Correlations of cortical Hebbian reverberations: theory versus experiment
Correlations of cortical Hebbian reverberations: theory versus experiment
复制标题
皮质赫布混响的相关性：理论与实验
作者：
D. Amit;N. Brunel;M. Tsodyks
从混响动力学的角度解释最近猴子前腹侧颞叶(AVT)皮层延迟匹配实验中延迟活动的单单位记录，我们提出了一个由准现实元素组成的模型神经网络，该模型非常详细地再现了实验结果。关于训练序列中连续刺激的邻接性的信息被嵌入到突触结构中，该信息表示训练是在固定时间序列中呈现的一组不相关的刺激上进行的。该模型非常准确地再现了对应于刺激的延迟活动分布与用于训练的不相关刺激之间的相关性。它还再现了作为刺激模式函数的样本细胞上的尖峰速率的活动分布。在我们看来，这是第一次在神经生理学水平上表现的计算现象在其所有量化方面得到再现。然后，该模型被用来预测这类实验的进一步生理学特征。这些包括相关性的进一步性质，作为刺激不同延迟活动分布的刺激的鉴别器的选择性细胞的特征，以及由给定模式产生的延迟活动中神经元之间的活动分布。该模型还对延迟活动对不同训练方案的依赖性具有预测意义。最后，我们讨论了这些模型与神经生理学之间相互作用的前景，以及它的局限性和可能的扩展。
Interpreting recent single-unit recordings of delay activities in delayed match-to-sample experiments in anterior ventral temporal (AVT) cortex of monkeys in terms of reverberation dynamics, we present a model neural network of quasi-realistic elements that reproduces the empirical results in great detail. Information about the contiguity of successive stimuli in the training sequence, representing the fact that training is done on a set of uncorrelated stimuli presented in a fixed temporal sequence, is embedded in the synaptic structure. The model reproduces quite accurately the correlations between delay activity distributions corresponding to stimulation with the uncorrelated stimuli used for training. It reproduces also the activity distributions of spike rates on sample cells as a function of the stimulating pattern. It is, in our view, the first time that a computational phenomenon, represented on the neurophysiological level, is reproduced in all its quantitative aspects. The model is then used to make predictions about further features of the physiology of such experiments. Those include further properties of the correlations, features of selective cells as discriminators of stimuli provoking different delay activity distributions, and activity distributions among the neurons in a delay activity produced by a given pattern. The model has predictive implications also for the dependence of the delay activities on different training protocols. Finally, we discuss the perspectives of the interplay between such models and neurophysiology as well as its limitations and possible extensions.