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Title: Timing and episodic-like memory in the rufous hummingbird
Author: Marshall, Rachael E. S.
ISNI:       0000 0004 2738 3152
Awarding Body: University of St Andrews
Current Institution: University of St Andrews
Date of Award: 2013
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How animals remember past events has recently received a lot of attention, as researchers search for an animal model of episodic memory, the system used by humans to remember their pasts and imagine the future. It has now been repeatedly demonstrated that animals can remember what they did where and when, although how similar these memories might be to episodic memory remains controversial. Another broader point highlighted by this research is the variety of different ways an event's location can be specified in time, and how little we know of how animals in the real world organise their behaviour in time. In this thesis I had two aims: to expand our understanding of the timing systems used by a free-living animal to organise its behaviour and, to look for novel ways of assessing the similarities and differences between animal and human memory. To this end, I investigated the timing abilities of free-living rufous hummingbirds Selasphorus rufus, in the Rocky Mountains of Alberta, Canada. In particular, I looked at the cues birds use to learn floral refill schedules, the types of temporal rules birds could learn, and the relationships between their memories for What, Where, and When. I also adapted a test used to study bird memory for use with human participants. Together, the studies presented in this thesis suggest two potentially useful future avenues for research into human episodic memory: investigating whether animal memory is subject to similar distortions to human memory, and looking at human memory under similar situations to those used to test animals. This research also highlights the variety of temporal systems hummingbirds can use to guide their behaviour, and points to the study of timing as a potentially fruitful arena for investigating how an animal's cognitive abilities can be predicted by its environment.
Supervisor: Healy, Susan Denise; Brown, Gillian Ruth Sponsor: Natural Environment Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available