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  Learning in a small vertebrate: A novel paradigm for juvenile zebrafish to study conditioned place avoidance

Yashina, K. (2018). Learning in a small vertebrate: A novel paradigm for juvenile zebrafish to study conditioned place avoidance. PhD Thesis, Ludwig-Maximilians-Universität, Graduate School of Systemic Neurosciences (GSN), München.

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Yashina_Ksenia.pdf (beliebiger Volltext), 8MB
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Yashina, Ksenia1, Autor           
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1Department: Genes-Circuits-Behavior / Baier, MPI of Neurobiology, Max Planck Society, ou_1128545              

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 Zusammenfassung: Learning has been extensively studied in many species (including primates, rodents, and insects). In larval and juvenile zebrafish, an established model organism, simple learning paradigms with one or two cues have been developed, with fish responding to classical and operant conditioning. However, more sophisticated paradigms, which would allow the study of more complex forms of learning, are still missing. We aimed to expand the existing set of learning paradigms for larval and juvenile zebrafish by introducing a conditioned place avoidance protocol in a Y-maze. Fish were conditioned to avoid one of the visually distinct arms of a Y-maze. Mild electric shocks were used as unconditioned aversive stimuli (US). We found that a robust response to conditioning emerges in 3-week-old juvenile zebrafish. The fish required distinct visual cues to develop a conditioned response. Moreover, we showed that fish could use various strategies to avoid the US: pattern avoidance, a preference for a safe pattern, or a preference for the center of the maze. The described paradigm lays the groundwork for studies of more complex learning abilities of juvenile zebrafish, such as spatial learning. Moreover, the juvenile zebrafish, which allows for non-invasive whole-brain imaging, provides an opportunity to study how different parts of the brain interact during memory formation and retrieval.

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Sprache(n): eng - English
 Datum: 2018-09-18
 Publikationsstatus: Angenommen
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 Ort, Verlag, Ausgabe: München : Ludwig-Maximilians-Universität, Graduate School of Systemic Neurosciences (GSN)
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 Identifikatoren: URN: urn:nbn:de:bvb:19-231630
 Art des Abschluß: Doktorarbeit

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