Optimal and human eye movements to clustered low value cues to increase decision rewards during search.
Optimal and human eye movements to clustered low value cues to increase decision rewards during search.
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DOI：
10.1016/j.visres.2015.05.016
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发表时间：
2015-08
期刊：
影响因子：
1.8
通讯作者：
Akbas E
中科院分区：
文献类型：
--
作者：
Eckstein MP;Schoonveld W;Zhang S;Mack SC;Akbas E
奖赏对灵长类动物的运动规划和编码视觉信息和动作的神经元的放电有重要影响。当眼球运动到一个目标是不同的奖励跨位置，灵长类动物执行扫视可能的目标位置与最高的预期值，产品的感官证据和潜在的回报（扫视最大预期值模型，sMEV）。然而，在自然界中，眼球运动并没有直接得到奖励。他们的作用是收集信息，以支持随后的奖励搜索决策和行动。关于决策奖励对眼跳的影响知之甚少。我们发现，当视觉搜索后，在线索位置上改变决策奖励时，人类可以计划他们的眼球运动来增加决策奖励。至关重要的是，我们报告了这样一种情况：七分之五的受试者不会优先将眼跳部署到奖励最高的可能目标位置，这是奖励眼睛运动时的最佳策略。相反，当这种策略优化决策奖励时，这些人会向价值较低但聚集的位置进行扫视，这与理想贝叶斯奖励策略的偏好一致，该策略考虑到目标在偏心率上的可见性。理想的回报率可以用sMEV模型来近似，该模型具有来自空间聚类位置的回报池。我们还发现观察员与系统偏离的最佳策略和观察员间的眼动计划的变化。这些偏差通常反映了导致接近最佳决策奖励的固定策略的多样性，但对于一些观察者来说，它与眼动规划中的次优选择有关。
Rewards have important influences on the motor planning of primates and the firing of neurons coding visual information and action. When eye movements to a target are differentially rewarded across locations, primates execute saccades towards the possible target location with the highest expected value, a product of sensory evidence and potentially earned reward (saccade to maximum expected value model, sMEV). Yet, in the natural world eye movements are not directly rewarded. Their role is to gather information to support subsequent rewarded search decisions and actions. Less is known about the effects of decision rewards on saccades. We show that when varying the decision rewards across cued locations following visual search, humans can plan their eye movements to increase decision rewards. Critically, we report a scenario for which five of seven tested humans do not preferentially deploy saccades to the possible target location with the highest reward, a strategy which is optimal when rewarding eye movements. Instead, these humans make saccades towards lower value but clustered locations when this strategy optimizes decision rewards consistent with the preferences of an ideal Bayesian reward searcher that takes into account the visibility of the target across eccentricities. The ideal reward searcher can be approximated with a sMEV model with pooling of rewards from spatially clustered locations. We also find observers with systematic departures from the optimal strategy and inter-observer variability of eye movement plans. These deviations often reflect multiplicity of fixation strategies that lead to near optimal decision rewards but, for some observers, it relates to suboptimal choices in eye movement planning.
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影响因子：
13.9
作者：
Bisley JW;Goldberg ME
通讯作者：
Goldberg ME
影响因子：
1.7
作者：
Castelhano, Monica S.;Heaven, Chelsea
通讯作者：
Heaven, Chelsea
DOI：
10.3758/bf03208380
发表时间：
1995-11-01
期刊：
PERCEPTION & PSYCHOPHYSICS
影响因子：
--
作者：
CARRASCO, M;EVERT, DL;KATZ, SM
通讯作者：
KATZ, SM
DOI：
10.1073/pnas.1104047108
发表时间：
2011-06-21
影响因子：
11.1
作者：
Anderson, Brian A.;Laurent, Patryk A.;Yantis, Steven
通讯作者：
Yantis, Steven
影响因子：
1.8
作者：
Findlay, JM
通讯作者：
Findlay, JM