South Africa's small, micro and medium enterprise (SMME) sector is an important contributor to GDP and employment. However, the contributions underperform the average low-income and middle-income country. The government has plans to increase SMME GDP and employment contributions. To do this, the Department of Small Business Development was recently established, and together with other agencies, several business incubators have been established. The number of incubators operating in the country has increased significantly in the recent past. There is a belief that incubators are organisations that will help SMMEs perform better and improve their chances of survival. To improve employment and GDP growth, SMMEs need to perform better and survive longer. However, there is limited evidence to confirm this understanding. This research aims to fill this gap of knowledge by investigating whether firms that participate in incubators have improved revenue, employment and financing performance, which improves survival prospects. The ordinary least squares estimation techniques was employed to estimate a cross sectional model to examine the effect of incubator participation on the performance of 182 SMMEs. The performance measures used included revenue, employment, and external equity, debt and philanthropic finance. The findings in the study from the cross-sectional analysis showed there was no selection bias and endogeneity evident. Firms with better performing dependent variables (revenue, employment and external financing) were no more likely to be selected to be incubated. Following this, the study found that firms that participated in incubators did not have a statistically significant different level of revenue, number of employees or external equity and debt financing, compared to firms that did not participate in incubators. The findings from the study indicated that increased participation in incubators did not guarantee increased revenue, employment and external equity and debt financing. The findings indicated that there was a possibility that incubated firms could raise more philanthropic financing than non-incubated firms. The policy recommendations from these finding are, therefore, to minimise the resources provided to incubators as they do not improve SMME performance. Resources should be provided to other SMME interventions such as providing growth capital directly to these firms.

In order to safely move through the environment, visually-guided animals use several types of visual cues for orientation. Optic flow provides faithful information about ego-motion and can thus be used to maintain a straight course. Additionally, local motion cues or landmarks indicate potentially interesting targets or signal danger, triggering approach or avoidance, respectively. The visual system must reliably and quickly evaluate these cues and integrate this information in order to orchestrate behavior. The underlying neuronal computations for this remain largely inaccessible in higher organisms, such as in humans, but can be studied experimentally in more simple model species. The fly Drosophila, for example, heavily relies on such visual cues during its impressive flight maneuvers. Additionally, it is genetically and physiologically accessible. Hence, it can be regarded as an ideal model organism for exploring neuronal computations during visual processing. In my PhD studies, I have designed and built several autonomous virtual reality setups to precisely measure visual behavior of walking flies. The setups run in open-loop and in closed-loop configuration. In an open-loop experiment, the visual stimulus is clearly defined and does not depend on the behavioral response. Hence, it allows mapping of how specific features of simple visual stimuli are translated into behavioral output, which can guide the creation of computational models of visual processing. In closedloop experiments, the behavioral response is fed back onto the visual stimulus, which permits characterization of the behavior under more realistic conditions and, thus, allows for testing of the predictive power of the computational models. In addition, Drosophila’s genetic toolbox provides various strategies for targeting and silencing specific neuron types, which helps identify which cells are needed for a specific behavior. We have focused on visual interneuron types T4 and T5 and assessed their role in visual orientation behavior. These neurons build up a retinotopic array and cover the whole visual field of the fly. They constitute major output elements from the medulla and have long been speculated to be involved in motion processing. This cumulative thesis consists of three published studies: In the first study, we silenced both T4 and T5 neurons together and found that such flies were completely blind to any kind of motion. In particular, these flies could not perform an optomotor response anymore, which means that they lost their normally innate following responses to motion of large-field moving patterns. This was an important finding as it ruled out the contribution of another system for motion vision-based behaviors. However, these flies were still able to fixate a black bar. We could show that this behavior is mediated by a T4/T5-independent flicker detection circuitry which exists in parallel to the motion system. In the second study, T4 and T5 neurons were characterized via twophoton imaging, revealing that these cells are directionally selective and have very similar temporal and orientation tuning properties to directionselective neurons in the lobula plate. T4 and T5 cells responded in a contrast polarity-specific manner: T4 neurons responded selectively to ON edge motion while T5 neurons responded only to OFF edge motion. When we blocked T4 neurons, behavioral responses to moving ON edges were more impaired than those to moving OFF edges and the opposite was true for the T5 block. Hence, these findings confirmed that the contrast polarityspecific visual motion pathways, which start at the level of L1 (ON) and L2 (OFF), are maintained within the medulla and that motion information is computed twice independently within each of these pathways. Finally, in the third study, we used the virtual reality setups to probe the performance of an artificial microcircuit. The system was equipped with a camera and spherical fisheye lens. Images were processed by an array of Reichardt detectors whose outputs were integrated in a similar way to what is found in the lobula plate of flies. We provided the system with several rotating natural environments and found that the fly-inspired artificial system could accurately predict the axes of rotation.

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Most of the commonly used antidepressants block monoamine reuptake transporters to enhance serotonergic or noradrenergic neurotransmission. Effects besides or downstream of increased monoaminergic neurotransmission are poorly understood and yet presumably important for the drugs’ mode of action. In my PhD thesis I employed proteomics and metabolomics technologies combined with in silico analyses and identified cellular pathways affected by antidepressant drug treatment. DBA/2 mice were treated with paroxetine as a representative Selective Serotonin Reuptake Inhibitor (SSRI). Hippocampal protein levels were compared between chronic paroxetine- and vehicle-treated animals using in vivo 15N metabolic labeling combined with mass spectrometry. I also studied chronic changes in the hippocampus using unbiased metabolite profiling and the time course of metabolic changes with the help of a targeted polar metabolomics profiling platform. I identified profound alterations related to hippocampal energy metabolism. Glycolytic metabolite levels acutely increased while Krebs cycle metabolite levels decreased upon chronic treatment. Changes in energy metabolism were influenced by altered glycogen metabolism rather than by altered glycolytic or Krebs cycle enzyme levels. Increased energy levels were reflected by an increased ATP/ADP ratio and by increased ratios of high-to-low energy purines and pyrimidines. Paralleling the shift towards aerobic glycolysis upon paroxetine treatment I identified decreased levels of Krebs cycle and oxidative phosphorylation enzyme levels upon the antidepressant-like 15N isotope effect in high-anxiety behavior mice. In the course of my analyses I also identified GABA, galactose-6-phosphate and leucine as biomarker candidates for the assessment of chronic paroxetine treatment effects in the periphery and myo-inositol as biomarker candidate for an early assessment of chronic treatment effects. The identified antidepressant drug treatment affected molecular pathways and novel SSRI modes of action warrant consideration in antidepressant drug development efforts.

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