Bibliographic Details
| Title: |
Neuronal arithmetic. |
| Authors: |
Silver, R. Angus1 a.silver@ucl.ac.uk |
| Source: |
Nature Reviews Neuroscience. Jul2010, Vol. 11 Issue 7, p474-489. 16p. 1 Diagram, 1 Graph. |
| Subject Terms: |
*Brain -- Mathematical models, *Neural transmission, *Biological neural networks, *Arithmetic, *Neuroplasticity, *Brain research, *Brain physiology, *Neural physiology, *Dendritic cells, *Mathematics, *Neurophysiology, *Research funding |
| Abstract: |
The vast computational power of the brain has traditionally been viewed as arising from the complex connectivity of neural networks, in which an individual neuron acts as a simple linear summation and thresholding device. However, recent studies show that individual neurons utilize a wealth of nonlinear mechanisms to transform synaptic input into output firing. These mechanisms can arise from synaptic plasticity, synaptic noise, and somatic and dendritic conductances. This tool kit of nonlinear mechanisms confers considerable computational power on both morphologically simple and more complex neurons, enabling them to perform a range of arithmetic operations on signals encoded ina variety of different ways. [ABSTRACT FROM AUTHOR] |
| Database: |
Academic Search Index |