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水蛭神经系统中的决策。

Decision-making in the leech nervous system.

机构信息

UCSD, Division of Biology, Neurobiology Section 0357, 9500 Gilman Dr., La Jolla, California 92093-0357.

出版信息

Integr Comp Biol. 2002 Aug;42(4):716-24. doi: 10.1093/icb/42.4.716.

DOI:10.1093/icb/42.4.716
PMID:21708768
Abstract

Previous models of behavioral choice have described two types of hierarchy, a decision hierarchy, in which different classes of decisions are made at each level (Tinbergen, 1951), and a behavioral hierarchy, in which one behavior will take precedence over others (Davis, 1985). Most experimental work on the neuronal basis of decision-making has focussed on the latter of these: a behavioral hierarchy is described for an animal, and the neuronal basis for this hierarchy, hypothesized to depend on inhibitory interactions, is investigated. Although the concept of "dedicated command neurons" has been useful for guiding these studies, it appears that such neurons are rare. We present evidence that in the leech, most neurons, including high-level decision neurons, are active in more than one behavior. We include data from one newly-identified neuron that elicits both swimming and crawling motor patterns. We suggest that decisions are made by a "combinatorial code": what behavior is produced depends on the specific combination of decision neurons that are active at a particular time. Finally, we discuss how decision neurons may be arranged into a decision hierarchy, with neurons at each sequential level responsible for choosing between a narrower range of behaviors. We suggest additional sensory information is incorporated at each level to inform the decision.

摘要

先前的行为选择模型描述了两种层次结构,一种是决策层次结构,其中在每个级别做出不同类别的决策(Tinbergen,1951),另一种是行为层次结构,其中一种行为将优先于其他行为(Davis,1985)。大多数关于决策神经基础的实验工作都集中在后一种层次结构上:为动物描述了一种行为层次结构,并研究了假设依赖于抑制相互作用的这种层次结构的神经基础。尽管“专用命令神经元”的概念对于指导这些研究很有用,但似乎这种神经元很少。我们提出证据表明,在水蛭中,包括高级决策神经元在内的大多数神经元在不止一种行为中都活跃。我们包括了一个新识别的神经元的数据,该神经元引发游泳和爬行运动模式。我们认为决策是通过“组合码”做出的:产生的行为取决于特定时间内活跃的决策神经元的特定组合。最后,我们讨论了决策神经元如何被安排成决策层次结构,每个连续层次的神经元负责在更窄的行为范围内进行选择。我们建议在每个级别都纳入额外的感官信息来通知决策。

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