Sharif Digital Repository

Recent studies of brain activities indicate that Phase-Amplitude Coupling (PAC) between several regions of the brain, are meaningfully related to Parkinson’s Disease. In this research, we have studied PAC as a statistical measure in Parkinsonian patients’ brains while Deep Brain Stimulation treatment with different stimulation frequencies are being applied. In order to do so, we have investigated patients’ brain signals, and estimated PAC between regions of interest; afterwards, by using the estimated PAC values, we have found significant effects of the treatments on parkinsonian brains; furthermore, two treatments that are using 130 Hz and 340 Hz stimuli signals are compared. In this... 

Considering that emigration has been one of the serious and popular issues in Iran during the past decades, the capacity of talents and non-resident elites, who are important pillars of the development of the country's knowledge-based economy, should not be overlooked. One of the best measures in order to achieve the long-term goals of the country's scientific perspective and to take advantage of the scientific reserves of Iranian scientists and specialists abroad is to increase return migration. However, the country does not have enough capacity to hire skilled and specialized labor abroad, Iran can become an entrepreneurial power plant for several reasons. Therefore, the entrepreneurial... 

The brain is one of the most critical parts of the body with a lot of complexity. The treatment of brain diseases has always been in an aura of uncertainty due to its high sensitivity. In the meantime, Parkinson's disease has become the second most frequent brain disease after Alzheimer's, involving more than two percent of the population over 65 years of age. One of the biggest questions in this field is how the Parkinson's process is formed. This question has already received much attention from the pathophysiological point of view but has not been answered from the functional and structural brain network's point of view. This research compares healthy macaque monkeys' functional and... 

Electroencephalogram (EEG) brain source localization carries many potential applications in systems and cognitive neuroscience, and for treatment of various neurological problems such as epilepsy. According to some recent studies, determining the spatial extent of sources and estimating their true time courses have proved challenging. This master's thesis proposes a method for localizing extended brain sources. Cortical surface parcellation has been used to reduce the dimension of the inverse problem without losing much information. The active regions are assumed to be sparse and the time course of the sources exhibits a correlation structure. The reduced dimension problem was then solved by... 

During the time that the simplest action (rest) of the human brain is active, and for integration and coordination of the brain, different parts of it are in connection with each other. This connection can be directional and directionless, which are called effective connectivity and functional connectivity, respectively. It is clear that effective connectivity shows brain function better than other connectivity due to its directionality.One of the most common ways to define effective connectivity is the use of the Multivariate Autoregressive (MVAR). The MVAR model provides the time Cause of different signals on each other, meaning that the influence of the past of a variable on other... 

The processing of brain signals, including the electrocorticogram (ECoG) signal, is widely used in the investigation of neurological diseases. Conventionally, the ECoG signal has frequency components up to the range of 80 Hz. Studies have proven that in some conditions, such as epilepsy, the brain signal includes frequency components higher than 80 Hz, which are called high-frequency oscillations (HFO). Therefore, HFOs are recognized as a biomarker for epilepsy. The aim of this thesis is to review the previous methods of detecting HFOs and to present new methods with greater efficiency in the direction of diagnosis or treatment of epileptic patients. For this purpose, we used the ECoG data... 

Emotions are one of the most important issues which affects daily life and activities. On the other hand, robots play an increasing role in human life and play a fundamental role in meeting our needs. One of these basic roles is empathy and verbal interaction between the robot and human. In this research, participant's emotions were stimulated in two ways: by using OASIS and GAPED image data sets and by instructing the participants to remind about their good or bad memories. During emotional stimulation, EEG signals have been recorded for the training and testing process. The preprocessing of training data includes filtering, removing bad parts of data, removing bad channels and... 

The brain is constantly anticipating the future of sensory inputs based on past experiences. When new sensory data is different from predictions shaped by recent trends, neural signals are generated to report this surprise. Surprise leads to garnering attention, causes arousal, and motivates engagement. It motivates the formation of an explanation or updating of current models. Three models have been proposed for quantifying surprise as the Shannon, Bayesian, and confidence-corrected surprises. In this thesis, we analyze EEG and MEG signals recorded during oddball tasks to examine and statistically compare the value of temporal/ spatial components in decoding the brain’s surprise. We... 

Alzheimer's disease is the most common type of dementia, which has been recognized as the seventh most common fatal disease in the elderly over 65 years of age. Despite all the research done to recognize and treat this disease, so far there is no cure for this disease, and even most of the chemical treatments that are prescribed for Alzheimer's patients are only effective towards reducing the symptoms of this disease and lose their effectiveness as it progresses. Therefore, in the last two decades, in order to find a way to better understand and even treat AD, scientists have reached a concept called brain frequency stimulation, which can improve people's cognitive performance without the... 

In most of brain studies, the primary objective is to find dipole activities, an underdetermined problem that requires additional constraints. Adequate constraints can be added by using information from other modalities. This research aims to develop a platform that combines various noninvasive modalities to improve localization accuracy. To accomplish this, two novel general approaches to combining modalities are proposed. In the first approach, the result of localizing by different methods and in different modalities are processed and combined in intervals by Dempster Shaffer's combination law. The final amount of bipolar activity is obtained by cumulating the activities obtained at... 

In recent years, due to the structural need of most medical data for graphic models such as the graphic model of patients and the loss of data correlation in previous methods, graphic methods have been designed and developed. On the other hand, with the growing presence of magnetic resonance imaging devices in various medical centers, a large amount of functional magnetic resonance images of healthy and sick people have become available to researchers. In this study, our goal is to use a new method in the field of graphic modeling so that we can extract functional connectivity graphs from functional magnetic resonance images and measure the performance of these graphs in different groups of... 

The human brain is one of the most complex and least understood systems in nature. In recent decades, numerous studies have been conducted to identify the behavior of this system. One of the areas of brain research is the investigation of the connections between different regions of the brain during a presumed process or in a resting state. Among various types of brain connections, effective connectivity provides researchers with higher-level information on brain behavior compared to other connections, but also entails greater computational complexity. In recent years, researchers have aimed to provide an estimator with the maximum desirable capabilities, and with the advent of (deep) neural... 

EEG brain signals have gained particular attention among researchers in the field of brain signal processing due to their easy and cheap recording, high temporal resolution, and non-invasiveness. On the other hand, defects such as high vulnerability to various types of noise and artifacts have caused the main challenge before processing them to improve the signal-to-noise ratio and the interpretability of brain connectivity obtained from them. In order to solve these challenges, two important problems of "separation of desired and undesired signal subspace" and "functional and effective connectivity analysis" have been raised, respectively. In solving both problems, EEG signals are usually... 

For more than two decades psychologists and sociologists have been warning about the damage of new social media. in the last decade, the neurological research has been developed to provide an empirical foundation to support the above hypothesis. Much of the research has focused on teenagers and young adults as the so-called digital native and as the largest number of social media users. They hold that a significant contribution to the adolescent trend plays a significant role in the tendency of individuals toward social media, thus increasing impulsive behavior. The three parts of the brain, namely the "social cognition network," the "self-referential cognition network" and the "reward... 

Nowadays, the brain drain problem has become a challenge for countries of origin (COO) and a blessing for countries hosting student migrants. This issue has been studied in many domestic and international types of research. These studies' results can lead to the ability to identify the causes and discover methods to solve this problem. For several decades, the human capital flight has been one of the most challenging educational-economic-social problems in Iran and has grown significantly in recent years. The waste of the country's resources, the ineffectiveness of the education provided to students to improve the country's condition and its construction, the social and psychological... 

In recent years, the subject of student mobility has become one of the most important areas of migration studies. The growing number of students moving from developing countries to developed ones has raised many concerns. Governments and institutions related to this issue have always tried to adopt policies to encourage the return of their diaspora students after graduation. However, to propose evidence-based policies there is a need to understand what shapes the intention of the Iranian international students to return or stay. This study tries to look at the factors that shape the intention of Iranian international students after graduation using the theory of planned behaviour.In the... 

Genetic differences among patients and cancer types result in different responses to treatments and care from patients. Using personalized medicine, treatments and care can be designed with the specific needs of the patient in mind. To achieve this goal, the informative characteristics of the patient and the disease should be quantified. Quantitative Imaging or Radiomics are concerned with the characterization and quantification of the phenotypical characteristics of the tumors from medical images. Developing handcrafted features is time-consuming and requires the 3D volume of the tumor to be segmented before extracting the features. The segmentation task is considered an open problem and... 

Despite the remarkable success of deep learning algorithms in recent years, it still has a long way to reach the status of human natural intelligence and to acquire the expected self-autonomy. As a result, many researchers in this field have focused on the development of these algorithms while taking inspiration from human cognitive behaviors. One of the disadvantages of current algorithms is the lack of their ability to learn in a continual manner while deployed in the environment. More precisely, deep learning models are not able to gradually gather knowledge from the environment and if they are in a situation of limited access to data, they will suffer from catastrophic forgetting; a... 

Depression is a type of mental disorder that is characterized by the continuous occurrence of bad moods in the affected person. Studies by the World Health Organization (WHO) show that depression is the second disease that threatens human life, and eight hundred thousand people die due to suicide every year. In order to reduce the damage caused by depression, it is necessary to have an accurate method for diagnosing depression and its rapid treatment, in which electroencephalogram (EEG) signals are considered as one of the best methods for diagnosing depression. Until now, various researches have been conducted to diagnose depression using electroencephalogram signals, most of which were... 

The use of protons and charged particles such as carbon in the treatment of cancerous tumors is one of the new methods of external radiation therapy. Proton therapy can achieve almost the same tumor dose coverage as traditional photon therapy with a greatly reduced dose to the normal organ. The radiation deviations caused by the magnetic field are an effective factor in reducing the dose of vital organs without sacrificing the dose coverage of tumors; Therefore, a new method of proton therapy, called magnetic field-modulated proton therapy, has been proposed, in which the Bragg peak positions of proton beams can be modulated under the cover of predesigned magnetic fields inside cancer...