@phdthesis{Yarali2008,
  author    = {Yarali, Ayse},
  title     = {Aspects of predictive learning in the fruit fly},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-28741},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2008},
  abstract  = {Past experience contributes to behavioural organization mainly via learning: Animals learn otherwise ordinary cues as predictors for biologically significant events. This thesis studies such predictive, associative learning, using the fruit fly Drosophila melanogaster. I ask two main questions, which complement each other: One deals with the processing of those cues that are to be learned as predictors for an important event; the other one deals with the processing of the important event itself, which is to be predicted. Do fruit flies learn about combinations of olfactory and visual cues? I probe larval as well as adult fruit flies for the learning about combinations of olfactory and visual cues, using a so called 'biconditional discrimination' task: During training, one odour is paired with reinforcement only in light, but not in darkness; the other odour in turn is reinforced only in darkness, but not in light. Thus, neither the odours nor the visual conditions alone predict reinforcement, only combinations of both do. I find no evidence that either larval or adult fruit flies were to solve such task, speaking against a cross-talk between olfactory and visual modalities. Previous studies however suggest such cross-talk. To reconcile these results, I suggest classifying different kinds of interaction between sensory modalities, according to their site along the sensory-motor continuum: I consider an interaction 'truly' cross-modal, if it is between the specific features of the stimuli. I consider an interaction 'amodal' if it instead engages the behavioural tendencies or 'values' elicited by each stimulus. Such reasoning brings me to conclude that different behavioural tasks require different kinds of interaction between sensory modalities; whether a given kind of interaction will be found depends on the neuronal infrastructure, which is a function of the species and the developmental stage. Predictive learning of pain-relief in fruit flies Fruit flies build two opposing kinds of memory, based on an experience with electric shock: Those odours that precede shock during training are learned as predictors for punishment and are subsequently avoided; those odours that follow shock during training on the other hand are learned as signals for relief and are subsequently approached. I focus on such relief learning. I start with a detailed parametric analysis of relief learning, testing for reproducibility as well as effects of gender, repetition of training, odour identity, odour concentration and shock intensity. I also characterize how relief memories, once formed, decay. In addition, concerning the psychological mechanisms of relief learning, first, I show that relief learning establishes genuinely associative conditioned approach behaviour and second, I report that it is most likely not mediated by context associations. These results enable the following neurobiological analysis of relief learning; further, they will form in the future the basis for a mathematical model; finally, they will guide the researchers aiming at uncovering relief learning in other experimental systems. Next, I embark upon neurogenetic analysis of relief learning. First, I report that fruit flies mutant for the so called white gene build overall more 'negative' memories about an experience with electric shock. That is, in the white mutants, learning about the painful onset of shock is enhanced, whereas learning about the relieving offset of shock is diminished. As they are coherently affected, these two kinds of learning should be in a balance. The molecular mechanism of the effect of white on this balance remains unresolved. Finally, as a first step towards a neuronal circuit analysis of relief learning, I compare it to reward learning and punishment learning. I find that relief learning is distinct from both in terms of the requirement for biogenic amine signaling: Reward and punishment are respectively signalled by octopamine and dopamine, for relief learning, either of these seem dispensible. Further, I find no evidence for roles for two other biogenic amines, tyramine and serotonin in relief learning. Based on these findings I give directions for further research.},
  subject      = {Lernen},
  language  = {en}
}
@phdthesis{Thum2006,
  author    = {Thum, Andreas Stephan},
  title     = {Sugar reward learning in Drosophila : neuronal circuits in Drosophila associative olfactory learning},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-17930},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2006},
  abstract  = {Genetic intervention in the fly Drosophila melanogaster has provided strong evidence that the mushroom bodies of the insect brain act as the seat of memory traces for aversive and appetitive olfactory learning (reviewed in Heisenberg, 2003). In flies, electroshock is mainly used as negative reinforcer. Unfortunately this fact complicates a comparative consideration with other inscets as most studies use sugar as positive reinforcer. For example, several lines of evidence from honeybee and moth have suggested another site, the antennal lobe, to house neuronal plasticity underlying appetitive olfactory memory (reviewed in Menzel, 2001; Daly et al., 2004). Because of this I focused my work mainly on appetitive olfactory learning. In the first part of my thesis, I used a novel genetic tool, the TARGET system (McGuire et al., 2003), which allows the temporally controlled expression of a given effector gene in a defined set of cells. Comparing effector genes which either block neurotransmission or ablate cells showed important differences, revealing that selection of the appropriate effector gene is critical for evaluating the function of neural circuits. In the second part, a new engram of olfactory memory in the Drosophila projection neurons is described by restoring Rutabaga adenlylate cyclase (rut-AC) activity specifically in these cells. Expression of wild-type rutabaga in the projection neurons fully rescued the defect in sugar reward memory, but not in aversive electric shock memory. No difference was found in the stability of the appetitive memories rescued either in projection neurons or Kenyon cells. In the third part of the thesis I tried to understand how the reinforcing signals for sugar reward are internally represented. In the bee Hammer (1993) described a single octopaminergic neuron - called VUMmx1 - that mediates the sugar stimulus in associative olfactory reward learning. Analysis of single VUM neurons in the fly (Selcho, 2006) identified a neuron with a similar morphology as the VUMmx1 neuron. As there is a mutant in Drosophila lacking the last enzymatic step in octopamine synthesis (Monastirioti et al., 1996), Tyramine beta Hydroxylase, I was able to show that local Tyramine beta Hydroxylase expression successfully rescued sugar reward learning. This allows to conclude that about 250 cells including the VUM cluster are sufficient for mediating the sugar reinforcement signal in the fly. The description of a VUMmx1 similar neuron and the involvement of the VUM cluster in mediating the octopaminergic sugar stimulus are the first steps in establishing a neuronal map for US processing in Drosophila. Based on this work several experiments are contrivable to reach this ultimate goal in the fly. Taken together, the described similiarities between Drosophila and honeybee regarding the memory organisation in MBs and PNs and the proposed internal representation of the sugar reward suggest an evolutionarily conserved mechanism for appetitive olfactory learning in insects.},
  subject      = {Taufliege},
  language  = {en}
}