A Fast and Simple Population Code for Orientation in Primate V1
A Fast and Simple Population Code for Orientation in Primate V1
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DOI：
10.1523/jneurosci.1335-12.2012
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发表时间：
2012-08-01
影响因子：
5.3
通讯作者：
Tolias, Andreas S.
中科院分区：
文献类型：
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作者：
Berens, Philipp;Ecker, Alexander S.;Tolias, Andreas S.
取向调整一直是了解新皮层中单神经元计算的经典模型。但是，关于如何从神经种群的活动（尤其是在警报动物的活动中）读取方向知之甚少。我们的研究是朝着这一目标迈出的第一步。我们同时在警报猕猴的主要视觉皮层中从多达20个孤立的单个神经元录制，并应用了一个简单的，神经合理的解码器来读取人口代码。我们关注两个问题：首先，可以从人口响应中读取方向的时间课程和时间表？其次，下游神经元中的解码机制必须可靠地区分不同方向的视觉刺激？我们表明，在醒目猕猴的主要视觉皮层中的神经合奏代表取向取向，以促进快速而简单的读出机制：平均潜伏期为30-80毫秒，可以在短时间内逐步读取人口代码。仅需要考虑几十毫秒，并且不需要考虑刺激对比度和相关性来计算最佳的突触体重模式。我们的研究表明，与单神经元计算的情况相似 - 在神经种群的尖峰模式中表示方向可以作为理解行为过程中基础视觉处理的神经结合物执行的计算的模范情况。
Orientation tuning has been a classic model for understanding single-neuron computation in the neocortex. However, little is known about how orientation can be read out from the activity of neural populations, in particular in alert animals. Our study is a first step toward that goal. We recorded from up to 20 well isolated single neurons in the primary visual cortex of alert macaques simultaneously and applied a simple, neurally plausible decoder to read out the population code. We focus on two questions: First, what are the time course and the timescale at which orientation can be read out from the population response? Second, how complex does the decoding mechanism in a downstream neuron have to be to reliably discriminate between visual stimuli with different orientations? We show that the neural ensembles in primary visual cortex of awake macaques represent orientation in a way that facilitates a fast and simple readout mechanism: With an average latency of 30-80 ms, the population code can be read out instantaneously with a short integration time of only tens of milliseconds, and neither stimulus contrast nor correlations need to be taken into account to compute the optimal synaptic weight pattern. Our study shows that-similar to the case of single-neuron computation-the representation of orientation in the spike patterns of neural populations can serve as an exemplary case for understanding the computations performed by neural ensembles underlying visual processing during behavior.