Extracting Information: Characterizing neuronal cell types in the GPh by their activity profile.
نویسندگان
چکیده
منابع مشابه
Extracting Material Information from the CT Numbers by Artificial Neural Networks for Use in the Monte Carlo Simulations of Different Tissue Types in Brachytherapy
Background: The artificial neural networks (ANNs) are useful in solving nonlinear processes, without the need for mathematical models of the parameters. Since the relationship between the CT numbers and material compositions is not linear, ANN can be used for obtaining tissue density and composition.Objective: The aim of this study is to utilize ANN for determination of the composition and mass...
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Identifying the functionally distinct types of neuron is central to any bottom-up understanding of how the brain works. The different cell types are the brain’s elementary computational elements — the components from which the larger machine is made. We have known of some cell types for more than a century, but the coverage has been spotty and anecdotal. This is changing: it is now possible to ...
متن کاملextracting material information from the ct numbers by artificial neural networks for use in the monte carlo simulations of different tissue types in brachytherapy
background: the artificial neural networks (anns) are useful in solving nonlinear processes, without the need for mathematical models of the parameters. since the relationship between the ct numbers and material compositions is not linear, ann can be used for obtaining tissue density and composition. objective: the aim of this study is to utilize ann for determination of the composition and mas...
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Over the past 25 years, there have been two opposing views of how taste information is represented in the activity of gustatory neurons. One view, the across-fiber pattern (AFP) theory, postulates that taste quality is represented by the pattern of activity across the afferent population. Stimuli with similar tastes produce similar patterns of activity. The other view is that activity in a few ...
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Cortical neurons behave similarly to stochastic processes, as a consequence of their irregularity and dense connectivity. Their firing pattern is close to a Poisson process, and their membrane potential (V(m)) is analogous to colored noise. One way to characterize this activity is to identify V(m) to a multidimensional stochastic process. We review here this approach and how it can be used to e...
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ژورنال
عنوان ژورنال: Berkeley Scientific Journal
سال: 2015
ISSN: 2373-8146,1097-0967
DOI: 10.5070/bs3201030259