Odor supported place cell model and goal navigation in rodents (Kulvicius et al. 2008)

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Accession:118434
" ... Here we model odor supported place cells by using a simple feed-forward network and analyze the impact of olfactory cues on place cell formation and spatial navigation. The obtained place cells are used to solve a goal navigation task by a novel mechanism based on self-marking by odor patches combined with a Q-learning algorithm. We also analyze the impact of place cell remapping on goal directed behavior when switching between two environments. ..."
Reference:
1 . Kulvicius T, Tamosiunaite M, Ainge J, Dudchenko P, Wörgötter F (2008) Odor supported place cell model and goal navigation in rodents. J Comput Neurosci 25:481-500 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Connectionist Network;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
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Simulation Environment: MATLAB;
Model Concept(s): Rate-coding model neurons; Reinforcement Learning; Place cell/field; Spatial Navigation; Olfaction;
Implementer(s):
warning off MATLAB:griddata:DuplicateDataPoints

ti = 0:0.01:1; 
[X,Y] = meshgrid(ti,ti);

HPC=[];
wb=waitbar(0,'Please wait... Creating Place Fields.');

int=1:M;

for i=1:N
    HPC(:,:,i)=griddata(location(int,1)/envSize, location(int,2)/envSize, rate(int,i), X, Y);
    waitbar(i/N,wb);
end;
close(wb);

HPC(find(isnan(HPC)==1))=0;