Abstract
Recent work has explored a Kalman filter model of animal spatial learning the presence uncertainty in sensory as well as path integration estimates. This model was able to successfully account for several of the behavioral experiments reported in the animal navigation literature. This paper extends this model in some important directions. It accounts for the observed firing patterns of hippocampal neurons in visually symmetric environments that offer polarizing sensory cues. It incorporates mechanisms that allow for differential contribution from proximal and distal landmarks during localization. It also supports learning of associations between rewards and places to guide goal-directed navigation.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the International Joint Conference on Neural Networks |
| Publisher | IEEE |
| Pages | 27-32 |
| Number of pages | 6 |
| Volume | 1 |
| State | Published - 1999 |
| Event | International Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA Duration: Jul 10 1999 → Jul 16 1999 |
Other
| Other | International Joint Conference on Neural Networks (IJCNN'99) |
|---|---|
| City | Washington, DC, USA |
| Period | 7/10/99 → 7/16/99 |
All Science Journal Classification (ASJC) codes
- Software