Behavioral Methods for the Study of the Ras–ERK Pathway in Memory Formation and Consolidation: Passive Avoidance and Novel Object Recognition Tests

MAPK/ERK通路 记忆巩固 神经科学 心理学 合并(业务) 奶油 计算机科学 生物 激酶 遗传学 转录因子 基因 会计 业务 海马体
作者
Raffaele d’Isa,Riccardo Brambilla,Stefania Fasano
出处
期刊:Methods in molecular biology [Springer Science+Business Media]
卷期号:: 131-156 被引量:28
标识
DOI:10.1007/978-1-62703-791-4_9
摘要

Memory is a high-level brain function that enables organisms to adapt their behavioral responses to the environment, hence increasing their probability of survival. The Ras–ERK pathway is a key molecular intracellular signalling cascade for memory consolidation. In this chapter we will describe two main one-trial behavioral tests commonly used in the field of memory research in order to assess the role of Ras–ERK signalling in long-term memory: passive avoidance and object recognition. Passive avoidance (PA) is a fear-motivated instrumental learning task, designed by Jarvik and Essman in 1960, in which animals learn to refrain from emitting a behavioral response that has previously been associated with a punishment. We will describe here the detailed protocol and show some examples of how PA can reveal impairments or enhancements in memory consolidation following loss or gain of function genetic manipulations of the Ras–ERK pathway. The phenotypes of global mutants as Ras-GRF1 KO, GENA53, and ERK1 KO mice, as well as of conditional region-specific mutants (striatal K-CREB mice), will be illustrated as examples. Novel object recognition (NOR), developed by Ennaceur and Delacour in 1988, is instead a more recent and highly ecological test, which relies on the natural tendency of rodents to spontaneously approach and explore novel objects, representing hence a useful non-stressful tool for the study of memory in animals without the employment of punishments or starvation/water restriction regimens. Careful indications will be given on how to select the positions for the novel object, in order to counterbalance for individual side preferences among mice during the training. Finally, the methods for calculating two learning indexes will be described. In addition to the classical discrimination index (DI) that measures the ability of an animal to discriminate between two different objects which are presented at the same time, we will describe the formula of a new index that we present here for the first time, the recognition index (RI), which quantifies the ability of an animal to recognize a same object at different time points and that, by taking into account the basal individual preferences displayed during the training, can give a more accurate measure of an animal’s actual recognition memory.

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