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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Belavkin, R.V. |
| Copyright Year | 2007 |
| Description | Author affiliation: Middlesex Univ., London (Belavkin, R.V.) |
| 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. |
| Starting Page | 2312 |
| Ending Page | 2317 |
| File Size | 506342 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424413799 |
| ISSN | 10987576 |
| DOI | 10.1109/IJCNN.2007.4371319 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-08-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Brain modeling Humans Biological system modeling Neurons Cognition Predictive models Biological information theory Nervous system Optimal control Information theory |
| Content Type | Text |
| Resource Type | Article |
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