Temporal Encoding in a Nervous System

We examined the extent to which temporal encoding may be implemented by single neurons in the cercal sensory system of the house cricket Acheta domesticus. We found that these neurons exhibit a greater-than-expected coding capacity, due in part to an increased precision in brief patterns of action potentials. We developed linear and non-linear models for decoding the activity of these neurons. We found that the stimuli associated with short-interval patterns of spikes (ISIs of 8 ms or less) could be predicted better by second-order models as compared to linear models. Finally, we characterized the difference between these linear and second-order models in a low-dimensional subspace, and showed that modification of the linear models along only a few dimensions improved their predictive power to parity with the second order models. Together these results show that single neurons are capable of using temporal patterns of spikes as fundamental symbols in their neural code, and that they communicate specific stimulus distributions to subsequent neural structures.

本研究针对家蟋蟀（Acheta domesticus）尾须感觉系统内单个神经元实现时间编码的程度展开了探究。研究发现，此类神经元的编码能力超出预期，部分原因在于其动作电位短时程模式具备更高的精度。我们针对此类神经元的活动构建了线性与非线性解码模型。研究表明，相较于线性模型，二阶模型对短间隔峰电位模式（峰电位间期（Interspike Interval，简称ISI）≤8ms）对应的刺激的预测效果更优。最后，我们在低维子空间中对上述线性模型与二阶模型的差异进行了表征，并证实仅需对线性模型进行少量维度的调整，即可使其预测能力达到与二阶模型相当的水平。综合上述结果可知，单个神经元能够以峰电位的时间模式作为神经编码的基本符号，并可将特定的刺激分布传递至下游神经结构。