Maia Pedro D, Kutz J Nathan
Department of Applied Mathematics, University of Washington, 98195-3925, Seattle, WA, USA,
J Comput Neurosci. 2014 Oct;37(2):317-32. doi: 10.1007/s10827-014-0504-x. Epub 2014 Jun 12.
Axonal swellings are almost universal in neurodegenerative diseases of the central nervous system, including Alzheimer's and Parkinson's disease. Concussions and traumatic brain injuries can also produce cognitive and behavioral deficits by compromising neuronal morphology. Using a spike metric analysis, we characterize computationally the effects of such axonal varicosities on spike train propagation by comparing Poisson spike train classes before and after propagation through a prototypical axonal enlargement, or focused axonal swelling. Misclassification of spike train classes and low-pass filtering of firing rate activity increases with more pronounced axonal injury. We show that confusion matrices and a calculation of the loss of transmitted information provide a very practical way to characterize how injured neurons compromise the signal processing and faithful conductance of spike trains. The method demonstrates that (i) neural codes encoded with low firing rates are more robust to injury than those encoded with high firing rates, (ii) classification depends upon the length of the spike train used to encode information, and (iii) axonal injuries reduce the variance of spike trains within a given stimulus class. The work introduces a novel theoretical and computational framework to quantify the interplay between electrophysiological dynamics with focused axonal swellings generated by injury or other neurodegenerative processes. It further suggests how pharmacology and plasticity may play a role in recovery of neural computation. Ultimately, the work bridges vast experimental observations of in vitro morphological pathologies with post-traumatic cognitive and behavioral dysfunction.
轴突肿胀在包括阿尔茨海默病和帕金森病在内的中枢神经系统神经退行性疾病中几乎普遍存在。脑震荡和创伤性脑损伤也会通过损害神经元形态而导致认知和行为缺陷。通过尖峰度量分析,我们通过比较在通过典型轴突扩大或聚焦轴突肿胀传播之前和之后的泊松尖峰序列类别,从计算上表征了这种轴突曲张对尖峰序列传播的影响。随着轴突损伤更加明显,尖峰序列类别的错误分类和放电率活动的低通滤波会增加。我们表明,混淆矩阵和传输信息损失的计算提供了一种非常实用的方法来表征受损神经元如何损害尖峰序列的信号处理和忠实传导。该方法表明:(i)以低放电率编码的神经编码比以高放电率编码的神经编码对损伤更具鲁棒性;(ii)分类取决于用于编码信息的尖峰序列的长度;(iii)轴突损伤会降低给定刺激类别内尖峰序列的方差。这项工作引入了一个新颖的理论和计算框架,以量化电生理动力学与由损伤或其他神经退行性过程产生的聚焦轴突肿胀之间的相互作用。它进一步表明了药理学和可塑性在神经计算恢复中可能发挥的作用。最终,这项工作将体外形态病理学的大量实验观察结果与创伤后认知和行为功能障碍联系起来。