No description available.

Networks are ubiquitous with several levels of complexity, configuration, hierarchy and function. Many micro- and macro-scale biological or non-biological interactions define complex systems. Our most sophisticated organ, the brain, accommodates the interaction of its billions of neurons through trillions of synapses and is a good example of a complex system. Network structure has been shown to be the key to determine network functions. For instance, communities or modules in the network explain functional segregation and modular interactions reveal functional integration. Moreover, the dynamics of cortical networks have been experimentally shown to be linked to the behavioral states of the animal. The level of rate and synchrony have been demonstrated to be related to sleep (inactive) and awake (active) states of animals. The structure of brain networks is not static. New synapses are formed and some existing synapses or neurons die due to neurodegenerative disease, environmental influences, development and learning, etc. Although there are many studies on the function of brain networks, the changes by neuronal and synaptic degeneration have not been so far in focus. In fact, there is no known mathematical model on the progressive pattern of synaptic pruning and neurodegeneration. The goal of this dissertation is to develop various models of progressive network degeneration and analyze their impact on structural and functional features of the networks. In order to expand the often chosen approach of the "random networks", the "small world" and "scale-free" network topologies are considered which have recently been proposed as alternatives. The effect of four progressive synaptic pruning strategies on the size of critical sites of brain networks and other complex networks is analyzed. Different measures are used to estimate the levels of population rate, regularity, synchrony and pair-wise correlation of neuronal networks. Our analysis reveals that the network degree, instead of network topology, highly affects the mean population activity. / <p>QC 20170906</p>

No description available.

During adolescence, the brain undergoes significant reorganization due to myelination and synaptic pruning. These changes are associated with risk-taking behaviors and the development of social relationships. Recent advancements in adolescent brain development can potentially enhance strategies for preventing and treating mental health disorders. This systematic review focuses on structural changes in the adolescent brain, specifically emphasizing a decrease in gray matter and an increase in white matter changes. Four longitudinal MRI studies were included in this systematic review to identify changes in brain volume among healthy adolescents with an age range of 10 to 19 years. The results revealed observable changes in gray and white matter volume in various brain regions during this period. A decrease in gray matter was observed in the frontal, temporal, and parietal cortex, and several subcortical regions. Contrary to our expectations, the amygdala displayed an increase in gray matter in early adolescence. We expected this findings to occur in late childhood. The results also indicated that males undergo more significant changes in the brain during this period than females. Considering the Social Process Network (SIPN) and triadic model, changes occurring in the frontal cortex and the amygdala could be linked to social behavior. While the changes in the thalamus, hippocampus, and amygdala may be linked to heightened risk-taking and mental health disorders. Further research is necessary to clarify the relationship between mental health disorders, behaviors, and developmental processes during adolescence.