Laboratoire Psychologie de la Perception, CNRS and Université Paris Descartes, Sorbonne Paris Cité, Paris, France.
PLoS Comput Biol. 2012;8(6):e1002561. doi: 10.1371/journal.pcbi.1002561. Epub 2012 Jun 14.
Neurons communicate primarily with spikes, but most theories of neural computation are based on firing rates. Yet, many experimental observations suggest that the temporal coordination of spikes plays a role in sensory processing. Among potential spike-based codes, synchrony appears as a good candidate because neural firing and plasticity are sensitive to fine input correlations. However, it is unclear what role synchrony may play in neural computation, and what functional advantage it may provide. With a theoretical approach, I show that the computational interest of neural synchrony appears when neurons have heterogeneous properties. In this context, the relationship between stimuli and neural synchrony is captured by the concept of synchrony receptive field, the set of stimuli which induce synchronous responses in a group of neurons. In a heterogeneous neural population, it appears that synchrony patterns represent structure or sensory invariants in stimuli, which can then be detected by postsynaptic neurons. The required neural circuitry can spontaneously emerge with spike-timing-dependent plasticity. Using examples in different sensory modalities, I show that this allows simple neural circuits to extract relevant information from realistic sensory stimuli, for example to identify a fluctuating odor in the presence of distractors. This theory of synchrony-based computation shows that relative spike timing may indeed have computational relevance, and suggests new types of neural network models for sensory processing with appealing computational properties.
神经元主要通过尖峰（spikes）进行交流，但大多数神经计算理论都是基于发放率（firing rates）的。然而，许多实验观察表明，尖峰的时间协调在感觉处理中起着作用。在潜在的基于尖峰的编码中，同步似乎是一个很好的候选者，因为神经发放和可塑性对精细的输入相关性敏感。然而，目前尚不清楚同步在神经计算中可能扮演什么角色，以及它可能提供什么功能优势。通过理论方法，我表明，当神经元具有异质性特征时，神经同步的计算意义就会显现出来。在这种情况下，刺激与神经同步之间的关系可以用同步感受野（synchrony receptive field）的概念来捕捉，即一组能够在一群神经元中引起同步反应的刺激。在异质的神经元群体中，同步模式似乎代表了刺激中的结构或感觉不变量，然后可以被突触后神经元检测到。具有依赖于尖峰时间的可塑性的所需神经回路可以自发出现。我通过不同感觉模态的例子表明，这使得简单的神经电路能够从现实的感觉刺激中提取相关信息，例如在存在干扰的情况下识别波动的气味。这种基于同步的计算理论表明，相对尖峰时间确实可能具有计算意义，并为具有吸引人的计算特性的感觉处理提出了新型神经网络模型。
