Modulation of neuronal excitability

在本财政年度，我们已经确定了最佳的刺激形状的神经元兴奋使用鱿鱼巨轴突作为模型系统。 这些实验采用兴奋性和抑制性突触后电位在计算机生成的随机时间传递到轴突。刺激的总体强度被滴定以产生相对不频繁的动作电位或尖峰。 从尖峰触发平均确定引起动作电位的电流输入的形状。 这些结果在产生尖峰所需的电流量最小的意义上是最佳的。 这项工作与用于治疗帕金森病患者运动障碍的脑深部电刺激（DBS）协议有关。 DBS中通常使用的刺激协议由矩形电流脉冲组成。 基于噪声的方法可能不仅在延长植入这些患者体内的电池组的电池寿命方面更有效，而且在治疗运动障碍方面也更有效。

During the current fiscal year we have determined optimal stimulus shapes for neuronal excitation using the squid giant axon as a model system. These experiments employed excitatory and inhibitory post-synaptic potentials delivered to the axon at computer-generated random times. The overall intensity of the stimulus was titrated to yield relatively infrequent action potentials, or spikes. The shapes of current input that elicited action potentials were determined from spike-triggered averaging. These results are optimal in the sense that minimal amounts of current were required to produce spikes. The work is relevant to deep brain stimulation (DBS) protocols used to treat movement disorders in patients with Parkinson's disease. The stimulation protocol typically used in DBS consists of rectangular current pulses. A noise based approach may be more efficacious not only in prolonging battery life of the battery pack implanted in these patients but also in a qualitative improvement in treatment of movement disorders.