Name
Title | ||
|---|---|---|
Studying The Economy Of Energy Expenditure In A Large Balanced Spiking Neuron Network |
Abstract | ||
|---|---|---|
The link between neural activity and energy flows forms the basis of several forms of functional neuroimaging. Since the biophysics of neurovascular interactions is extremely complex, it would be worthwhile to investigate this question using simple computational models. Since neural networks are models of computation in the brain it would be interesting to study energy utilization in these models under various conditions of operation. In this paper, we study energy utilization in large, sparse spiking neuron network containing a mixture of excitatory and inhibitory neurons. In such a network, a balanced state, in which the total excitation and inhibition are designed to cancel out, has been considered to reflect the situation in real cortical networks. In our simulations, the network in balanced state is found to correspond to a state of minimum energy consumption very often. Such a state is also associated with low regularity of firing of individual neurons, and only moderate levels of synchrony across the network. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IJCNN.2010.5596857 | 2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010 |
Keywords | Field | DocType |
model of computation,neural nets,functional neuroimaging,energy expenditure,computer model,neurophysiology,computational models,energy flow,computational modeling,neural network | Neurophysiology,Random neural network,Computer science,Functional neuroimaging,Computational model,Model of computation,Artificial intelligence,Artificial neural network,Spiking neural network,Energy consumption,Machine learning | Conference |
ISSN | Citations | PageRank |
2161-4393 | 0 | 0.34 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hiroyasu Ando | 1 | 4 | 2.15 |
| K. Karthik | 2 | 0 | 0.34 |
| V. Srinivasa Chakravarthy | 3 | 118 | 14.15 |