@phdthesis{PradaSalcedo2018,
  author    = {Prada Salcedo, Juan Pablo},
  title     = {Image Processing and other bioinformatic tools for Neurobiology},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157721},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {Neurobiology is widely supported by bioinformatics. Due to the big amount of data generated from the biological side a computational approach is required. This thesis presents four different cases of bioinformatic tools applied to the service of Neurobiology. The first two tools presented belong to the field of image processing. In the first case, we make use of an algorithm based on the wavelet transformation to assess calcium activity events in cultured neurons. We designed an open source tool to assist neurobiology researchers in the analysis of calcium imaging videos. Such analysis is usually done manually which is time consuming and highly subjective. Our tool speeds up the work and offers the possibility of an unbiased detection of the calcium events. Even more important is that our algorithm not only detects the neuron spiking activity but also local spontaneous activity which is normally discarded because it is considered irrelevant. We showed that this activity is determinant in the calcium dynamics in neurons and it is involved in important functions like signal modulation and memory and learning. The second project is a segmentation task. In our case we are interested in segmenting the neuron nuclei in electron microscopy images of c.elegans. Marking these structures is necessary in order to reconstruct the connectome of the organism. C.elegans is a great study case due to the simplicity of its nervous system (only 502 neurons). This worm, despite its simplicity has taught us a lot about neuronal mechanisms. There is still a lot of information we can extract from the c.elegans, therein lies the importance of reconstructing its connectome. There is a current version of the c.elegans connectome but it was done by hand and on a single subject which leaves a big room for errors. By automatizing the segmentation of the electron microscopy images we guarantee an unbiased approach and we will be able to verify the connectome on several subjects. For the third project we moved from image processing applications to biological modeling. Because of the high complexity of even small biological systems it is necessary to analyze them with the help of computational tools. The term in silico was coined to refer to such computational models of biological systems. We designed an in silico model of the TNF (Tumor necrosis factor) ligand and its two principal receptors. This biological system is of high relevance because it is involved in the inflammation process. Inflammation is of most importance as protection mechanism but it can also lead to complicated diseases (e.g. cancer). Chronic inflammation processes can be particularly dangerous in the brain. In order to better understand the dynamics that govern the TNF system we created a model using the BioNetGen language. This is a rule based language that allows one to simulate systems where multiple agents are governed by a single rule. Using our model we characterized the TNF system and hypothesized about the relation of the ligand with each of the two receptors. Our hypotheses can be later used to define drug targets in the system or possible treatments for chronic inflammation or lack of the inflammatory response. The final project deals with the protein folding problem. In our organism proteins are folded all the time, because only in their folded conformation are proteins capable of doing their job (with some very few exceptions). This folding process presents a great challenge for science because it has been shown to be an NP problem. NP means non deterministic Polynomial time problem. This basically means that this kind of problems cannot be efficiently solved. Nevertheless, somehow the body is capable of folding a protein in just milliseconds. This phenomenon puzzles not only biologists but also mathematicians. In mathematics NP problems have been studied for a long time and it is known that given the solution to one NP problem we could solve many of them (i.e. NP-complete problems). If we manage to understand how nature solves the protein folding problem then we might be able to apply this solution to many other problems. Our research intends to contribute to this discussion. Unfortunately, not to explain how nature solves the protein folding problem, but to explain that it does not solve the problem at all. This seems contradictory since I just mentioned that the body folds proteins all the time, but our hypothesis is that the organisms have learned to solve a simplified version of the NP problem. Nature does not solve the protein folding problem in its full complexity. It simply solves a small instance of the problem. An instance which is as simple as a convex optimization problem. We formulate the protein folding problem as an optimization problem to illustrate our claim and present some toy examples to illustrate the formulation. If our hypothesis is true, it means that protein folding is a simple problem. So we just need to understand and model the conditions of the vicinity inside the cell at the moment the folding process occurs. Once we understand this starting conformation and its influence in the folding process we will be able to design treatments for amyloid diseases such as Alzheimer's and Parkinson's. In summary this thesis project contributes to the neurobiology research field from four different fronts. Two are practical contributions with immediate benefits, such as the calcium imaging video analysis tool and the TNF in silico model. The neuron nuclei segmentation is a contribution for the near future. A step towards the full annotation of the c.elegans connectome and later for the reconstruction of the connectome of other species. And finally, the protein folding project is a first impulse to change the way we conceive the protein folding process in nature. We try to point future research in a novel direction, where the amino code is not the most relevant characteristic of the process but the conditions within the cell.},
  subject      = {Bildverarbeitung},
  language  = {en}
}
@phdthesis{Eschbach2011,
  author    = {Eschbach, Claire},
  title     = {Classical and operant learning in the larvae of Drosophila melanogaster},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-70583},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {In dieser Doktorarbeit studiere ich einige psychologische Aspekte im Verhalten der Drosophila, insbesondere von Drosophila Larven. Nach einer Einleitung, in der ich den wissenschaftlichen Kontext darstelle und die Mechanismen der olfaktorischen Wahrnehmung sowie des klassichen und operanten Lernens beschreibe, stelle ich die verschiedenen Experimente meiner Doktorarbeit vor. Wahrnehmung Das zweite Kapitel behandelt die Art, in der adulte Drosophila zwischen Einzeld{\"u}ften und Duftgemischen generaliseren. Ich habe gefunden, daß die Fliegen eine Mischung aus zwei D{\"u}ften als gleich verschieden von ihren beiden Elementen wahrnehmen; und daß die Intensit{\"a}t sowie die chemisch-physikalische Natur der Elemente das Ausmass der Generalisierung zwischen der Mischung und ihren beiden Elementen beeinflusst. Diese Entdeckungen sollten f{\"u}r die weitere Forschung anregend sein, wie zum Beispiel zum functional imaging. Ged{\"a}chtnis Das dritte Kapitel stellt die Etablierung eines neuen Protokolls zur klassischen Konditionierung bei Drosophila Larven dar. Es handelt sich um Experimente, bei denen ein Duft mit einer mechanischen St{\"o}rung als Strafreiz verkn{\"u}pft wird. Das Protokoll wird einen Vergleich zwischen zwei Arten vom aversiven Ged{\"a}chtnissen (Geschmack vs. mechanische St{\"o}rung als Strafreize) erm{\"o}glichen, einschliesslich eines Vergleiches ihrer neurogenetischen Grundlagen; zudem kann nun geforscht werden, ob die jeweiligen Ged{\"a}chtnisse spezifisch f{\"u}r die Art des verwendeten Strafreizes sind. Selbstgestaltung Das vierte Kapitel umfasst unsere Versuche, operantes Ged{\"a}chtnis bei Drosophila Larven zu beobachten. Zumindest f{\"u}r die unmittelbar ersten Momente des Tests konnte ich zeigen, dass die Larven ihr Verhalten entsprechend dem Training ausrichten. Dieses Ged{\"a}chtnis scheint jedoch im Laufe des Tests schnell zu verschwinden. Es ist daher geraten, diese Ergebnisse {\"u}ber operantes Lernen zu wiederholen, eventuell das experimentelle Protokoll zu verbessern, um so eine systematische Analyse der Bedingungen und Mechanismen f{\"u}r das operante Lernen bei der Drosophila Larve zu erlauben. Im f{\"u}nften Kapitel verwende ich die im Rahmen des vierten Kapitels entwickelten Methoden f{\"u}r eine Analyse der Fortbewegung der Larven. Ich habe insbesondere die Wirkung des pflanzlichen ‚cognitive enhancers' Rhodiola rosea untersucht, sowie die Auswirkungen von Mutationen in den Genen, welche f{\"u}r Synapsin und SAP47 kodieren; schliesslich habe ich getestet, ob die Geschmacksqualit{\"a}t der Testsituation lokomotorische Parameter ver{\"a}ndert. Diese Dissertation erbringt also eine Reihe neuer Aspekte zur Psychologie der Drosophila und wird hoffentlich in diesem Bereich der Forschung neue Wege {\"o}ffnen.},
  subject      = {Lernen},
  language  = {en}
}
@phdthesis{Hahn2010,
  author    = {Hahn, Tim},
  title     = {Integrating neurobiological markers of depression: an fMRI-based pattern classification approach},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-49962},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2010},
  abstract  = {While depressive disorders are, to date, diagnosed based on behavioral symptoms and course of illness, the interest in neurobiological markers of psychiatric disorders has grown substantially in recent years. However, current classification approaches are mainly based on data from a single biomarker, making it difficult to predict diseases such as depression which are characterized by a complex pattern of symptoms. Accordingly, none of the previously investigated single biomarkers has shown sufficient predictive power for practical application. In this work, we therefore propose an algorithm which integrates neuroimaging data associated with multiple, symptom-related neural processes relevant in depression to improve classification accuracy. First, we identified the core-symptoms of depression from standard classification systems. Then, we designed and conducted three experimental paradigms probing psychological processes known to be related to these symptoms using functional Magnetic Resonance Imaging. In order to integrate the resulting 12 high-dimensional biomarkers, we developed a multi-source pattern recognition algorithm based on a combination of Gaussian Process Classifiers and decision trees. Applying this approach to a group of 30 healthy controls and 30 depressive in-patients who were on a variety of medications and displayed varying degrees of symptom-severity allowed for high-accuracy single-subject classification. Specifically, integrating biomarkers yielded an accuracy of 83\% while the best of the 12 single biomarkers alone classified a significantly lower number of subjects (72\%) correctly. Thus, integrated biomarker-based classification of a heterogeneous, real-life sample resulted in accuracy comparable to the highest ever achieved in previous single biomarker research. Furthermore, investigation of the final prediction model revealed that neural activation during the processing of neutral facial expressions, large rewards, and safety cues is most relevant for over-all classification. We conclude that combining brain activation related to the core-symptoms of depression using the multi-source pattern classification approach developed in this work substantially increases classification accuracy while providing a sparse relational biomarker-model for future prediction.},
  subject      = {Patientenklassifikation},
  language  = {en}
}
@phdthesis{Ruchty2010,
  author    = {Ruchty, Markus},
  title     = {Sensory basis of thermal orientation in leaf-cutting ants},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-48906},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2010},
  abstract  = {Leaf-cutting ants have a highly developed thermal sense which the insects use to regulate the own body temperature and also to optimize brood and fungus development. Apart from the already described temperature guided behaviors inside the nest it is unknown to what extent the ants may use their thermal sense outside the nest. As part of the present thesis, the question was addressed whether leaf-cutting ants (Atta vollenweideri) are able to learn the position of a warm object as landmark for orientation during foraging. Using absolute conditioning, it was shown that ten training trials are sufficient to elicit the association be-tween food reward and the temperature stimulus. In the test situation (without reward) a significantly higher amount of ants preferred the heated site compared to the unheated con-trol. Importantly, thermal radiation alone was sufficient to establish the learned association and served as orientation cue during the test situation (chapter IV). Based on the experi-mental design used in the previous chapter, the localization of thermosensitive neurons, which detect the underlying thermal stimuli, is restricted to the head or the antennae of the ants. The antennal sensillum coeloconicum is a potential candidate to detect the thermal stimuli during the orientation behavior. In chapter V the sensillum coeloconicum of Atta vollenweideri was investigated concerning its gross morphology, fine-structure and the phy-siology of the associated thermosensitive neuron. The sensillum is predominantly located on the apical antennal segment (antennal tip) where around 12 sensilla are clustered, and it has a peg-in-pit morphology with a double walled, multiporous peg. The sensory peg is deeply embedded in a cuticular pit, connected to the environment only by a tiny aperture. The sen-sillum houses three receptor neurons of which one is thermosensitive whereas the sensory modality of the other two neurons remains to be shown. Upon stimulation with a drop in temperature, the thermosensitve neuron responds with a phasic-tonic increase in neuronal activity (cold-sensitive neuron) and shows rapid adaptation to prolonged stimulation. In ad-dition, it is shown that thermal radiation is an effective stimulus for the thermosensitive neuron. This is the first evidence that sensilla coeloconica play an important role during the thermal orientation behavior described in chapter IV. During the test situation of the classic-al conditioning paradigm, the ants showed rapid antennal movements, indicating that they scan their environment in order to detect the heated object. Rapid antennal movements will result in rapid discontinuities of thermal radiation that re-quire thermosensitive neurons with outstanding sensitivity and high temporal resolution. In Chapter VI the question was addressed whether the thermosensitive neuron of the sensilla coeloconica fulfils these preconditions. Extracellular recordings revealed that the neuron is extremely sensitive to temperature transients and that, due to the response dynamics, an estimated stimulus frequency of up to 5 Hz can be resolved by the neuron. Already a tem-perature increase of only 0.005 °C leads to a pronounced response of the thermosensitive neuron. Through sensory adaptation, the sensitivity to temperature transients is maintained over a wide range of ambient temperatures. The discovered extreme sensitivity, the high temporal resolution and the pronounced adaptation abilities are further evidence support-ing the idea that sensilla coeloconica receive information of the thermal environment, which the ants may use for orientation. In order to understand how the ants use their thermal environment for orientation, it is ne-cessary to know where and how thermal information is processed in their central nervous system. In Chapter VII the question is addressed where in the brain the thermal information, specifically received by the thermosensitive neuron of sensilla coeloconica, is represented. By selectively staining single sensilla coeloconica, the axons of the receptor neurons could be tracked into the antennal lobe of Atta vollenweideri workers. Each of the three axons termi-nated in a single functional unit (glomerulus) of the antennal lobe. Two of the innervated glomeruli were adjacent to each other and are located lateral, while the third one was clear-ly separate and located medial in the antennal lobe. Using two-photon Ca2+ imaging of an-tennal lobe projection neurons, the general representation of thermal information in the antennal lobe was studied. In 11 investigated antennal lobes up to six different glomeruli responded to temperature stimulation in a single specimen. Both, warm- and cold-sensitive glomeruli could be identified. All thermosensitive glomeruli were located in the medial half of the antennal lobe. Based on the correlative evidence of the general representation of thermal information and the results from the single sensilla stainings, it is assumed that thermal information received by sensilla coeloconica is processed in the medial of the three target glomeruli. This part of the thesis shows the important role of the antennal lobe in temperature processing and links one specific thermosensitive neuron to its target region (a single glomerulus). In chapter V it was shown that the sensilla coeloconica are clustered at the antennal tip and have an extraordinary peg-in-pit morphology. In the last chapter of this thesis (Chapter VIII) the question is addressed whether the morphology of the sensilla coeloconica predicts the receptive field of the thermosensitive neuron during the detection of thermal radiation. The sensory pegs of all sensilla coeloconica in the apical cluster have a similar orientation, which was not constraint by the shape of the antennal tip where the cluster is located. This finding indicates that the sensilla coeloconica function as a single unit. Finally the hypothesis was tested whether a single sensillum could be direction sensitive to thermal radiation based on its eye-catching morphology. By stimulating the thermosensitive neuron from various angles around the sensillum this indeed could be shown. This is the last and most significant evi-dence that the sensilla coeloconica may be adapted to detect spatially distributed heated objects in the environment during the thermal landmark orientation of ants.},
  subject      = {Neurobiologie},
  language  = {en}
}