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Technological addiction is a common issue worldwide that has seldomly been investigated; this research has developed a possible path model on further acknowledgment of the problematic use of technology. Present study (N = 211 Chinese adults) has investigated the relationships of parenting styles (PS), attachment style (AS), self-regulation, self-esteem and Smartphone addiction (SA). Results show that PS considerably predicts different types of AS. Secure and anxious AS was desirably predicted self-regulation and self-esteem. Under self-regulation, higher impulse control also successfully predicts less SA, while goal setting negatively predicted SA. The model helps explore new relationships between Smartphone addiction and other constructs in an educational psychology aspect. It also helps gain insight on how parenting and selfregulation influences Smartphone usage. Programs which promote parenting skills and correct regulating skills are suggested.

Brain–computer interfaces (BCIs) can be used in real-time fMRI neurofeedback (rtfMRI NF) investigations to provide feedback on brain activity to enable voluntary regulation of the blood-oxygen-level dependent (BOLD) signal from localized brain regions. However, the temporal pattern of successful self-regulation is dynamic and complex. In particular, the general linear model (GLM) assumes fixed temporal model functions and misses other dynamics. We propose a novel data-driven analyses approach for rtfMRI NF using intersubject covariance (ISC) analysis. The potential of ISC was examined in a reanalysis of data from 21 healthy individuals and nine patients with post-traumatic stress-disorder (PTSD) performing up-regulation of the anterior cingulate cortex (ACC). ISC in the PTSD group differed from healthy controls in a network including the right inferior frontal gyrus (IFG). In both cohorts, ISC decreased throughout the experiment indicating the development of individual regulation strategies. ISC analyses are a promising approach to reveal novel information on the mechanisms involved in voluntary self-regulation of brain signals and thus extend the results from GLM-based methods. ISC enables a novel set of research questions that can guide future neurofeedback and neuroimaging investigations.

We present a model of a three-step food chain. Population A grows at a certain rate and at another rate is eaten by the population B which has its own birth rate but is, in turn, eaten at a different rate by the population C. The dynamics of the model is given by a set of differential equations and via Monte Carlo simulations. Our system undergoes sudden cataclysms in the form of partial destruction of one of the populations. We show that there exist threshold values for the possible percentage of destroyed populations, above which the system returns to its previous state, thus showing a self-regulatory character.