Paper Info
Title
Determine Neuronal Tuning Curves by Exploring Optimum Firing Rate Distribution for Information Efficiency.
Abstract
This paper proposed a new method to determine the neuronal tuning curves for maximum information efficiency by computing the optimum firing rate distribution. Firstly, we proposed a general definition for the information efficiency, which is relevant to mutual information and neuronal energy consumption. The energy consumption is composed of two parts: neuronal basic energy consumption and neuronal spike emission energy consumption. A parameter to model the relative importance of energy consumption is introduced in the definition of the information efficiency. Then, we designed a combination of exponential functions to describe the optimum firing rate distribution based on the analysis of the dependency of the mutual information and the energy consumption on the shape of the functions of the firing rate distributions. Furthermore, we developed a rapid algorithm to search the parameter values of the optimum firing rate distribution function. Finally, we found with the rapid algorithm that a combination of two different exponential functions with two free parameters can describe the optimum firing rate distribution accurately. We also found that if the energy consumption is relatively unimportant (important) compared to the mutual information or the neuronal basic energy consumption is relatively large (small), the curve of the optimum firing rate distribution will be relatively flat (steep), and the corresponding optimum tuning curve exhibits a form of sigmoid if the stimuli distribution is normal.
Year
DOI
Venue
2017
10.3389/fncom.2017.00010
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
Keywords
Field
DocType
neuronal tuning curve,information efficiency,optimum firing rate distribution,mutual information,energy consumption
Exponential function,Search engine,Computer science,Artificial intelligence,Mutual information,Neuronal tuning,Distribution function,Energy consumption,Machine learning,Free parameter,Sigmoid function
Journal
Volume
ISSN
Citations 
11
1662-5188
0
PageRank 
References 
Authors
0.34
12
3
Name
Order
Citations
PageRank
fang han120.73
Zhijie Wang28911.14
Hong Fan321.06