Synaptic “noise”: Experiments, computational consequences and methods to analyze experimental data
نویسندگان
چکیده
In the cerebral cortex of awake animals, neurons are subject to a tremendous fluctuating activity mostly of synaptic origin and termed “synaptic noise”. Synaptic noise is the dominant source of membrane potential fluctuations in neurons and can have a strong influence on their integrative properties. We review here the experimental measurements of synaptic noise, and its modeling by conductance-based stochastic processes. We next review the consequences of synaptic noise on neuronal integrative properties, as predicted by computational models and investigated experimentally using dynamic-clamp. We also review analysis methods, such as spike-triggered average or conductance analysis, which are derived from the modeling of synaptic noise by stochastic processes. These different approaches aim at understanding the integrative properties of neocortical neurons in the intact brain.
منابع مشابه
Contributions of computational neuroscience to the exploration of the effect of background activity on central neurons
The central nervous system is subject to many different sources of noise, which have fascinated researchers since the beginning of electrophysiological recordings. In cerebral cortex, the largest amplitude noise source is the “synaptic noise”, which is dominant in intracellular recordings in vivo. The consequences of this background activity is a classic theme of modeling studies. In the last 2...
متن کاملInferring network activity from synaptic noise.
During intense network activity in vivo, cortical neurons are in a high-conductance state, in which the membrane potential (V(m)) is subject to a tremendous fluctuating activity. Clearly, this "synaptic noise" contains information about the activity of the network, but there are presently no methods available to extract this information. We focus here on this problem from a computational neuros...
متن کاملSilent Synapses, LTP, and the Indirect Parallel-Fibre Pathway: Computational Consequences of Optimal Cerebellar Noise-Processing
Computational analysis of neural systems is at its most useful when it uncovers principles that provide a unified account of phenomena across multiple scales and levels of description. Here we analyse a widely used model of the cerebellar contribution to sensori-motor learning to demonstrate both that its response to intrinsic and sensor noise is optimal, and that the unexpected synaptic and be...
متن کاملNoise pollution analysis in Tehran cement plant
Background : Cement industry has many process units. Basically all of these units can be considered as a source of noise. Since noise pollution is defined based on its offensive hearing effects, the importance of the noise sources depends directly on the number of workers in the unit. Materials and Methods : An experimental study has been done at Tehran cement factory to recogn...
متن کاملComputational Models Reduce Complexity and Accelerate Insight Into Cardiac Signaling Networks Alternans and Arrhythmias: From Cells to the Heart Whole Heart Modeling: Applications to Cardiac Electrophysiology and Electromechanics
Cardiac signaling networks exhibit considerable complexity in size and connectivity. The intrinsic complexity of these networks complicates the interpretation of experimental findings. This motivates new methods for investigating the mechanisms regulating cardiac signaling networks and the consequences these networks have on cardiac physiology and disease. Next-generation experimental technique...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2008