Lefebvre Jérémie, Longtin André, Leblanc Victor G
J Biol Phys. 2011 Mar;37(2):189-212. doi: 10.1007/s10867-010-9207-3. Epub 2010 Nov 20.
A neural field model of ON and OFF cells with all-to-all inhibitory feedback is investigated. External spatiotemporal stimuli drive the ON and OFF cells with, respectively, direct and inverted polarity. The dynamic differences between networks built of ON and OFF cells ("ON/OFF") and those having only ON cells ("ON/ON") are described for the general case where ON and OFF cells can have different spontaneous firing rates; this asymmetric case is generic. Neural responses to nonhomogeneous static and time-periodic inputs are analyzed in regimes close to and away from self-oscillation. Static stimuli can cause oscillatory behavior for certain asymmetry levels. Time-periodic stimuli expose dynamical differences between ON/OFF and ON/ON nets. Outside the stimulated region, we show that ON/OFF nets exhibit frequency doubling, while ON/ON nets cannot. On the other hand, ON/ON networks show antiphase responses between stimulated and unstimulated regions, an effect that does not rely on specific receptive field circuitry. An analysis of the resonance properties of both net types reveals that ON/OFF nets exhibit larger response amplitude. Numerical simulations of the neural field models agree with theoretical predictions for localized static and time-periodic forcing. This is also the case for simulations of a network of noisy integrate-and-fire neurons. We finally discuss the application of the model to the electrosensory system and to frequency-doubling effects in retina.
研究了具有全对全抑制反馈的开(ON)细胞和关(OFF)细胞的神经场模型。外部时空刺激分别以直接极性和反转极性驱动ON细胞和OFF细胞。对于ON细胞和OFF细胞可以具有不同自发放电率的一般情况,描述了由ON细胞和OFF细胞构建的网络(“ON/OFF”)与仅具有ON细胞的网络(“ON/ON”)之间的动态差异;这种不对称情况是普遍存在的。在接近和远离自振荡的状态下,分析了对非均匀静态和时间周期输入的神经反应。对于某些不对称水平,静态刺激可导致振荡行为。时间周期刺激揭示了ON/OFF和ON/ON网络之间的动态差异。在受刺激区域之外,我们表明ON/OFF网络表现出倍频,而ON/ON网络则不会。另一方面,ON/ON网络在受刺激区域和未受刺激区域之间表现出反相反应,这种效应不依赖于特定的感受野电路。对两种网络类型的共振特性分析表明,ON/OFF网络表现出更大的响应幅度。神经场模型的数值模拟与局部静态和时间周期强迫的理论预测一致。对于有噪声的积分发放神经元网络的模拟也是如此。我们最后讨论了该模型在电感觉系统和视网膜倍频效应中的应用。