Computational Neuroscience: A Comprehensive Approach (Chapman & Hall/CRC Mathematical and Computational Biology)
Language: English
Pages: 656
ISBN: B000Q36EME
Format: PDF / Kindle (mobi) / ePub
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Are less important, and the average charge density is good enough. However, this remains to be determined in specific cases. 2.2.3 Brownian dynamics A different approach, that maintains some of the benefits of atomistic simulation, is provided by Brownian dynamics (BD). In BD, typically ions and the ion channel are represented explicitly whereas solvent and lipids are represented implicitly (see also Figure 2.3). In these simulations, ions move stochastically in a potential that is a combination.
Selectivities? Third, why is the channel not more selective for anions, even with 8 charged lysines pointing into the channel? To address these questions a number of computer simulations of the system has been performed, of 10 ns each of the octameric bundle in a lipid bilayer environment, with either 0, 4, or 8 lysines charged in the absence of salt, and with 8 lysines charged in the presence of 0.5 M or 1 M KCl. Without salt present and with all lysines charged, on average 1.9 Cl− ions are.
Spatial distribution of clusters of voltage-gated calcium channels on vesicle release was explored. In this model, vesicles at different locations are exposed to different calcium concentrations resulting in different release probabilities. The authors suggest that this spatially heterogeneous release probability has functional advantages for synaptic transmission. A third model of calcium dynamics in the synapse of the frog saccular hair cell has been proposed by Roberts [40, 41]. In this model,.
Define transition probabilities pi j (t) by pi j (t) = P(X(t) = j|X(0) = i) Then by the total probability theorem, if we consider the situation at times t and t + ∆t, pi j (t + ∆t) = ∑ pik (t)Prob(X(t + ∆t) = j|X(0) = i and X(t) = k) k But the Markov property implies that the condition in the second factor of this expression can be replaced by the condition X(t) = k only (the most recent thing known) so that we have, approximately, pi j (t + ∆t) = ∑ pik (t)qk j ∆t + pi j (t){1 + q j j ∆t} k= j.
The power spectrum is a sum of Lorentzian components. Almost always, though, for actual channels, the power of one or two of these components is dominant. For example, Figure 6.3 shows the noise through NMDA receptor channels at a single synapse [47]. The power of the lower frequency component is more than ten times that of the higher frequency component. Roughly speaking, this first component corresponds to the correlation due to the mean open lifetime of channels or predominant burst lifetime.