Neuroscience
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Recent studies using genomic and functional approaches in the fruit fly Drosophila melanogaster have revealed the effects of viral infection on nervous system homeostasis. An established connection between viral infection and brain function is critical due to its significant contribution to several areas of biomedical research, particularly the molecular pathogenesis of neurotropic viruses, the neurobiology of viral disease, and understanding the genetic basis and pathophysiology of viral tropism.
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A new method for analyzing brain complex dynamics and states is presented. This method constructs functional brain graphs and is comprised of two pylons: (a) Operational architectonics (OA) concept of brain and mind functioning. (b) Network neuroscience. In particular, the algorithm utilizes OA framework for a non-parametric segmentation of EEG signals, which leads to the identification of change points, namely abrupt jumps in EEG amplitude, called Rapid Transition Processes (RTPs). ⋯ The classification results, based on a Naïve Bayes classifier, show that the overall accuracies were found to be above chance level in all tested cases. This method was also compared with other state-of-the-art computational approaches commonly used for functional network generation, exhibiting competitive performance. The method can be useful to neuroscientists wishing to enhance their repository of brain research algorithms.