Journal of Computational Neuroscience

, Volume 37, Issue 2, pp 317–332 | Cite as

Compromised axonal functionality after neurodegeneration, concussion and/or traumatic brain injury

  • Pedro D. MaiaEmail author
  • J. Nathan Kutz


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.


Neurodegenerative diseases Traumatic brain injury Concussion Alzheimer Parkinson Axonal Swellings Axonal Computation Spike train metrics 



We are especially grateful to Bingni Brunton, Steven Brunton, Borna Dabiri and Matthew Hemphill for discussions relating to the filtering and functionality of the injured axons. We also thank Eric Shea-Brown, Ben Lansdell and Alex Cayco-Gajic for helpful discussions relating to this work. Finally, we acknowledge our anonymous reviewers for pointing out other neurodegenerative diseases beyond TBI where our work could be potentially applied.

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Applied MathematicsUniversity of WashingtonSeattleUSA

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