Fox, C. and Prescott, T. (2009) Hippocampal formation as unitary coherent particle filter. In: Eighteenth Annual Computational Neuroscience Meeting: CNS 2009, 18–23 July 2009, Berlin, Germany.Full text not available from this repository.
A standard approach to localization, recall and prediction from sensors is the Hidden Markov Model (HMM, ), with location as hidden state and sense data as observations. Assuming that hippocampus performs a similar task, we present a new top-down mapping of this function onto its anatomy. In localization models of CA3 , firing rates of individual place cells encode probabilities over current location and recurrent connections may represent transitions probabilities between them. In auto-associative models , recurrent connections bring the network into a vector-coded memorized state. The existence of cells encoding rewards and locations of external objects supports this view .
|Item Type:||Conference or Workshop Item (Poster)|
|Copyright, Publisher and Additional Information:||© 2009 Fox and Prescott; licensee BioMed Central Ltd.|
|Institution:||The University of Sheffield|
|Academic Units:||The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield)|
|Depositing User:||Sheffield Import|
|Date Deposited:||05 Oct 2009 10:30|
|Last Modified:||08 Oct 2009 09:43|