讯作者：
Ditterich J
影响因子：
5.3
作者：
Hawkins, Guy E.;Forstmann, Birte U.;Brown, Scott D.
通讯作者：
Brown, Scott D.
影响因子：
4.8
作者：
Keuken MC;Van Maanen L;Bogacz R;Schäfer A;Neumann J;Turner R;Forstmann BU
通讯作者：
Forstmann BU
影响因子：
16.2
作者：
Heitz RP;Schall JD
通讯作者：
Schall JD
影响因子：
1.7
作者：
Balci, Fuat;Simen, Patrick;Cohen, Jonathan D.
通讯作者：
Cohen, Jonathan D.