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Eine der größten Herausforderungen in der Neurobiologie ist es, die neuronalen Prozesse zu verstehen, die Lernen und Gedächtnis zugrundeliegen. Welche biochemischen Pfade liegen z.B. der Koinzidenzdetektion von Reizen (klassische Konditionierung) oder einer Handlung und ihren Konsequenzen (operante Konditionierung) zugrunde? In welchen neuronalen Unterstrukturen werden diese Informationen gespeichert? Wie ähnlich sind die Stoffwechselwege, die diese beiden Arten des assoziativen Lernens vermitteln und auf welchem Niveau divergieren sie? Drosophila melanogaster ist wegen der Verfügbarkeit von Lern-Paradigmen und neurogenetischen Werkzeugen ein geeigneter Modell-Organismus, zum diese Fragen zu adressieren. Er ermöglicht eine umfangreiche Studie der Funktion des Gens S6KII, das in der Taufliege in klassischer und operanter Konditionierung unterschiedlich involviert ist (Bertolucci, 2002; Putz et al., 2004). Rettungsexperimenten zeigen, dass die olfaktorische Konditionierung in der Tully Maschine (ein klassisches, Pawlow’sches Konditionierungsparadigma) von dem Vorhandensein eines intakten S6KII Gens abhängt. Die Rettung war sowohl mit einer vollständigen, als auch einer partiellen Deletion erfolgreich und dies zeigt, dass der Verlust der phosphorylierenden Untereinheit der Kinase die Hauptursache des Funktionsdefektes war. Das GAL4/UAS System wurde benutzt, um die S6KII Expression zeitlich und räumlich zu steuern. Es wurde gezeigt, dass die Expression der Kinase während des adulten Stadiums für die Rettung hinreichend war. Dieser Befund schließt eine Entwicklungsstörung als Ursache für den mutanten Phänotyp aus. Außerdem zeigte die gezielte räumliche Rettung von S6KII die Notwendigkeit der Pilzkörper und schloss Strukturen wie das mediane Bündel, die Antennalloben und den Zentralkomplex aus. Dieses Muster ist dem vorher mit der rutabaga Mutation identifizierten sehr ähnlich (Zars et al., 2000). Experimente mit der Doppelmutante rut, ign58-1 deuten an, dass rutabaga und S6KII im gleichen Signalweg aktiv sind. Vorhergehende Studien hatten bereits gezeigt, dass die unterschiedlichen Ergebnisse bei operanter und klassischer Konditionierung auf verschiedenen Rollen für S6KII in den zwei Arten des Lernens hindeuten (Bertolucci, 2002; Putz, 2002). Diese Schlussfolgerung wurde durch den mutanten Phänotyp der transgenen Linien in der Positionskonditionierung und ihr wildtypisches Verhalten in der klassischen Konditionierung zusätzlich bekräftigt. Eine neue Art von Lern-Experiment, genannt „Idle Experiment“, wurde entworfen. Es basiert auf der Konditionierung der Laufaktivität, stellt eine operante Aufgabenstellung dar und überwindet einige der Limitationen des „Standard“ Heat-Box Experimentes. Die neue Art des Idle Experimentes erlaubt es, „gelernte Hilflosigkeit“ in Fliegen zu erforschen, dabei zeigte sich eine erstaunliche Ähnlichkeit zu den Vorgängen in komplizierteren Organismen wie Ratten, Mäusen oder Menschen. Gelernte Hilflosigkeit in der Taufliege wurde nur in den Weibchen beobachtet und wird von Antidepressiva beeinflusst.
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.
Sugar reward learning in Drosophila : neuronal circuits in Drosophila associative olfactory learning
(2006)
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.
It has been known for a long time that Drosophila can learn to discriminate not only between different odorants but also between different concentrations of the same odor. Olfactory associative learning has been described as a pairing between odorant and electric shock and since then, most of the experiments conducted in this respect have largely neglected the dual properties of odors: quality and intensity. For odorant-coupled short-term memory, a biochemical model has been proposed that mainly relies on the known cAMP signaling pathway. Mushroom bodies (MB) have been shown to be necessary and sufficient for this type of memory, and the MB-model of odor learning and short-term memory was established. Yet, theoretically, based on the MB-model, flies should not be able to learn concentrations if trained to the lower of the two concentrations in the test. In this thesis, I investigate the role of concentration-dependent learning, establishment of a concentration-dependent memory and their correlation to the standard two-odor learning as described by the MB-model. In order to highlight the difference between learning of quality and learning of intensity of the same odor I have tried to characterize the nature of the stimulus that is actually learned by the flies, leading to the conclusion that during the training flies learn all possible cues that are presented at the time. The type of the following test seems to govern the usage of the information available. This revealed a distinction between what flies learned and what is actually measured. Furthermore, I have shown that learning of concentration is associative and that it is symmetrical between high and low concentrations. I have also shown how the subjective quality perception of an odor changes with changing intensity, suggesting that one odor can have more than one scent. There is no proof that flies perceive a range of concentrations of one odorant as one (odor) quality. Flies display a certain level of concentration invariance that is limited and related to the particular concentration. Learning of concentration is relevant only to a limited range of concentrations within the boundaries of concentration invariance. Moreover, under certain conditions, two chemically distinct odorants could smell sufficiently similarly such, that they can be generalized between each other like if they would be of the same quality. Therefore, the abilities of the fly to identify the difference in quality or in intensity of the stimuli need to be distinguished. The way how the stimulus is analyzed and processed speaks in favor of a concept postulating the existence of two separated memories. To follow this concept, I have proposed a new form of memory called odor intensity memory (OIM), characterized it and compared it to other olfactory memories. OIM is independent of some members of the known cAMP signaling pathway and very likely forms the rutabaga-independent component of the standard two-odor memory. The rutabaga-dependent odor memory requires qualitatively different olfactory stimuli. OIM is revealed within the limits of concentration invariance where the memory test gives only sub-optimal performance for the concentration differences but discrimination of odor quality is not possible at all. Based on the available experimental tools, OIM seems to require the mushroom bodies the same as odor-quality memory but its properties are different. Flies can memorize the quality of several odorants at a given time but a newly formed memory of one odor interferes with the OIM stored before. In addition, the OIM lasts only 1 to 3 hours - much shorter than the odor-quality memory.
Zars and co-workers were able to localize an engram of aversive olfactory memory to the mushroom bodies of Drosophila (Zars et al., 2000). In this thesis, I followed up on this finding in two ways. Inspired by Zars et al. (2000), I first focused on the whether it would also be possible to localize memory extinction.While memory extinction is well established behaviorally, little is known about the underlying circuitry and molecular mechanisms. In extension to the findings by Zars et al (2000), I show that aversive olfactory memories remain localized to a subset of mushroom body Kenyon cells for up to 3 hours. Extinction localizes to the same set of Kenyon cells. This common localization suggests a model in which unreinforced presentations of a previously learned odorant intracellularly antagonizes the signaling cascades underlying memory formation. The second part also targets memory localization, but addresses appetitive memory. I show that memories for the same olfactory cue can be established through either sugar or electric shock reinforcement. Importantly, these memories localize to the same set of neurons within the mushroom body. Thus, the question becomes apparent how the same signal can be associated with different events. It is shown that two different monoamines are specificaly necessary for formation of either of these memories, dopamine in case of electric shock and octopamine in case of sugar memory, respectively. Taking the representation of the olfactory cue within the mushroom bodies into account, the data suggest that the two memory traces are located in the same Kenyon cells, but in separate subcellular domains, one modulated by dopamine, the other by octopamine. Taken together, this study takes two further steps in the search for the engram. (1) The result that in Drosophila olfactory learning several memories are organized within the same set of Kenyon cells is in contrast to the pessimism expressed by Lashley that is might not be possible to localize an engram. (2) Beyond localization, a possibible mechanism how several engrams about the same stimulus can be localized within the same neurons might be suggested by the models of subcellular organisation, as postulated in case of appetitive and aversive memory on the one hand and acquisition and extinction of aversive memory on the other hand.
Die Dissertation befaßt sich mit der Entwicklung einer multimedialen, datenbankgestützten Lehr- und Lernplattform. Die entwickelten Module ermöglichen und erweitern nicht nur die Möglichkeit des Selbststudiums für den Studenten sondern erleichtern auch die Arbeit der Dozenten. Außerdem wird auch die Zusammenarbeit und der Austausch von Lernobjekten zwischen verschiedenen Institutionen ermöglicht. In der Lehr- und Lernplattform können verschiedene Lernobjekt-Typen verwaltet werden. Exemplarisch wurden die Typen Bilder, 3D-Animationen, Vorlesungen, Lerntexte, Fallbeispiele und Quizelemente integriert. Die Lehr- und Lernplattform besteht aus drei Bausteinen: 1. In der Lernobjekt-Datenbank werden alle Lernobjekt-Typen und Lernobjekte verwaltet. 2. Autorenwerkzeuge dienen zur Erstellung von Lernobjekten. 3. In der Lernplattform werden die Lernobjekte den Studenten zum (Selbst-)Lernen präsentiert. Neben den Vorteilen, die der Einsatz von E-Learning im allgemeinen bietet, wie die flexible Lernorganisation oder die Nutzung von Lerninhalten unabhängig von Ort und Zeit, zeichnet sich die entwickelte Lehr- und Lernplattform besonders durch folgende Punkte aus: Generierung von Lerninhalten höherer Qualität durch multizentrische Expertenbündelung und Arbeitsteilung, Erweiterbarkeit auf andere, neue Lernobjekt-Typen, Verwaltbarkeit, Konsistenz, Flexibilität, geringer Verwaltungsaufwand, Navigationsmöglichkeiten für den Studenten, Personalisierbarkeit und Konformität zu internationalen Standards. Sowohl bei der Modellierung als auch bei der Umsetzung wurde darauf geachtet, möglichst gut die Anforderungen der Dermatologie bei gleichzeitiger Erweiterbarkeit auf andere, ähnliche Szenarien zu erfüllen. Besonders einfach sollte die Anpassung der Plattform für andere bildorientierte Disziplinen sein.
Most natural learning situations are of a complex nature and consist of a tight conjunction of the animal's behavior (B) with the perceived stimuli. According to the behavior of the animal in response to these stimuli, they are classified as being either biologically neutral (conditioned stimuli, CS) or important (unconditioned stimuli, US or reinforcer). A typical learning situation is thus identified by a three term contingency of B, CS and US. A functional characterization of the single associations during conditioning in such a three term contingency has so far hardly been possible. Therefore, the operational distinction between classical conditioning as a behavior-independent learning process (CS-US associations) and operant conditioning as essentially behavior-dependent learning (B-US associations) has proven very valuable. However, most learning experiments described so far have not been successful in fully separating operant from classical conditioning into single-association tasks. The Drosophila flight simulator in which the relevant behavior is a single motor variable (yaw torque), allows for the first time to completely separate the operant (B-US, B-CS) and the classical (CS-US) components of a complex learning situation and to examine their interactions. In this thesis the contributions of the single associations (CS-US, B-US and B-CS) to memory formation are studied. Moreover, for the first time a particularly prominent single association (CS-US) is characterized extensively in a three term contingency. A yoked control shows that classical (CS-US) pattern learning requires more training than operant pattern learning. Additionally, it can be demonstrated that an operantly trained stimulus can be successfully transferred from the behavior used during training to a new behavior in a subsequent test phase. This result shows unambiguously that during operant conditioning classical (CS-US) associations can be formed. In an extension to this insight, it emerges that such a classical association blocks the formation of an operant association, which would have been formed without the operant control of the learned stimuli. Instead the operant component seems to develop less markedly and is probably merged into a complex three-way association. This three-way association could either be implemented as a sequential B-CS-US or as a hierarchical (B-CS)-US association. The comparison of a simple classical (CS-US) with a composite operant (B, CS and US) learning situation and of a simple operant (B-US) with another composite operant (B, CS and US) learning situation, suggests a hierarchy of predictors of reinforcement. Operant behavior occurring during composite operant conditioning is hardly conditioned at all. The associability of classical stimuli that bear no relation to the behavior of the animal is of an intermediate value, as is operant behavior alone. Stimuli that are controlled by operant behavior accrue associative strength most easily. If several stimuli are available as potential predictors, again the question arises which CS-US associations are formed? A number of different studies in vertebrates yielded amazingly congruent results. These results inspired to examine and compare the properties of the CS-US association in a complex learning situation at the flight simulator with these vertebrate results. It is shown for the first time that Drosophila can learn compound stimuli and recall the individual components independently and in similar proportions. The attempt to obtain second-order conditioning with these stimuli, yielded a relatively small effect. In comparison with vertebrate data, blocking and sensory preconditioning experiments produced conforming as well as dissenting results. While no blocking could be found, a sound sensory preconditioning effect was obtained. Possible reasons for the failure to find blocking are discussed and further experiments are suggested. The sensory preconditioning effect found in this study is revealed using simultaneous stimulus presentation and depends on the amount of preconditioning. It is argued that this effect is a case of 'incidental learning', where two stimuli are associated without the need of reinforcement. Finally, the implications of the results obtained in this study for the general understanding of memory formation in complex learning situations are discussed.