Franzius, M and Sprekeler, H and Wiskott, L (2007) Slowness and sparseness lead to place, head-direction, and spatial-view cells. PLoS Comput Biol, 3. e166-.Full text not available from this repository.
We present a model for the self-organized formation of place cells, head-direction cells, and spatial-view cells in the hippocampal formation based on unsupervised learning on quasi-natural visual stimuli. The model comprises a hierarchy of Slow Feature Analysis (SFA) nodes, which were recently shown to reproduce many properties of complex cells in the early visual system . The system extracts a distributed grid-like representation of position and orientation, which is transcoded into a localized place-field, head-direction, or view representation, by sparse coding. The type of cells that develops depends solely on the relevant input statistics, i.e., the movement pattern of the simulated animal. The numerical simulations are complemented by a mathematical analysis that allows us to accurately predict the output of the top SFA layer.
|Uncontrolled Keywords:||Animals Computer Simulation Head Movements Hippocampus Models, Neurological Nerve Net Neurons, Afferent Orientation Rats Space Perception|
|Divisions:||Div F > Computational and Biological Learning|
|Depositing User:||Cron Job|
|Date Deposited:||09 Dec 2016 17:13|
|Last Modified:||30 Mar 2017 05:19|