近似的,而不是完美的同步最大化了兴奋性神经元集合的下游有效性。

IF 2.3 4区 医学 Q1 Neuroscience Journal of Mathematical Neuroscience Pub Date : 2014-12-01 Epub Date: 2014-04-25 DOI:10.1186/2190-8567-4-10
Christoph Börgers, Jie Li, Nancy Kopell
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引用次数: 3

摘要

通常认为大脑中同步最基本的功能作用是放大兴奋性神经元信号。原因很简单:当正电荷在一段时间内注入到漏的目标神经元时,在动作电位在目标中被触发之前,一些正电荷会有时间漏出来,从这个意义上说,它会被浪费掉。如果目标是用尽可能少的装药引起目标的射击反应,那么似乎最好是一次发射所有的装药,即以完美的同步。在本文中,我们将证明,只有假设输入在目标越过触发阈值时停止,但在实际触发之前停止,这种推理才是正确的。如果稍后停止输入——例如,作为对发射目标触发的反馈信号的响应——“最经济”的输入方式(需要最少总输入量的方式)不再是精确同步的,而仅仅是近似同步的。如果目标是一个异构网络,就像它在大脑中一直存在的那样,那么“当目标越过触发阈值时”停止输入就不是一种选择,因为没有单一的时刻会越过触发阈值。从这个意义上说,精确的同步在大脑中从来都不是最佳的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Approximate, not Perfect Synchrony Maximizes the Downstream Effectiveness of Excitatory Neuronal Ensembles.

The most basic functional role commonly ascribed to synchrony in the brain is that of amplifying excitatory neuronal signals. The reasoning is straightforward: When positive charge is injected into a leaky target neuron over a time window of positive duration, some of it will have time to leak back out before an action potential is triggered in the target, and it will in that sense be wasted. If the goal is to elicit a firing response in the target using as little charge as possible, it seems best to deliver the charge all at once, i.e., in perfect synchrony. In this article, we show that this reasoning is correct only if one assumes that the input ceases when the target crosses the firing threshold, but before it actually fires. If the input ceases later-for instance, in response to a feedback signal triggered by the firing of the target-the "most economical" way of delivering input (the way that requires the least total amount of input) is no longer precisely synchronous, but merely approximately so. If the target is a heterogeneous network, as it always is in the brain, then ceasing the input "when the target crosses the firing threshold" is not an option, because there is no single moment when the firing threshold is crossed. In this sense, precise synchrony is never optimal in the brain.

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来源期刊
Journal of Mathematical Neuroscience
Journal of Mathematical Neuroscience Neuroscience-Neuroscience (miscellaneous)
自引率
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审稿时长
13 weeks
期刊介绍: The Journal of Mathematical Neuroscience (JMN) publishes research articles on the mathematical modeling and analysis of all areas of neuroscience, i.e., the study of the nervous system and its dysfunctions. The focus is on using mathematics as the primary tool for elucidating the fundamental mechanisms responsible for experimentally observed behaviours in neuroscience at all relevant scales, from the molecular world to that of cognition. The aim is to publish work that uses advanced mathematical techniques to illuminate these questions. It publishes full length original papers, rapid communications and review articles. Papers that combine theoretical results supported by convincing numerical experiments are especially encouraged. Papers that introduce and help develop those new pieces of mathematical theory which are likely to be relevant to future studies of the nervous system in general and the human brain in particular are also welcome.
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