DocumentCode :
61474
Title :
Firing Rate Propagation Through Neuronal–Astrocytic Network
Author :
Ying Liu ; Chunguang Li
Author_Institution :
Dept. of Inf. Sci. & Electron. Eng., Zhejiang Univ., Hangzhou, China
Volume :
24
Issue :
5
fYear :
2013
fDate :
May-13
Firstpage :
789
Lastpage :
799
Abstract :
Understanding the underlying mechanism of the propagation of neuronal activities within the brain is a fundamental issue in neuroscience. Traditionally, communication and information processing have been exclusively considered as the province of synaptic coupling between neurons. Astrocytes, however, have recently been acknowledged as active partners in neuronal information processing. So, it is more reasonable and accurate to study the nature of neuronal signal propagation with the participation of astrocytes. In this paper, we first propose a feedforward neuronal-astrocytic network (FNAsN), which includes the mutual neuron-astrocyte interaction. Besides, we also consider the unreliability of both the synaptic transmission between neurons and the coupling between neurons and astrocytes. Then, the performance of firing rate propagation through the proposed FNAsN is studied through a series of simulations. Results show that the astrocytes can mediate neuronal activities, and consequently improve the performance of firing rate propagation, especially in a weak and noisy environment. From this point of view, astrocytes can be regarded as a realistic internal source of noise, which collaborates with an externally applied weak noise to prevent synchronous neuron firing within the same layer and thus to ensure reliable transmission.
Keywords :
bioelectric phenomena; brain; cellular biophysics; feedforward neural nets; neurophysiology; synchronisation; FNAsN; astrocytes; brain; feedforward neuronal-astrocytic network; firing rate propagation; mutual neuron-astrocyte interaction; neuronal activity propagation; neuronal communication; neuronal information processing; neuronal signal propagation; neuroscience; synaptic coupling; synaptic transmission; synchronous neuron firing prevention; Calcium; Couplings; Erbium; Kinetic theory; Mathematical model; Neurons; Noise; Astrocyte; astrocytic field; firing rate; neuron–astrocyte interaction; signal propagation; unreliability;
fLanguage :
English
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
2162-237X
Type :
jour
DOI :
10.1109/TNNLS.2013.2245678
Filename :
6464601
Link To Document :
بازگشت