@article{MTMT:1317888,
	title = {Episodes in space: A modeling study of hippocampal place representation},
	url = {https://m2.mtmt.hu/api/publication/1317888},
	author = {Ujfalussy, Balázs Benedek and Eros, P and Somogyvári, Zoltán and Kiss, Tamás},
	doi = {10.1007/978-3-540-69134-1_13},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {5040 LNAI},
	unique-id = {1317888},
	issn = {0302-9743},
	abstract = {A computer model of learning and representing spatial locations 
		is studied. The model builds on biological constraints and 
		assumptions drawn from the anatomy and physiology of the 
		hippocampal formation of the rat. The emphasis of the presented 
		research is on the usability of a computer model originally 
		proposed to describe episodic memory capabilities of the 
		hippocampus in a spatial task. In the present model two 
		modalities - vision and path integration - are contributing to 
		the recognition of a given place. We study how place cell 
		activity emerges due to Hebbian learning in the model 
		hippocampus as a result of random exploration of the 
		environment. The model is implemented in the Webots mobile 
		robotics simulation software. Our results show that the location 
		of the robot is well predictable from the activity of a 
		population of model place cells, thus the model is suitable to 
		be used as a basic building block of location-based navigation 
		strategies. However, some properties of the stored memories 
		strongly resembles that of episodic memories, which do not match 
		special spatial requirements. © 2008 Springer-Verlag Berlin 
		Heidelberg.},
	year = {2008},
	eissn = {1611-3349},
	pages = {123-136},
	orcid-numbers = {Ujfalussy, Balázs Benedek/0000-0002-2295-3828}
}