Literature DB >> 11243711

Automated behavioural analysis in animal pain studies.

D Jourdan1, D Ardid, A Eschalier.   

Abstract

The assessment of the effectiveness of analgesics is strongly based on observational data from behavioural tests. These tests are interesting and give a quantification of the effect of the drugs on the whole animal but their use is subject to several difficulties: (i) many results are difficult to analyse as they only correspond to the evaluation of a reflex response; (ii) the tests dealing with more integrated responses are also more difficult to use and closely depend on the experimenter's subjectivity. If automation is widely used in a lot of research fields, this is not the case in behavioural pharmacology. Yet, it can contribute to optimize the tests. The use of signal processing devices allows the automated (and thus objective) measurement of behavioural reactions to nociceptive stimulation (amplitude of a reflex, vocal emission intensity). Mechanical devices based on a computer-driven dynamic force detector allows the recording of some pain behaviours. Video image analysis allows the quantification of more complex behaviours (nociception-induced specific motor behaviours) as well as meaningful information during the same experimentation (exploratory behaviour, total motor activity, feeding behaviour). Moreover, these methods make it possible to obtain a more objective measurement, to reduce animal-experimenter interactions, to ease system use, and to improve effectiveness. The prospects to work in this field are multiple: continuation of the attempts at an automation of the behaviours specifically induced by chronic pain; development of real animal pain monitoring based on analysis of specific and non-specific behavioural modifications induced by pain. In this context, the automation of the behavioural analysis is likely to make possible real ethical progress thanks to an increase in the test's effectiveness and a real taking into account of animal's pain. Nevertheless, there are some limits due to characteristics of the behavioural expression of nociception and technological problems. Copyright 2001 Academic Press.

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Year:  2001        PMID: 11243711     DOI: 10.1006/phrs.2000.0760

Source DB:  PubMed          Journal:  Pharmacol Res        ISSN: 1043-6618            Impact factor:   7.658


  4 in total

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Authors:  Han Yi Fu; Shiang Jiuun Chen; Ruei Feng Chen; Wang Hsien Ding; Ling Long Kuo-Huang; Rong Nan Huang
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2.  Burrowing behavior as an indicator of post-laparotomy pain in mice.

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Review 3.  Animal models of cancer pain.

Authors:  Cholawat Pacharinsak; Alvin Beitz
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4.  Machine learning-based automated phenotyping of inflammatory nocifensive behavior in mice.

Authors:  Janine M Wotton; Emma Peterson; Laura Anderson; Stephen A Murray; Robert E Braun; Elissa J Chesler; Jacqueline K White; Vivek Kumar
Journal:  Mol Pain       Date:  2020 Jan-Dec       Impact factor: 3.395

  4 in total

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