Title :
Do Neural Models Scale up to a Human Brain?
Author :
Belavkin, Roman V.
Author_Institution :
Middlesex Univ., London
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;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4371319