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  2. Bayesian approaches to brain function - Wikipedia

    en.wikipedia.org/wiki/Bayesian_approaches_to...

    As early as the 1860s, with the work of Hermann Helmholtz in experimental psychology, the brain's ability to extract perceptual information from sensory data was modeled in terms of probabilistic estimation. The basic idea is that the nervous system needs to organize sensory data into an accurate internal model of the outside world.

  3. Graphical model - Wikipedia

    en.wikipedia.org/wiki/Graphical_model

    A graphical model or probabilistic graphical model ( PGM) or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random variables. They are commonly used in probability theory, statistics —particularly Bayesian statistics —and machine learning .

  4. Bayesian network - Wikipedia

    en.wikipedia.org/wiki/Bayesian_network

    v. t. e. A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). [1] While it is one of several forms of causal notation, causal networks are special cases of ...

  5. Bayesian inference - Wikipedia

    en.wikipedia.org/wiki/Bayesian_inference

    v. t. e. Bayesian inference ( / ˈbeɪziən / BAY-zee-ən or / ˈbeɪʒən / BAY-zhən) [1] is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Fundamentally, Bayesian inference uses prior knowledge, in the form of a prior distribution ...

  6. Erdős–Rényi model - Wikipedia

    en.wikipedia.org/wiki/Erdős–Rényi_model

    Category:Graph theory. v. t. e. In the mathematical field of graph theory, the Erdős–Rényi model refers to one of two closely related models for generating random graphs or the evolution of a random network. These models are named after Hungarian mathematicians Paul Erdős and Alfréd Rényi, who introduced one of the models in 1959.

  7. Neural oscillation - Wikipedia

    en.wikipedia.org/wiki/Neural_oscillation

    The bottom neuron is not oscillating. [2] Neural oscillations, or brainwaves, are rhythmic or repetitive patterns of neural activity in the central nervous system. Neural tissue can generate oscillatory activity in many ways, driven either by mechanisms within individual neurons or by interactions between neurons.

  8. Hopfield network - Wikipedia

    en.wikipedia.org/wiki/Hopfield_network

    Hopfield network. A Hopfield network ( associative memory or Ising–Lenz–Little model or Nakano-Amari-Hopfield network) is a spin glass system used to model neural networks, based on Ernst Ising 's work with Wilhelm Lenz on the Ising model of magnetic materials. [ 1 ]

  9. Biological neuron model - Wikipedia

    en.wikipedia.org/wiki/Biological_neuron_model

    Biological neuron model. Fig. 1. Neuron and myelinated axon, with signal flow from inputs at dendrites to outputs at axon terminals. The signal is a short electrical pulse called action potential or 'spike'. Fig 2. Time course of neuronal action potential ("spike").

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