Lim Sukbin, McKee Jillian L, Woloszyn Luke, Amit Yali, Freedman David J, Sheinberg David L, Brunel Nicolas
Department of Neurobiology, University of Chicago, Chicago, Illinois, USA.
Department of Neuroscience, Columbia University, New York, New York, USA.
Nat Neurosci. 2015 Dec;18(12):1804-10. doi: 10.1038/nn.4158. Epub 2015 Nov 2.
Information about external stimuli is thought to be stored in cortical circuits through experience-dependent modifications of synaptic connectivity. These modifications of network connectivity should lead to changes in neuronal activity as a particular stimulus is repeatedly encountered. Here we ask what plasticity rules are consistent with the differences in the statistics of the visual response to novel and familiar stimuli in inferior temporal cortex, an area underlying visual object recognition. We introduce a method that allows one to infer the dependence of the presumptive learning rule on postsynaptic firing rate, and we show that the inferred learning rule exhibits depression for low postsynaptic rates and potentiation for high rates. The threshold separating depression from potentiation is strongly correlated with both mean and s.d. of the firing rate distribution. Finally, we show that network models implementing a rule extracted from data show stable learning dynamics and lead to sparser representations of stimuli.
外界刺激的信息被认为是通过依赖经验的突触连接修饰存储在皮层回路中的。随着特定刺激的反复出现，网络连接的这些修饰应该会导致神经元活动的变化。在这里，我们探讨什么样的可塑性规则与颞下皮层（视觉物体识别的一个基础区域）对新刺激和熟悉刺激的视觉反应统计差异相一致。我们引入了一种方法，该方法允许推断假定学习规则对突触后放电率的依赖性，并且我们表明推断出的学习规则在低突触后率时表现为抑制，在高突触后率时表现为增强。区分抑制和增强的阈值与放电率分布的均值和标准差都密切相关。最后，我们表明，实现从数据中提取的规则的网络模型表现出稳定的学习动态，并导致刺激的更稀疏表示。
