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Network science. Hierarchical network models are iterative algorithms for creating networks which are able to reproduce the unique properties of the scale-free topology and the high clustering of the nodes at the same time. These characteristics are widely observed in nature, from biology to language to some social networks.
A biological network is a method of representing systems as complex sets of binary interactions or relations between various biological entities. [ 1 ] In general, networks or graphs are used to capture relationships between entities or objects. [ 1 ]
Behavioral neuroscience, also known as biological psychology, [1] biopsychology, or psychobiology, [2] is the application of the principles of biology to the study of physiological, genetic, and developmental mechanisms of behavior in humans and other animals. [3]
Biological applications of bifurcation theory provide a framework for understanding the behavior of biological networks modeled as dynamical systems. In the context of a biological system, bifurcation theory describes how small changes in an input parameter can cause a bifurcation or qualitative change in the behavior of the system.
In biology. In the context of biology, a neural network is a population of biological neurons chemically connected to each other by synapses. A given neuron can be connected to hundreds of thousands of synapses. [1] Each neuron sends and receives electrochemical signals called action potentials to its connected neighbors.
A neural network, also called a neuronal network, is an interconnected population of neurons (typically containing multiple neural circuits). [1] Biological neural networks are studied to understand the organization and functioning of nervous systems .
Global workspace theory (GWT) is a framework for thinking about consciousness proposed by cognitive scientists Bernard Baars and Stan Franklin in the late 1980s. [ 1 ] It was developed to qualitatively explain a large set of matched pairs of conscious and unconscious processes. GWT has been influential in modeling consciousness and higher-order ...
Biological network inference is the process of making inferences and predictions about biological networks. [1] By using these networks to analyze patterns in biological systems, such as food-webs, we can visualize the nature and strength of these interactions between species, DNA, proteins, and more. The analysis of biological networks with ...