Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany.
International Max Planck Research School (IMPRS) for Neural Circuits, 60438, Frankfurt am Main, Germany.
Nat Commun. 2023 May 25;14(1):3021. doi: 10.1038/s41467-023-38587-2.
Parallel multisite recordings in the visual cortex of trained monkeys revealed that the responses of spatially distributed neurons to natural scenes are ordered in sequences. The rank order of these sequences is stimulus-specific and maintained even if the absolute timing of the responses is modified by manipulating stimulus parameters. The stimulus specificity of these sequences was highest when they were evoked by natural stimuli and deteriorated for stimulus versions in which certain statistical regularities were removed. This suggests that the response sequences result from a matching operation between sensory evidence and priors stored in the cortical network. Decoders trained on sequence order performed as well as decoders trained on rate vectors but the former could decode stimulus identity from considerably shorter response intervals than the latter. A simulated recurrent network reproduced similarly structured stimulus-specific response sequences, particularly once it was familiarized with the stimuli through non-supervised Hebbian learning. We propose that recurrent processing transforms signals from stationary visual scenes into sequential responses whose rank order is the result of a Bayesian matching operation. If this temporal code were used by the visual system it would allow for ultrafast processing of visual scenes.
在经过训练的猴子的视觉皮层中进行的并行多部位记录显示，对自然场景的空间分布神经元的反应按顺序排列。这些序列的等级顺序是刺激特异性的，即使通过操纵刺激参数来修改响应的绝对时间，也能保持不变。当这些序列由自然刺激引起时，它们的刺激特异性最高，而当去除某些统计规律时，刺激版本的特异性会降低。这表明响应序列是由感官证据和存储在皮质网络中的先验之间的匹配操作产生的。基于序列顺序训练的解码器与基于速率向量训练的解码器表现一样好，但前者可以从比后者短得多的响应间隔解码刺激身份。模拟的递归网络再现了类似结构的刺激特异性反应序列，尤其是在通过非监督赫布学习使网络熟悉刺激之后。我们提出，递归处理将来自静态视觉场景的信号转换为顺序响应，其等级顺序是贝叶斯匹配操作的结果。如果视觉系统使用这种时间码，它将允许对视觉场景进行超快速处理。
