Paper Info
Title
Input-output relation and energy efficiency in the neuron with different spike threshold dynamics.
Abstract
Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na+ and K+ currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism.
Year
DOI
Venue
2015
10.3389/fncom.2015.00062
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
Keywords
Field
DocType
spike threshold dynamic,input-output relation,energy efficiency,biophysical connection,spike initiation
Neuroscience,Biological system,Neural coding,Input/output,Artificial intelligence,Subthreshold conduction,Depolarization,Phase response curve,Threshold voltage,Mathematics,Hopf bifurcation,Bifurcation
Journal
Volume
Citations 
PageRank 
9
2
0.45
References 
Authors
15
5
Name
Order
Citations
PageRank
Guosheng Yi1228.16
Jiang Wang221446.99
K. M. Tsang38713.94
Xile Wei48817.97
Bin Deng5598.79