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Neural modeling of an internal clock (Yamazaki and Tanaka 2008)
 
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Model Information
Model File
Accession:
115966
"We studied a simple random recurrent inhibitory network. Despite its simplicity, the dynamics was so rich that activity patterns of neurons evolved with time without recurrence due to random recurrent connections among neurons. The sequence of activity patterns was generated by the trigger of an external signal, and the generation was stable against noise.... Therefore, a time passage from the trigger of an external signal could be represented by the sequence of activity patterns, suggesting that this model could work as an internal clock. ..."
Reference:
1 .
Yamazaki T, Tanaka S (2005) Neural modeling of an internal clock.
Neural Comput
17
:1032-58
[
PubMed
]
Citations
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Model Information
(Click on a link to find other models with that property)
Model Type:
Realistic Network;
Brain Region(s)/Organism:
Cerebellum;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
C or C++ program;
Model Concept(s):
Temporal Pattern Generation;
Spatio-temporal Activity Patterns;
Rate-coding model neurons;
Implementer(s):
/
internalclock
readme.html
button.png
*
Other models using button.png:
Robust Reservoir Generation by Correlation-Based Learning (Yamazaki & Tanaka 2008)
internalclock.c
Makefile
metainfo.txt
mt19937ar-cok.c
*
Other models using mt19937ar-cok.c:
Cerebellar gain and timing control model (Yamazaki & Tanaka 2007)(Yamazaki & Nagao 2012)
Robust Reservoir Generation by Correlation-Based Learning (Yamazaki & Tanaka 2008)
readout.dat
s.dat
s.png
similarity.c
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