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How do circuits in the mammalian cerebral cortex encode properties of the sensory environment in a way that can drive adaptive behavior? This question is fundamental to neuroscience, but it has been very difficult to approach directly. Various computational and theoretical models can explain a wide range of phenomena observed in the primary visual cortex (V1), including the anatomical organization of its circuits, the development of functional properties like orientation tuning, and behavioral effects like surround modulation. However, so far no model has been able to bridge these levels of description to explain how the machinery that develops directly affects behavior. Bridging these levels is important, because phenomena at any one specific level can have many possible explanations, but there are far fewer possibilities to consider once all of the available evidence is taken into account. In this thesis we integrate the information gleaned about cortical development, circuit and cell-type specific interactions, and anatomical, behavioral and electrophysiological measurements, to develop a computational model of V1 that is constrained enough to make predictions across multiple levels of description. Through a series of models incorporating increasing levels of biophysical detail and becoming increasingly better constrained, we are able to make detailed predictions for the types of mechanistic interactions required for robust development of cortical maps that have a realistic anatomical organization, and thereby gain insight into the computations performed by the primary visual cortex. The initial models focus on how existing anatomical and electrophysiological knowledge can be integrated into previously abstract models to give a well-grounded and highly constrained account of the emergence of pattern-specific tuning in the primary visual cortex. More detailed models then address the interactions between specific excitatory and inhibitory cell classes in V1, and what role each cell type may play during development and function. Finally, we demonstrate how these cell classes come together to form a circuit that gives rise not only to robust development but also the development of realistic lateral connectivity patterns. Crucially, these patterns reflect the statistics of the visual environment to which the model was exposed during development. This property allows us to explore how the model is able to capture higher-order information about the environment and use that information to optimize neural coding and aid the processing of complex visual tasks. Using this model we can make a number of very specific predictions about the mechanistic workings of the brain. Specifically, the model predicts a crucial role of parvalbumin-expressing interneurons in robust development and divisive normalization, while it implicates somatostatin immunoreactive neurons in mediating longer range and feature-selective suppression. The model also makes predictions about the role of these cell classes in efficient neural coding and under what conditions the model fails to organize. In particular, we show that a tight coupling of activity between the principal excitatory population and the parvalbumin population is central to robust and stable responses and organization, which may have implications for a variety of diseases where parvalbumin interneuron function is impaired, such as schizophrenia and autism. Further the model explains the switch from facilitatory to suppressive surround modulation effects as a simple by-product of the facilitating response function of long-range excitatory connections targeting a specialized class of inhibitory interneurons. Finally, the model allows us to make predictions about the statistics that are encoded in the extensive network of long-range intra-areal connectivity in V1, suggesting that even V1 can capture high-level statistical dependencies in the visual environment. The final model represents a comprehensive and well constrained model of the primary visual cortex, which for the first time can relate the physiological properties of individual cell classes to their role in development, learning and function. While the model is specifically tuned for V1, all mechanisms introduced are completely general, and can be used as a general cortical model, useful for studying phenomena across the visual cortex and even the cortex as a whole. This work is also highly relevant for clinical neuroscience, as the cell types studied here have been implicated in neurological disorders as wide ranging as autism, schizophrenia and Parkinson’s disease.

For the first time the transcriptional reprogramming of distinct root cortex cells during the arbuscular mycorrhizal (AM) symbiosis was investigated by combining Laser Capture Mirodissection and Affymetrix GeneChip® Medicago genome array hybridization. The establishment of cryosections facilitated the isolation of high quality RNA in sufficient amounts from three different cortical cell types. The transcript profiles of arbuscule-containing cells (arb cells), non-arbuscule-containing cells (nac cells) of Rhizophagus irregularis inoculated Medicago truncatula roots and cortex cells of non-inoculated roots (cor) were successfully explored. The data gave new insights in the symbiosis-related cellular reorganization processes and indicated that already nac cells seem to be prepared for the upcoming fungal colonization. The mycorrhizal- and phosphate-dependent transcription of a GRAS TF family member (MtGras8) was detected in arb cells and mycorrhizal roots. MtGRAS shares a high sequence similarity to a GRAS TF suggested to be involved in the fungal colonization processes (MtRAM1). The function of MtGras8 was unraveled upon RNA interference- (RNAi-) mediated gene silencing. An AM symbiosis-dependent expression of a RNAi construct (MtPt4pro::gras8-RNAi) revealed a successful gene silencing of MtGras8 leading to a reduced arbuscule abundance and a higher proportion of deformed arbuscules in root with reduced transcript levels. Accordingly, MtGras8 might control the arbuscule development and life-time. The targeting of MtGras8 by the phosphate-dependent regulated miRNA5204* was discovered previously (Devers et al., 2011). Since miRNA5204* is known to be affected by phosphate, the posttranscriptional regulation might represent a link between phosphate signaling and arbuscule development. In this work, the posttranscriptional regulation was confirmed by mis-expression of miRNA5204* in M. truncatula roots. The miRNA-mediated gene silencing affects the MtGras8 transcript abundance only in the first two weeks of the AM symbiosis and the mis-expression lines seem to mimic the phenotype of MtGras8-RNAi lines. Additionally, MtGRAS8 seems to form heterodimers with NSP2 and RAM1, which are known to be key regulators of the fungal colonization process (Hirsch et al., 2009; Gobbato et al., 2012). These data indicate that MtGras8 and miRNA5204* are linked to the sym pathway and regulate the arbuscule development in phosphate-dependent manner. / Die Leguminose Medicago truncatula (gehört zur Gattung des Schneckenklees) ist in der Lage sowohl eine Symbiose mit stickstofffixierenden Bakterien (Rhizobien), als auch mit Mykorrhiza-Pilzen einzugehen. Der Mykorrhiza-Pilz Rhizophagus irregularis dringt in die Wurzelrindenzellen ein und bildet Strukturen aus, die als Arbuskeln bezeichnet werden. Diese ermöglichen den Transfer von Nährstoffen, wie Phosphat in die Wurzelzellen. Die Pflanze liefert hingegen bis zu 20 % ihrer Photosyntheseprodukte an den Pilz. Da die Lebenszeit der Arbuskeln nur wenige Tage beträgt, können Wurzelrindenzellen mehrere Arbuskeln nacheinander beherbergen. Somit können neben arbuskelhaltigen, auch nicht-arbuskelhaltige Zellen in kolonisierten Wurzeln auftreten. Die nicht-arbuskelhaltigen Zellen beeinträchtigen die Sensitivität von Genregulationsanalysen, wenn die Genregulation während der Mykorrhiza-Symbiose anhand von ganzen kolonisierten Wurzeln untersucht wird. In dieser Arbeit konnte eine Zelltyp-spezifische Analyse der Genregulation von arbuskelhaltigen und nicht-arbuskelhaltigen Zellen durchgeführt, und eine Erhöhung der Sensitivität erreicht werden. Mittels Laser Capture Microdissection wurden Zellen aus Gefrierschnitten von Wurzeln isoliert. Aus den so gewonnen Zellen konnte RNA von ausreichender Qualität und Quantität extrahiert werden, um das Transkriptom der beiden Zelltypen mittels Mikroarrayhybridisierung zu untersuchen. Transkriptionsfaktoren (TFs) spielen wahrscheinlich eine Schlüsselrolle in der Umprogrammierung von Wurzelzellen während der Mykorrhiza-Symbiose. Daher wurde die Genregulation von TF-Genen in den zwei Zelltypen gezielt untersucht. Anhand von quantitativer RT-PCR und Promoter-Reporter-Fusionen wurde die differentielle Expression von mehreren TF-Transkripten in den verschiedenen Zelltypen bestätigt. Die Charakterisierung eines potentiellen GRAS TF (MtGRAS8) konnte eine stark Symbiose- und Phosphat-abhängige Induktion von Transkripten bestätigt werden. Mutanten mit verringerter MtGras8 Transkriptmenge wiesen eine verringerte Arbuskelzahl und deformierte Arbuskeln auf. MtGras8 scheint daher an der Arbuskelentwicklung beteiligt zu sein. Vorherige Experimente zeigten, dass MtGras8 Transkripte, von der Phosphat-regulierten MikroRNA5204* geschnitten werden (Devers et al., 2011). Dies konnte durch Überexpression der MikroRNA5204* in vivo bestätigt werden. Weiterhin konnten Protein-Protein-Interaktionen von MtGras8 mit bekannten GRAS TFs (NSP1, NSP2, RAM1) nachgewiesen und daraus eine Verbindung zu bekannten Symbiose-induzierten Signalkaskaden geschlossen werden. In dieser Arbeit wurde erstmals die Umprogrammierung von nicht-arbuskelhaltigen Zellen untersucht und neue Regulationselemente für die Kontrolle der Arbuskelentwicklung, wie MtGRAS8 und MikroRNA5204*, charakterisiert.

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