Time-warp-invariant neuronal processing.
Time-warp-invariant neuronal processing.
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DOI：
10.1371/journal.pbio.1000141
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发表时间：
2009-07
期刊：
影响因子：
9.8
通讯作者：
Sompolinsky H
中科院分区：
文献类型：
--
作者：
Gütig R;Sompolinsky H
听觉神经元中的生物物理机制允许大脑以时间扭曲不变的方式处理自然语音中的说话速率的高度可变性。感觉信号的持续时间的波动构成了自然刺激合奏内的可变性的主要来源。感觉系统通过神经元机制来稳定感知，对抗这种波动，这在很大程度上是未知的。这种鲁棒性的一个有趣的实例发生在人类的语音感知中，它严重依赖于嵌入在具有高度可变持续时间的信号中的时间声学线索。在自然语音的不同实例中，听觉线索可以经历范围从2倍压缩到2倍膨胀的时间扭曲，而没有显著的感知损害。在这里，我们报告说，时间弯曲不变的神经元处理可以subserved的分流作用的突触电导，自动重新缩放的有效整合时间的突触后神经元。我们提出了一种新的基于尖峰的突触电导的学习规则，该规则根据给定任务的时间处理要求调整突触分流的程度。应用这种一般的生物物理机制的语音处理的例子，我们提出了一个神经网络模型的时间弯曲不变的单词歧视，并证明其出色的性能在一个标准的基准语音识别任务。我们的研究结果表明，突触电导的重要功能作用，在尖峰为基础的神经元信息处理和学习。在神经元膜上的时间整合的生物物理学可以赋予感觉通路强大的时间扭曲不变的计算能力。大脑具有强大的处理感官刺激的能力，即使这些刺激在时间上是扭曲的。这种感知鲁棒性的最突出的例子发生在语音通信中。说话者之间的语速变化很大，但我们对单词的感知却保持稳定。几十年来，神经元的机制一直困扰着神经科学家，它既能使时间弯曲不变性，又不损害我们区分精细时间线索的能力。在这里，我们描述了一个细胞的过程，听觉神经元重新校准，在飞行中，他们的知觉时钟，并允许他们有效地纠正传入的感觉事件的速率的时间波动。我们证明了这种基本的生物物理机制允许简单的神经架构以近乎完美的性能解决标准的基准语音识别任务。这种提出的时间弯曲不变的神经处理机制导致了关于语音感知病理起源的新假设。
A biophysical mechanism acting in auditory neurons allows the brain to process the high variability of speaking rates in natural speech in a time-warp-invariant manner. Fluctuations in the temporal durations of sensory signals constitute a major source of variability within natural stimulus ensembles. The neuronal mechanisms through which sensory systems can stabilize perception against such fluctuations are largely unknown. An intriguing instantiation of such robustness occurs in human speech perception, which relies critically on temporal acoustic cues that are embedded in signals with highly variable duration. Across different instances of natural speech, auditory cues can undergo temporal warping that ranges from 2-fold compression to 2-fold dilation without significant perceptual impairment. Here, we report that time-warp–invariant neuronal processing can be subserved by the shunting action of synaptic conductances that automatically rescales the effective integration time of postsynaptic neurons. We propose a novel spike-based learning rule for synaptic conductances that adjusts the degree of synaptic shunting to the temporal processing requirements of a given task. Applying this general biophysical mechanism to the example of speech processing, we propose a neuronal network model for time-warp–invariant word discrimination and demonstrate its excellent performance on a standard benchmark speech-recognition task. Our results demonstrate the important functional role of synaptic conductances in spike-based neuronal information processing and learning. The biophysics of temporal integration at neuronal membranes can endow sensory pathways with powerful time-warp–invariant computational capabilities. The brain has a robust ability to process sensory stimuli, even when those stimuli are warped in time. The most prominent example of such perceptual robustness occurs in speech communication. Rates of speech can be highly variable both within and across speakers, yet our perceptions of words remain stable. The neuronal mechanisms that subserve invariance to time warping without compromising our ability to discriminate between fine temporal cues have puzzled neuroscientists for several decades. Here, we describe a cellular process whereby auditory neurons recalibrate, on the fly, their perceptual clocks and allows them effectively to correct for temporal fluctuations in the rate of incoming sensory events. We demonstrate that this basic biophysical mechanism allows simple neural architectures to solve a standard benchmark speech-recognition task with near perfect performance. This proposed mechanism for time-warp–invariant neural processing leads to novel hypotheses about the origin of speech perception pathologies.
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