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Neuropercolation
Percolation (from the Latin word ''percolatio'', meaning filtration) is a theoretical model used to understand the way activation and diffusion of neural activity occurs within neural networks.Friedenbreg, J., Silverman, G. (2012). ''Cognitive Science: An Introduction to the Study of Mind'' (2nd Ed.). Thousand Oaks, CA: SAGE Publications. Percolation is a model used to explain how neural activity is transmitted across the various connections within the brain. Percolation theory can be easily understood by explaining its use in epidemiology. Individuals whom are infected with a disease can spread the disease through contact with others in their social network. Those who are more social and come into contact with more people will help to propagate the disease quicker than those who are less social. Factors such as occupation and sociability influence the rate of infection. Now, if one were to think of ''neurons'' as ''individuals'' and ''synaptic connections'' as the ''social bonds'' ...
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Neural Activity
Neurotransmission (Latin: ''transmissio'' "passage, crossing" from ''transmittere'' "send, let through") is the process by which signaling molecules called neurotransmitters are released by the axon terminal of a neuron (the presynaptic neuron), and bind to and react with the receptors on the dendrites of another neuron (the postsynaptic neuron) a short distance away. A similar process occurs in retrograde neurotransmission, where the dendrites of the postsynaptic neuron release retrograde neurotransmitters (e.g., endocannabinoids; synthesized in response to a rise in intracellular calcium levels) that signal through receptors that are located on the axon terminal of the presynaptic neuron, mainly at GABAergic and glutamatergic synapses. Neurotransmission is regulated by several different factors: the availability and rate-of-synthesis of the neurotransmitter, the release of that neurotransmitter, the baseline activity of the postsynaptic cell, the number of available postsynapti ...
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Neural Network
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting fro ...
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Percolation Theory
In statistical physics and mathematics, percolation theory describes the behavior of a network when nodes or links are added. This is a geometric type of phase transition, since at a critical fraction of addition the network of small, disconnected clusters merge into significantly larger connected, so-called spanning clusters. The applications of percolation theory to materials science and in many other disciplines are discussed here and in the articles network theory and percolation. Introduction A representative question (and the source of the name) is as follows. Assume that some liquid is poured on top of some porous material. Will the liquid be able to make its way from hole to hole and reach the bottom? This physical question is modelled mathematically as a three-dimensional network of vertices, usually called "sites", in which the edge or "bonds" between each two neighbors may be open (allowing the liquid through) with probability , or closed with probability , ...
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Epidemiology
Epidemiology is the study and analysis of the distribution (who, when, and where), patterns and determinants of health and disease conditions in a defined population. It is a cornerstone of public health, and shapes policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare. Epidemiologists help with study design, collection, and statistical analysis of data, amend interpretation and dissemination of results (including peer review and occasional systematic review). Epidemiology has helped develop methodology used in clinical research, public health studies, and, to a lesser extent, basic research in the biological sciences. Major areas of epidemiological study include disease causation, transmission, outbreak investigation, disease surveillance, environmental epidemiology, forensic epidemiology, occupational epidemiology, screening, biomonitoring, and comparisons of treatment effects such as in clinical t ...
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Social Network
A social network is a social structure made up of a set of social actors (such as individuals or organizations), sets of dyadic ties, and other social interactions between actors. The social network perspective provides a set of methods for analyzing the structure of whole social entities as well as a variety of theories explaining the patterns observed in these structures. The study of these structures uses social network analysis to identify local and global patterns, locate influential entities, and examine network dynamics. Social networks and the analysis of them is an inherently interdisciplinary academic field which emerged from social psychology, sociology, statistics, and graph theory. Georg Simmel authored early structural theories in sociology emphasizing the dynamics of triads and "web of group affiliations". Jacob Moreno is credited with developing the first sociograms in the 1930s to study interpersonal relationships. These approaches were mathematically fo ...
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Neuron
A neuron, neurone, or nerve cell is an electrically excitable cell that communicates with other cells via specialized connections called synapses. The neuron is the main component of nervous tissue in all animals except sponges and placozoa. Non-animals like plants and fungi do not have nerve cells. Neurons are typically classified into three types based on their function. Sensory neurons respond to stimuli such as touch, sound, or light that affect the cells of the sensory organs, and they send signals to the spinal cord or brain. Motor neurons receive signals from the brain and spinal cord to control everything from muscle contractions to glandular output. Interneurons connect neurons to other neurons within the same region of the brain or spinal cord. When multiple neurons are connected together, they form what is called a neural circuit. A typical neuron consists of a cell body ( soma), dendrites, and a single axon. The soma is a compact structure, and the axo ...
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Synaptic Plasticity
In neuroscience, synaptic plasticity is the ability of synapses to strengthen or weaken over time, in response to increases or decreases in their activity. Since memories are postulated to be represented by vastly interconnected neural circuits in the brain, synaptic plasticity is one of the important neurochemical foundations of learning and memory (''see Hebbian theory''). Plastic change often results from the alteration of the number of neurotransmitter receptors located on a synapse. There are several underlying mechanisms that cooperate to achieve synaptic plasticity, including changes in the quantity of neurotransmitters released into a synapse and changes in how effectively cells respond to those neurotransmitters. Synaptic plasticity in both excitatory and inhibitory synapses has been found to be dependent upon postsynaptic calcium release. Historical discoveries In 1973, Terje Lømo and Tim Bliss first described the now widely studied phenomenon of long-term potent ...
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Long-term Potentiation
In neuroscience, long-term potentiation (LTP) is a persistent strengthening of synapses based on recent patterns of activity. These are patterns of synaptic activity that produce a long-lasting increase in signal transmission between two neurons. The opposite of LTP is long-term depression, which produces a long-lasting decrease in synaptic strength. It is one of several phenomena underlying synaptic plasticity, the ability of chemical synapses to change their strength. As memories are thought to be encoded by modification of synaptic strength, LTP is widely considered one of the major cellular mechanisms that underlies learning and memory. LTP was discovered in the rabbit hippocampus by Terje Lømo in 1966 and has remained a popular subject of research since. Many modern LTP studies seek to better understand its basic biology, while others aim to draw a causal link between LTP and behavioral learning. Still, others try to develop methods, pharmacologic or otherwise, of enhanc ...
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Epilepsy
Epilepsy is a group of non-communicable neurological disorders characterized by recurrent epileptic seizures. Epileptic seizures can vary from brief and nearly undetectable periods to long periods of vigorous shaking due to abnormal electrical activity in the brain. These episodes can result in physical injuries, either directly such as broken bones or through causing accidents. In epilepsy, seizures tend to recur and may have no immediate underlying cause. Isolated seizures that are provoked by a specific cause such as poisoning are not deemed to represent epilepsy. People with epilepsy may be treated differently in various areas of the world and experience varying degrees of social stigma due to the alarming nature of their symptoms. The underlying mechanism of epileptic seizures is excessive and abnormal neuronal activity in the cortex of the brain which can be observed in the electroencephalogram (EEG) of an individual. The reason this occurs in most cases of epilepsy ...
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Disorganized Schizophrenia
Disorganized schizophrenia, or hebephrenia, was a subtype of schizophrenia prior to 2013. Subtypes of schizophrenia were no longer recognized as separate conditions in the '' DSM 5'', published in 2013. The disorder is no longer listed in the 11th revision of the International Classification of Diseases (ICD-11). Disorganized schizophrenia was classified within ICD-10 the existing classification, in practice, until January 1, 2022, as a mental and behavioural disorder, because the classification was thought to be an extreme expression of the ''disorganization syndrome'' that has been hypothesized to be one aspect of a three-factor model of symptoms in schizophrenia, the other factors being ''reality distortion'' (involving delusions and hallucinations) and ''psychomotor poverty'' (lack of speech, lack of spontaneous movement and various aspects of blunting of emotion). Presentation The condition is also known as hebephrenia, named after the Greek term for "adolescence" – '' ...
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Divergent Thinking
Divergent thinking is a thought process or method used to generate creative ideas by exploring many possible solutions. It typically occurs in a spontaneous, free-flowing, "non-linear" manner, such that many ideas are generated in an emergent cognitive fashion. Many possible solutions are explored in a short amount of time, and unexpected connections are drawn. Following divergent thinking, ideas and information are organized and structured using convergent thinking, which follows a particular set of logical steps to arrive at one solution, which in some cases is a "correct" solution. The psychologist J.P. Guilford first coined the terms convergent thinking and divergent thinking in 1956. Activities Activities which promote divergent thinking include creating lists of questions, setting aside time for thinking and meditation, brainstorming, subject mapping, bubble mapping, keeping a journal, playing tabletop role-playing games, creating artwork, and free writing. In free wri ...
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Small-world Network
A small-world network is a type of mathematical graph in which most nodes are not neighbors of one another, but the neighbors of any given node are likely to be neighbors of each other and most nodes can be reached from every other node by a small number of hops or steps. Specifically, a small-world network is defined to be a network where the typical distance ''L'' between two randomly chosen nodes (the number of steps required) grows proportionally to the logarithm of the number of nodes ''N'' in the network, that is: :L \propto \log N while the global clustering coefficient is not small. In the context of a social network, this results in the small world phenomenon of strangers being linked by a short chain of acquaintances. Many empirical graphs show the small-world effect, including social networks, wikis such as Wikipedia, gene networks, and even the underlying architecture of the Internet. It is the inspiration for many network-on-chip architectures in contemp ...
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