Sharif Digital Repository

Parkinson’s disease (PD) is a progressive debilitating neurological disorder that causes motor and cognitive impairment. Administration of dopaminergic medication (Levodopa) has been reported to be effective in attenuating the excessive pathological synchronization in basal ganglia. However, long term levodopa therapy has its pitfalls. High frequency deep brain stimulation (DBS) has been suggested as an effective alternative for reducing motor symptoms in PD. In this method, distinct brain regions involved in the pathophysiology of the disease are stimulated electrically at high frequencies (i.e. at 130 Hz). While several studies have been carried out on the effects of DBS and its clinical... 

Learning is an essential mechanism for the survival of living things. There are different types of learning, and value learning is among the most important types. A child learns that water resolves the thirst need by repeatedly experiencing this situation. Eventually, the value of water, which has been valueless before that, increases gradually in his mind. How this concept is encoded in the brain? previous works reveal the role of different neurons and regions that are relevant to value learning. However, population analysis and dynamic modeling are less considered. Moreover, the links between different brain regions are unknown.Finding the relationship between two relevant regions of the... 

Perceptual memory used in novel vs familiar discrimination is not only vital for the evaluation of environmental variations but also essential for learning, perception, and correcting behavioral policies. On the other hand, value-based memory which allows for discrimination of valuable objects among equally familiar ones also drives behavioral interactions and decision making. Although many studies have been conducted to address the neuronal association regarding each separately, the neural correspondence between perceptual and value-based memory is not scrutinized adequately. To this end, the differential neural activation in two macaque monkeys to unrewarded novel vs familiar fractals (>100... 

Causal discovery is of utmost importance for agents who must plan and decide based on observations. Since mistaking correlation with causation might lead to un- wanted consequences. The gold standard to discover causal relation is to perform experiments. However, experiments are in many cases expensive, unethical or impossible to perform. In these situations, there is a need for observational causal discovery. Causal discovery in the observational data setting involves making significant assumptions on the data and on the underlying causal model. This thesis aims to alleviate some of the assumptions and tries to identify the causal relationships and causal mechanisms using generative neural... 

Nowadays, various policies are adopted by transportation managers and planners. These policies aim to improve system performance, reduce user costs, control and reduce air pollution, reduce noise pollution, and ultimately reduce congestion. A set of these policies in the form of transportation demand management is presented in the literature. A common way to find the effect of a policy on user behavior is to use questionnaires. Other causal inference models have been proposed in disciplines such as statistics, political science, marketing science, epidemiology, and psychology. The purpose of these models is to find the causal effect of an intervention (treatment) on a system. These studies...