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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. [5] [6] The basic idea is that the nervous system needs to organize sensory data into an accurate internal model of the outside world.

  3. Voxel-based morphometry - Wikipedia

    en.wikipedia.org/wiki/Voxel-based_morphometry

    Voxel-based morphometry is a computational approach to neuroanatomy that measures differences in local concentrations of brain tissue, through a voxel-wise comparison of multiple brain images. [ 1 ] [ 2 ] In traditional morphometry , volume of the whole brain or its subparts is measured by drawing regions of interest (ROIs) on images from brain ...

  4. Brain simulation - Wikipedia

    en.wikipedia.org/wiki/Brain_simulation

    In the field of computational neuroscience, brain simulation is the concept of creating a functioning computer model of a brain or part of a brain. [1] Brain simulation projects intend to contribute to a complete understanding of the brain, and eventually also assist the process of treating and diagnosing brain diseases .

  5. Computational neuroscience - Wikipedia

    en.wikipedia.org/wiki/Computational_neuroscience

    Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematics, computer science, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.

  6. Neuromorphic computing - Wikipedia

    en.wikipedia.org/wiki/Neuromorphic_computing

    As early as 2006, researchers at Georgia Tech published a field programmable neural array. [13] This chip was the first in a line of increasingly complex arrays of floating gate transistors that allowed programmability of charge on the gates of MOSFETs to model the channel-ion characteristics of neurons in the brain and was one of the first cases of a silicon programmable array of neurons.

  7. Adaptive resonance theory - Wikipedia

    en.wikipedia.org/wiki/Adaptive_resonance_theory

    Adaptive resonance theory (ART) is a theory developed by Stephen Grossberg and Gail Carpenter on aspects of how the brain processes information.It describes a number of artificial neural network models which use supervised and unsupervised learning methods, and address problems such as pattern recognition and prediction.

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  9. Nervous system network models - Wikipedia

    en.wikipedia.org/wiki/Nervous_system_network_models

    This model is the Integrate-and-Fire (IF) model that was mentioned in Section 2.3. Closely related to IF model is a model called Spike Response Model (SRM) (Gerstner, W. (1995) [15] Pages 738-758) that is dependent on impulse function response convoluted with the input stimulus signal. This forms a base for a large number of models developed ...