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Neural Mechanisms of Speed-Accuracy Tradeoff

机译：速度精度权衡的神经机制

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Intelligent agents balance speed of responding with accuracy of deciding. Stochastic accumulator models commonly explain this speed-accuracy tradeoff by strategic adjustment of response threshold. Several laboratories identify specific neurons in prefrontal and parietal cortex with this accumulation process, yet no neurophysiological correlates of speed-accuracy tradeoff have been described. We trained macaque monkeys to trade speed for accuracy on cue during visual search and recorded the activity of neurons in the frontal eye field. Unpredicted by any model, we discovered that speed-accuracy tradeoff is accomplished through several distinct adjustments. Visually responsive neurons modulated baseline firing rate, sensory gain, and the duration of perceptual processing. Movement neurons triggered responses with activity modulated in a direction opposite of model predictions. Thus, current stochastic accumulator models provide an incomplete description of the neural processes accomplishing speed-accuracy tradeoffs. The diversity of neural mechanisms was reconciled with the accumulator framework through an integrated accumulator model constrained by requirements of the motor system. Trading speed for accuracy is common in decision making, but the neuronal mechanisms have not been investigated. Heitz and Schall demonstrate proactive, sensory, and motor neurophysiological adjustments in prefrontal cortex. They also show how the findings can be reconciled with computational decision models.
机译：智能代理在响应速度与决策准确性之间取得平衡。随机蓄能器模型通常通过对响应阈值进行战略性调整来解释这种速度精度的权衡。几个实验室通过这种积累过程确定了额叶和顶叶皮层中的特定神经元，但尚未描述速度准确性权衡的神经生理相关性。我们训练了猕猴在视觉搜索过程中以速度换取提示的准确性，并记录了额眼视野中神经元的活动。在任何模型都无法预测的情况下，我们发现速度精度的权衡是通过几个不同的调整来完成的。视觉响应神经元调节基线放电率，感觉增益和知觉处理的持续时间。运动神经元以与模型预测相反的方向调制活动来触发响应。因此，当前的随机累加器模型对完成速度精度权衡的神经过程提供了不完整的描述。神经机制的多样性通过受电机系统要求约束的集成式蓄能器模型与蓄能器框架进行协调。在决策中，以准确性为代价的交易速度是很普遍的，但是尚未研究神经元机制。 Heitz和Schall证明前额叶皮层的主动，感觉和运动神经生理调节。他们还展示了如何将发现与计算决策模型相协调。

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