Department of Biomedical Engineering, The City College of The City University of New York, New York, NY 10031, USA.
Department of Biomedical Engineering, The City College of The City University of New York, New York, NY 10031, USA; Zuckerman Mind, Brain, and Behavior Institute, Columbia University, New York, NY 10027, USA.
Curr Biol. 2018 Mar 5;28(5):795-802.e6. doi: 10.1016/j.cub.2018.01.071. Epub 2018 Feb 15.
In dynamic environments, split-second sensorimotor decisions must be prioritized according to potential payoffs to maximize overall rewards. The impact of relative value on deliberative perceptual judgments has been examined extensively [1-6], but relatively little is known about value-biasing mechanisms in the common situation where physical evidence is strong but the time to act is severely limited. In prominent decision models, a noisy but statistically stationary representation of sensory evidence is integrated over time to an action-triggering bound, and value-biases are affected by starting the integrator closer to the more valuable bound. Here, we show significant departures from this account for humans making rapid sensory-instructed action choices. Behavior was best explained by a simple model in which the evidence representation-and hence, rate of accumulation-is itself biased by value and is non-stationary, increasing over the short decision time frame. Because the value bias initially dominates, the model uniquely predicts a dynamic "turn-around" effect on low-value cues, where the accumulator first launches toward the incorrect action but is then re-routed to the correct one. This was clearly exhibited in electrophysiological signals reflecting motor preparation and evidence accumulation. Finally, we construct an extended model that implements this dynamic effect through plausible sensory neural response modulations and demonstrate the correspondence between decision signal dynamics simulated from a behavioral fit of that model and the empirical decision signals. Our findings suggest that value and sensory information can exert simultaneous and dynamically countervailing influences on the trajectory of the accumulation-to-bound process, driving rapid, sensory-guided actions.
在动态环境中，必须根据潜在收益优先考虑瞬间的感觉运动决策，以最大化总体奖励。相对价值对审慎感知判断的影响已经被广泛研究过[1-6]，但在物理证据确凿但行动时间严重受限的常见情况下，关于价值偏见机制的了解相对较少。在著名的决策模型中，对感官证据的噪声但统计上稳定的表示会随时间积分到一个触发动作的边界，而价值偏见会受到更接近更有价值的边界的积分器起点的影响。在这里，我们发现人类进行快速感觉指导的行动选择时，该模型存在显著偏差。行为最好由一个简单的模型来解释，在该模型中，证据表示——因此，积累率——本身就受到价值的影响，并且是非稳定的，在短的决策时间框架内增加。由于价值偏见最初占主导地位，该模型独特地预测了低价值线索的动态“转向”效应，其中累积器最初朝向错误的动作启动，但随后被重新引导到正确的动作。这在反映运动准备和证据积累的电生理信号中得到了清晰的体现。最后，我们构建了一个扩展的模型，通过合理的感觉神经反应调制来实现这种动态效应，并证明了从该模型的行为拟合中模拟的决策信号动态与经验决策信号之间的对应关系。我们的发现表明，价值和感觉信息可以对积累到边界过程的轨迹同时产生动态的相互抵消的影响，从而驱动快速的、基于感觉的行动。
