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首页> 外文期刊>Journal of Computational Neuroscience >Sensory experience modifies spontaneous state dynamics in a large-scale barrel cortical model
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Sensory experience modifies spontaneous state dynamics in a large-scale barrel cortical model

机译：感官体验改变了大型桶状皮质模型中的自发状态动力学

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Experimental evidence suggests that spontaneous neuronal activity may shape and be shaped by sensory experience. However, we lack information on how sensory experience modulates the underlying synaptic dynamics and how such modulation influences the response of the network to future events. Here we study whether spike-timing-dependent plasticity (STDP) can mediate sensory-induced modifications in the spontaneous dynamics of a new large-scale model of layers II, III and IV of the rodent barrel cortex. Our model incorporates significant physiological detail, including the types of neurons present, the probabilities and delays of connections, and the STDP profiles at each excitatory synapse. We stimulated the neuronal network with a protocol of repeated sensory inputs resembling those generated by the protraction-retraction motion of whiskers when rodents explore their environment, and studied the changes in network dynamics. By applying dimensionality reduction techniques to the synaptic weight space, we show that the initial spontaneous state is modified by each repetition of the stimulus and that this reverberation of the sensory experience induces long-term, structured modifications in the synaptic weight space. The post-stimulus spontaneous state encodes a memory of the stimulus presented, since a different dynamical response is observed when the network is presented with shuffled stimuli. These results suggest that repeated exposure to the same sensory experience could induce long-term circuitry modifications via 'Hebbian' STDP plasticity.
机译：实验证据表明，自发性神经元活动可能会受到感官体验的影响。但是，我们缺乏有关感官体验如何调节潜在的突触动态以及这种调节如何影响网络对未来事件的响应的信息。在这里，我们研究是否依赖于时序定时的可塑性（STDP）可以介导啮齿动物的桶形皮质II，III和IV层的新型大规模模型的自发动力学中的感官诱导的修饰。我们的模型包含了重要的生理细节，包括当前神经元的类型，连接的概率和延迟以及每个兴奋性突触处的STDP分布图。我们用重复的感官输入协议刺激神经元网络，该协议类似于啮齿动物探索环境时晶须的伸缩运动所产生的感觉输入，并研究了网络动力学的变化。通过将降维技术应用于突触权重空间，我们表明，每次重复刺激都会改变初始自发状态，并且这种感觉回响会引起突触权重空间的长期结构性修改。刺激后的自发状态编码了所呈现刺激的记忆，因为当网络呈现为随机刺激时会观察到不同的动态响应。这些结果表明，重复暴露于相同的感官体验可能会通过“ Hebbian” STDP可塑性诱导长期的电路改变。

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