Ionic mechanisms underlying history-dependence of conduction delay in an unmyelinated axon

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Abstract

Axonal conduction velocity can change substantially during ongoing activity, thus modifying spike interval structures and, potentially, temporal coding. We used a biophysical model to unmask mechanisms underlying the history-dependence of conduction. The model replicates activity in the unmyelinated axon of the crustacean stomatogastric pyloric dilator neuron. At the timescale of a single burst, conduction delay has a non-monotonic relationship with instantaneous frequency, which depends on the gating rates of the fast voltage-gated Na⁺ current. At the slower timescale of minutes, the mean value and variability of conduction delay increase. These effects are due to hyperpolarization of the baseline membrane potential by the Na⁺/K⁺ pump, balanced by an h-current, both of which affect the gating of the Na⁺ current. We explore the mechanisms of history-dependence of conduction delay in axons and develop an empirical equation that accurately predicts this history-dependence, both in the model and in experimental measurements.

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Yang Zhang

Mathematical Sciences, New Jersey Institute of Technology, Newark, United States

Competing interests
The authors declare that no competing interests exist.
Dirk M Bucher

Biological Sceicnes, New Jersey Institute of Technology, Newark, United States

Competing interests
The authors declare that no competing interests exist.
Farzan Nadim

Biological Sciences, New Jersey Institute of Technology, Newark, United States

For correspondence
farzan@njit.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0003-4144-9042

Funding

National Institute of Neurological Disorders and Stroke (NS083319)

Dirk M Bucher
Farzan Nadim

National Institute of Mental Health (MH060505)

Farzan Nadim

National Institute of Neurological Disorders and Stroke (NS058825)

Dirk M Bucher

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

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