|
Neuronal noise or neural noise refers to the random intrinsic electrical fluctuations within neuronal networks. These fluctuations are not associated with encoding a response to internal or external stimuli and can be from one to two orders of magnitude.〔Jacobson, G. A., et al. (2005). "Subthreshold voltage noise of rat neocortical pyramidal neurones." J Physiol 564(Pt 1): 145-160.〕 Most noise commonly occurs below a voltage-threshold that is needed for an action potential to occur, but sometimes it can be present in the form of an action potential; for example, stochastic oscillations in pacemaker neurons in suprachiasmatic nucleus are partially responsible for the organization of circadian rhythms.〔Ko, C. H., et al. (2010). "Emergence of Noise-Induced Oscillations in the Central Circadian Pacemaker." Plos Biology 8(10).〕〔Mazzoni, E. O., et al. (2005). "Circadian Pacemaker Neurons Transmit and Modulate Visual Information to Control a Rapid Behavioral Response." Neuron 45(2): 293-300.〕 ==Background== Neuronal noise begins at the microscopic level with atomic collisions and agitation.〔Destexhe, A. (2012). Neuronal noise. New York: Springer.〕 On the postsynaptic membrane, neural noise has been evident in the early stages of processing sight, smell, and hearing. The exact reason for neuronal noise relating to computational processing is still not currently understood, but a great deal of theories have been proposed. Single neurons demonstrate different responses to specific neuronal input signals. This is commonly referred to as neural response variability. If a specific input signal is initiated in the dendrites of a neuron, then a hypervariability exists in the number of vesicles released from the axon terminal fiber into the synapse.〔Stein, R. B., et al. (2005). "Neuronal variability: noise or part of the signal?" Nature Reviews Neuroscience 6(5): 389-397.〕 This characteristic is true for fibers without neural input signals, such as pacemaker neurons, as mentioned previously,〔 and cortical pyramidal neurons that have highly-irregular firing pattern.〔Softky, W. R. and C. Koch (1993). "The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs." J Neurosci 13(1): 334-350.〕 Noise generally hinders neural performance, but recent studies show, in dynamical non-linear neural networks, this statement does not always hold true. Non-linear neural networks are a network of complex neurons that have many connections with one another such as the neuronal systems found within our brains. Comparatively, linear networks are an experimental view of analyzing a neural system by placing neurons in series with each other. Initially, noise in complex computer circuit or neural circuits is thought to slow down〔McDonnell, Mark D., and Lawrence M. Ward. "The Benefits Of Noise In Neural Systems: Bridging Theory And Experiment." Nature Reviews Neuroscience 12.7 (2011): 415-426. Academic Search Complete. Web. 19 Nov. 2012.〕 and negatively affect the processing power. However, current research suggests that neuronal noise is beneficial to non-linear or complex neural networks up until optimal value.〔Parnas, B. R. (1996). "Noise and neuronal populations conspire to encode simple waveforms reliably." IEEE Trans Biomed Eng 43(3): 313-318.〕 A theory by Anderson and colleagues supports that neural noise is beneficial. Their theory suggests that noise produced in the visual cortex helps linearize or smooth the threshold of action potentials.〔Anderson, J. S., et al. (2000). "The contribution of noise to contrast invariance of orientation tuning in cat visual cortex." Science 290(5498): 1968-1972.〕 Another theory suggests that stochastic noise in a non-linear network shows a positive relationship between the interconnectivity and noise-like activity.〔Serletis, D., et al. (2011). "Complexity in neuronal noise depends on network interconnectivity." Ann Biomed Eng 39(6): 1768-1778.〕 Thus based on this theory, Patrick Wilken and colleagues suggest that neuronal noise is the principal factor that limits the capacity of visual short-term memory. Investigators of neural ensembles and those who especially support the theory of distributed processing, propose that large neuronal populations effectively decrease noise by averaging out the noise in individual neurons. Some investigators have shown in experiments and in models that neuronal noise is a possible mechanism to facilitate neuronal processing.〔http://www.rochester.edu/news/show.php?id=2683〕〔Ma, W.J., Beck, J., Latham, P. and Pouget, A., Bayesian inference with probabilistic population codes. Nature Neuroscience. 9(11), 1432-1438. 2006. http://www.bcs.rochester.edu/people/alex/pub/articles/MaBeckLathamPougetNN06.pdf〕 The presence of neuronal noise (or more specifically synaptic noise) confers to neurons more sensitivity to a broader range of inputs, it can equalize the efficacy of synaptic inputs located at different positions on the neuron, and it can also enable finer temporal discrimination.〔See the ("High-conductance state" ) article in Scholarpedia.〕 There are many theories of why noise is apparent in the neuronal networks, but many neurologists are unclear of why they exist. More generally, two types of impacts of neuronal noise can be distinguished: it will either add variability to the neural response, or more interestingly enable noise - induced dynamical phenomena which would not have been observed in a noise-free system. For instance, channel noise has been shown to induce oscillations in the stochastic Hodgkin-Huxley model. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Neuronal noise」の詳細全文を読む スポンサード リンク
|