There is an abundance of literature on complex networks describing a variety of relationships among units in social, biological, and technological systems. Such networks, consisting of interconnected nodes, are often self-organized, naturally emerging without any overarching designs on topological structure yet enabling efficient interactions among nodes. Here we show that the number of nodes and the density of connections in such self-organized networks exhibit a power law relationship. We examined the size and connection density of 47 self-organizing networks of various biological, social, and technological origins, and found that the size-density relationship follows a fractal relationship spanning over 6 orders of magnitude. This finding indicates that there is an optimal connection density in self-organized networks following fractal scaling regardless of their sizes.
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http://dx.doi.org/10.1016/j.physa.2011.05.011 | DOI Listing |
Humans excel at applying learned behavior to unlearned situations. A crucial component of this generalization behavior is our ability to compose/decompose a whole into reusable parts, an attribute known as compositionality. One of the fundamental questions in robotics concerns this characteristic: How can linguistic compositionality be developed concomitantly with sensorimotor skills through associative learning, particularly when individuals only learn partial linguistic compositions and their corresponding sensorimotor patterns? To address this question, we propose a brain-inspired neural network model that integrates vision, proprioception, and language into a framework of predictive coding and active inference on the basis of the free-energy principle.
View Article and Find Full Text PDFJ R Soc Interface
January 2025
Department of Information Technology, Uppsala University, Uppsala, Sweden.
Building mathematical models of brains is difficult because of the sheer complexity of the problem. One potential starting point is basal cognition, which gives an abstract representation of a range of organisms without central nervous systems, including fungi, slime moulds and bacteria. We propose one such model, demonstrating how a combination of oscillatory and current-based reinforcement processes can be used to couple resources in an efficient manner, mimicking the way these organisms function.
View Article and Find Full Text PDFNano Lett
January 2025
National Laboratory of Solid States Microstructures, School of Physics, Nanjing University, Nanjing 210093, People's Republic of China.
While the highest-performing memristors currently available offer superior storage density and energy efficiency, their large-scale integration is hindered by the random distribution of filaments and nonuniform resistive switching in memory cells. Here, we demonstrate the self-organized synthesis of a type of two-dimensional protonic coordination polymers with high crystallinity and porosity. Hydrogen-bond networks containing proton carriers along its nanochannels enable uniform resistive switching down to the subnanoscale range.
View Article and Find Full Text PDFZh Nevrol Psikhiatr Im S S Korsakova
January 2025
Pirogov Russian National Research Medical University (Pirogov University), Moscow, Russia.
Stroke is the main cause of disability among neurological diseases. There are questions of the accuracy of topical diagnosis and rehabilitation prognosis in clinical practice. Answers to these questions may be given by an approach to the study of the nervous system as a dynamic network consisting of a set of brain regions with anatomical and functional connections between them.
View Article and Find Full Text PDFThe reaction-diffusion (RD) system is widely assumed to account for many complex, self- organized pigmentation patterns in natural organisms. However, the specific configurations of such RD networks and how RD systems interact with positional information (i.e.
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