Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.conb.2011.11.004
DC FieldValue
dc.titleThe surveillance state of behavioral automation
dc.contributor.authorSchaefer, A.T.
dc.contributor.authorClaridge-Chang, A.
dc.date.accessioned2016-06-01T10:32:14Z
dc.date.available2016-06-01T10:32:14Z
dc.date.issued2012-02
dc.identifier.citationSchaefer, A.T., Claridge-Chang, A. (2012-02). The surveillance state of behavioral automation. Current Opinion in Neurobiology 22 (1) : 170-176. ScholarBank@NUS Repository. https://doi.org/10.1016/j.conb.2011.11.004
dc.identifier.issn09594388
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/124862
dc.description.abstractGenetics' demand for increased throughput is driving automatization of behavior analysis far beyond experimental workhorses like circadian monitors and the operant conditioning box. However, the new automation is not just faster: it is also allowing new kinds of experiments, many of which erase the boundaries of the traditional neuroscience disciplines (psychology, ethology and physiology) while producing insight into problems that were otherwise opaque. Ironically, a central theme of current automatization is to improve observation of animals in increasingly naturalistic environments. This is not just a return to 19th century priorities: the new observational methods provide unprecedented quantitation of actions and ever-closer integration with experimentation. © 2011 Elsevier Ltd.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.conb.2011.11.004
dc.sourceScopus
dc.typeReview
dc.contributor.departmentDUKE-NUS GRADUATE MEDICAL SCHOOL S'PORE
dc.description.doi10.1016/j.conb.2011.11.004
dc.description.sourcetitleCurrent Opinion in Neurobiology
dc.description.volume22
dc.description.issue1
dc.description.page170-176
dc.description.codenCOPUE
dc.identifier.isiut000301874400022
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