Koulakov Alexei A, Rinberg Dmitry A, Tsigankov Dmitry N
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
Biol Cybern. 2005 Dec;93(6):447-62. doi: 10.1007/s00422-005-0022-z. Epub 2005 Nov 5.
Nervous systems often face the problem of classifying stimuli and making decisions based on these classifications. The neurons involved in these tasks can be characterized as sensory or motor, according to their correlation with sensory stimulus or motor response. In this study we define a third class of neurons responsible for making perceptual decisions. Our mathematical formalism enables the weighting of neuronal units according to their contribution to decision making, thus narrowing the field for more detailed studies of underlying mechanisms. We develop two definitions of a contribution to decision making. The first definition states that decision making activity can be found at the points of emergence for behavioral correlations in the system. The second definition involves the study of propagation of noise in the network. The latter definition is shown to be equivalent to the first one in the cases when they can be compared. Our results suggest a new approach to analyzing decision making networks.
神经系统常常面临对刺激进行分类并基于这些分类做出决策的问题。参与这些任务的神经元可根据其与感觉刺激或运动反应的相关性，被归类为感觉神经元或运动神经元。在本研究中，我们定义了负责做出感知决策的第三类神经元。我们的数学形式体系能够根据神经元单元对决策的贡献进行加权，从而为更详细地研究潜在机制缩小了研究范围。我们提出了两种对决策贡献的定义。第一个定义指出，在系统中行为相关性出现的点上可以发现决策活动。第二个定义涉及对网络中噪声传播的研究。在可比较的情况下，后一个定义被证明与第一个定义等效。我们的结果为分析决策网络提出了一种新方法。
