Attractor neural network models of spatial maps in hippocampus
β Scribed by Misha Tsodyks
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 145 KB
- Volume
- 9
- Category
- Article
- ISSN
- 1050-9631
No coin nor oath required. For personal study only.
β¦ Synopsis
Hippocampal pyramidal neurons in rats are selectively activated at specific locations in an environment (O'Keefe and Dostrovsky, Brain Res 1971;34:171-175). Different cells are active in different places, therefore providing a faithful representation of the environment in which every spatial location is mapped to a particular population state of activity of place cells (
π SIMILAR VOLUMES
A typical back-propagation neural network (BPN) model is developed for modelling radio propagation for field strength prediction based on data measurements of propagation loss (in decibels) with terrain information taken in an urban area (Athens region) in the 900 MHz band. The feasibility of the BP
The model parameters in artiΓcial neural networks have a great inΓuence on the training speed. It can be increased after choosing the optimum parameters, which was performed by a stepping technique. The training speed using the method is usually faster than that when adopting random or empirical par