Brown Eric, Moehlis Jeff, Holmes Philip
Program in Applied and Computational Mathematics, Princeton University, Princeton, NJ 08544, USA.
Neural Comput. 2004 Apr;16(4):673-715. doi: 10.1162/089976604322860668.
We undertake a probabilistic analysis of the response of repetitively firing neural populations to simple pulselike stimuli. Recalling and extending results from the literature, we compute phase response curves (PRCs) valid near bifurcations to periodic firing for Hindmarsh-Rose, Hodgkin-Huxley, FitzHugh-Nagumo, and Morris-Lecar models, encompassing the four generic (codimension one) bifurcations. Phase density equations are then used to analyze the role of the bifurcation, and the resulting PRC, in responses to stimuli. In particular, we explore the interplay among stimulus duration, baseline firing frequency, and population-level response patterns. We interpret the results in terms of the signal processing measure of gain and discuss further applications and experimentally testable predictions.
我们对重复发放脉冲的神经群体对简单脉冲状刺激的响应进行了概率分析。回顾并扩展文献中的结果，我们计算了在Hindmarsh-Rose、Hodgkin-Huxley、FitzHugh-Nagumo和Morris-Lecar模型中，接近分岔到周期性发放时有效的相位响应曲线（PRC），涵盖了四种一般（余维一）分岔。然后使用相位密度方程来分析分岔以及由此产生的PRC在对刺激的响应中的作用。特别是，我们探讨了刺激持续时间、基线发放频率和群体水平响应模式之间的相互作用。我们根据增益的信号处理度量来解释结果，并讨论进一步的应用和可通过实验检验的预测。
