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This research delves into simple Jerk-type dynamical networks, constructed using a specific bidirectional coupling scheme that influences the sub-oscillators and compound nonlinearity gradient functions that perturb each sub-unit of the network. The novelty of this work is to demonstrate a new pedagogical method able to stimulate the formation of higher-order multiscroll dynamics in the Jerk sub-oscillator. This is done by modeling a simple dynamic network built by applying a special bidirectional coupling between the Jerk sub-systems. Another novelty of this approach is that it allows us to study the collective dynamics of Jerk system networks, which has not yet been done in the literature. Multiscroll systems are exceedingly complex dynamically, making them valuable in chaos-based applications. The pedagogical approach used in this study is exceptional because it produces many additional equilibrium points (from 5 to 25 in dynamical network 1, and from 3 to 15 in dynamical network 2) in each Jerk sub-unit of the network. These equilibria elevate the complexity of Jerk systems by emulating higher-order multiscroll dynamics. The methodology used in this study is efficient and differs from those used in the literature, which mainly uses nonlinear multizero functions in dissipative systems. This research further explores the dynamic system characterization tools and conducts an experimental investigation on a microcontroller (ATMEGA2560) to confirm the predictions. [ABSTRACT FROM AUTHOR]

This study investigates the behavior of the Izhikevich discrete neuron model across various parameter configurations. Bifurcation diagrams and Lyapunov exponents are utilized to examine the impact of these parameters on the behavior of the system. The study specifically identifies important parameter ranges in which the attractor undergoes a sudden expansion, displaying characteristics of extreme events. Within the system, two distinct categories of extreme events can be identified: rare occurrences of small probability events located in the tail of the probability distribution and Dragon-King (DK) events, which possess a high probability amplitude. DK events are verified through the use of the DK test. The research concludes by examining the practical ramifications of these findings. The significance of forecasting and controlling extreme events in intricate systems is underscored, along with the cruciality of identifying their happening. [ABSTRACT FROM AUTHOR]

The influence of video games on the human brain has been a topic of extensive research and discussion. Video games, characterized by their dynamic and immersive qualities, have demonstrated the capacity to impact diverse cognitive processes. In this study, we conducted a detailed analysis of brain response variations to different genres of computer games, specifically focusing on boring, calm, horror, and funny games. To achieve this, we computed the sample entropy and approximate entropy of electroencephalograms (EEG) signals recorded from participants while they engaged with each type of game. Our findings revealed that EEG signals exhibited the highest complexity during the funny game and the lowest complexity during the calm game. This suggests that the brain is most active when playing the funny game and least active during the calm game. These results provide valuable insights into how different types of video game content can influence brain activity. The methodology employed in this study can be extended to explore brain activity under various conditions, potentially offering a broader understanding of how different stimuli impact cognitive processes. This approach can be useful in examining the effects of various interactive media on brain function and could inform the design of video games and other digital experiences to optimize cognitive engagement and mental well-being. [ABSTRACT FROM AUTHOR]

The examination of brain responses in individuals with a pornography addiction compared to those without sheds light on the neurobiological aspects associated with this behavior. Neuroscientific studies utilizing techniques such as electroencephalography (EEG) have shown that porn-addicted individuals may exhibit alterations in neural pathways related to reward processing and impulse control. In this paper, we analyzed the variations in the brain response of porn-addicted versus healthy individuals under five function tasks including baseline, emotional state, memorize task, executive task, and recall task. For this purpose, we analyzed the complexity of EEG signals using fractal theory, approximate entropy (ApEn), and sample entropy. The results showed that the EEG signals of porn-addicted teenagers are more complex than the ones for healthy individuals, which reflects a higher level of brain activity for porn-addicted teenagers. This method of analysis can be extended to examine the brain activity of other types of addiction versus healthy brains. [ABSTRACT FROM AUTHOR]