Center for Neural Science, New York University, New York, New York 10003, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, Howard Hughes Medical Institute, Kavli Institute and Department of Neuroscience, Columbia University, New York, New York 10038, and Department of Physiology and Biophysics, University of Washington, Seattle, Washington 98195.
J Neurosci. 2013 Oct 16;33(42):16483-9. doi: 10.1523/JNEUROSCI.2094-13.2013.
Many decisions involve integration of evidence conferred by discrete cues over time. However, the neural mechanism of this integration is poorly understood. Several decision-making models suggest that integration of evidence is implemented by a dynamic system whose state evolves toward a stable point representing the decision outcome. The internal dynamics of such point attractor models render them sensitive to the temporal gaps between cues because their internal forces push the state forward once it is dislodged from the initial stable point. We asked whether human subjects are as sensitive to such temporal gaps. Subjects reported the net direction of stochastic random dot motion, which was presented in one or two brief observation windows (pulses). Pulse strength and interpulse interval varied randomly from trial to trial. We found that subjects' performance was largely invariant to the interpulse intervals up to at least 1 s. The findings question the implementation of the integration process via mechanisms that rely on autonomous changes of network state. The mechanism should be capable of freezing the state of the network at a variety of firing rate levels during temporal gaps between the cues, compatible with a line of stable attractor states.
许多决策都涉及随着时间的推移整合来自离散线索的证据。然而，这种整合的神经机制还不太清楚。有几个决策模型表明，证据的整合是通过一个动态系统来实现的，该系统的状态朝着代表决策结果的稳定点演变。这种点吸引子模型的内部动力学使得它们对线索之间的时间间隔很敏感，因为一旦状态从初始稳定点上脱离，内部力量就会推动状态向前移动。我们想知道人类受试者是否对这种时间间隔也同样敏感。受试者报告随机点扩散运动的净方向，这些运动在一个或两个短暂的观察窗口（脉冲）中呈现。脉冲强度和脉冲间隔在每次试验中随机变化。我们发现，受试者的表现基本上不受脉冲间隔的影响，至少在 1 秒内是这样。这些发现质疑了通过依赖于网络状态自主变化的机制来实现整合过程的观点。该机制应该能够在线索之间的时间间隔内冻结网络的状态，使其处于各种发射率水平，与一系列稳定的吸引子状态兼容。
