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首页> 外文期刊>The Journal of Neuroscience: The Official Journal of the Society for Neuroscience >Self-organizing neural integrator predicts interval times through climbing activity.
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Self-organizing neural integrator predicts interval times through climbing activity.

机译：自组织神经积分器通过爬山活动预测间隔时间。

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摘要

Mammals can reliably predict the time of occurrence of an expected event after a predictive stimulus. Climbing activity is a prominent profile of neural activity observed in prefrontal cortex and other brain areas that is related to the anticipation of forthcoming events. Climbing activity might span intervals from hundreds of milliseconds to tens of seconds and has a number of properties that make it a plausible candidate for representing interval time. A biophysical model is presented that produces climbing, temporal integrator-like activity with variable slopes as observed empirically, through a single-cell positive feedback loop between firing rate, spike-driven Ca2+ influx, and Ca2+-activated inward currents. It is shown that the fine adjustment of this feedback loop might emerge in a self-organizing manner if the cell can use the variance in intracellular Ca2+ fluctuations as a learning signal. This self-organizing process is based on the present observation that the variance of the intracellularCa2+ concentration and the variance of the neural firing rate and of activity-dependent conductances reach a maximum as the biophysical parameters of a cell approach a configuration required for temporal integration. Thus, specific mechanisms are proposed for (1) how neurons might represent interval times of variable length and (2) how neurons could acquire the biophysical properties that enable them to work as timers.
机译：哺乳动物可以在预测性刺激后可靠地预测预期事件的发生时间。攀爬活动是在额叶前皮层和其他大脑区域观察到的神经活动的重要特征，与即将发生的事件有关。攀登活动可能跨越数百毫秒到数十秒的间隔，并且具有许多使之成为代表间隔时间的合理候选者的属性。提出了一种生物物理模型，该模型通过激发速率，尖峰驱动的Ca2 +内流和Ca2 +激活的内向电流之间的单细胞正反馈回路，产生凭经验观察到的具有变化斜率的攀登，类似时间积分器的活动。结果表明，如果细胞可以利用细胞内Ca2 +波动的变化作为学习信号，则该反馈回路的精细调整可能会以自组织的方式出现。这种自组织过程是基于目前的观察结果，即随着细胞的生物物理参数接近时间整合所需的构型，细胞内Ca2 +浓度的方差，神经放电速率和依赖于活性的电导的方差达到最大值。因此，提出了针对以下方面的特定机制：（1）神经元如何表示可变长度的间隔时间;（2）神经元如何获得使它们能够用作计时器的生物物理特性。

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