DocumentCode
1948555
Title
Do Neural Models Scale up to a Human Brain?
Author
Belavkin, Roman V.
Author_Institution
Middlesex Univ., London
fYear
2007
fDate
12-17 Aug. 2007
Firstpage
2312
Lastpage
2317
Abstract
Models of cognition generally operate either at a micro or a macro level. It is not clear, however, if the micro models can predict the macroscopic properties of biological neural systems, such as the human brain. Here, I evaluate some hypotheses about the main functions of neural processing by scaling them to higher levels. Using neurobiological literature, I estimate the numbers of inputs and outputs of the entire nervous system. Then, I apply optimal control and information theories to predict the numbers of neurons required to implement these functions. The addition of constraints on connectivity leads to numerical estimates comparable to the numbers of neurons and synapses in human brain.
Keywords
brain models; cognition; information theory; neural nets; neurophysiology; optimal control; biological neural systems; cognition model; human brain synapsis; information theory; nervous system; neural models; neural processing; neurobiology; neurons; optimal control; Biological information theory; Biological system modeling; Brain modeling; Cognition; Humans; Information theory; Nervous system; Neurons; Optimal control; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location
Orlando, FL
ISSN
1098-7576
Print_ISBN
978-1-4244-1379-9
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2007.4371319
Filename
4371319
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