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Variance-mean analysis: a simple and reliable approach for investigating synaptic transmission and modulation.

机译:方差均值分析:一种简单可靠的方法,用于研究突触传递和调制。

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The mechanisms underlying synaptic plasticity can be investigated by analyzing synaptic amplitude fluctuations before and after a synaptic modulation. However, many older fluctuation analysis techniques rely on models of synaptic transmission that incorporate unrealistic simplifying assumptions or have too many free parameters. As a result, these techniques have sometimes produced counterintuitive or contradictory results. In contrast, the variance-mean (V-M) technique requires fewer assumptions and is more robust than previous approaches. It achieves these improvements by focusing on two key parameters of synaptic transmission, the average probability that a vesicle is released from a synaptic terminal following a presynaptic stimulus (P(av)), and the average amplitude of the postsynaptic response to a vesicle of transmitter (Q(av)). To apply V-M analysis, a fluctuating postsynaptic current (PSC) is recorded at several different extracellular Ca(2+) or Cd(2+) concentrations. The variance of the PSC amplitude is plotted against the mean amplitude at each concentration, forming a parabola. The degree of parabolic curvature estimates P(av), and the limiting slope under low release conditions estimates Q(av). The shape of the V-M parabola changes in characteristic ways following each of the three standard forms of synaptic modulation: a change in Q(av) (postsynaptic), a change in P(av) (presynaptic), or a change in the number of terminals (N). The approach does not require specialized software, and can even be implemented as a purely graphical technique. V-M analysis has been used to investigate the site of expression of long-term potentiation and the mechanisms underlying paired-pulse depression. This report presents a detailed mathematical development of the technique, and explores the limiting conditions under which it can confidently be applied. V-M analysis requires fewer than 100 PSC amplitude measurements to accurately estimate P(av) and Q(av), and it can reliably identify whether a synaptic modulation occurs at a pre- or postsynaptic site. In contrast to other techniques, V-M analysis is largely insensitive to recording noise, nonuniform modulation and intrinsic variability of the unitary synaptic amplitude.
机译:可以通过分析突触调制前后的突触幅度波动来研究突触可塑性的潜在机制。但是,许多较旧的波动分析技术都依赖于突触传递模型,这些模型包含不现实的简化假设或自由参数过多。结果,这些技术有时会产生违反直觉或矛盾的结果。相比之下,方差均值(V-M)技术所需的假设更少,并且比以前的方法更可靠。它通过关注突触传递的两个关键参数,突触前刺激(P(av))后从突触末端释放囊泡的平均概率以及突触后对递质囊泡的平均振幅来实现这些改进。 (Q(av))。要应用V-M分析,在几种不同的细胞外Ca(2+)或Cd(2+)浓度下记录波动的突触后电流(PSC)。将PSC振幅的方差相对于每种浓度下的平均振幅作图,形成抛物线。抛物线曲率的程度估计为P(av),低释放条件下的极限斜率估计为Q(av)。 VM抛物线的形状按照三种标准形式的突触调制中的每一种以特征性方式变化:Q(av)的变化(突触后),P(av)的变化(突触前)或突触数的变化。端子(N)。该方法不需要专门的软件,甚至可以实现为纯图形技术。 V-M分析已用于研究长期增强表达的位点和成对脉冲抑制的机制。该报告介绍了该技术的详细数学发展,并探讨了可以放心地应用该技术的限制条件。 V-M分析需要少于100个PSC幅度测量值才能准确估计P(av)和Q(av),并且它可以可靠地识别突触调制是发生在突触前还是突触后。与其他技术相比,V-M分析对记录噪声,非均匀调制和单一突触幅度的固有变化不敏感。

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