Cerebellar gain and timing control model (Yamazaki & Tanaka 2007)(Yamazaki & Nagao 2012)

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Accession:144416
This paper proposes a hypothetical computational mechanism for unified gain and timing control in the cerebellum. The hypothesis is justified by computer simulations of a large-scale spiking network model of the cerebellum.
References:
1 . Yamazaki T, Tanaka S (2007) A spiking network model for passage-of-time representation in the cerebellum. Eur J Neurosci 26:2279-92 [PubMed]
2 . Yamazaki T, Nagao S (2012) A computational mechanism for unified gain and timing control in the cerebellum. PLoS One 7:e33319 [PubMed]
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): Cerebellum Purkinje GABA cell; Cerebellum interneuron granule GLU cell; Cerebellum golgi cell; Cerebellum deep nucleus neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: C or C++ program;
Model Concept(s): Spatio-temporal Activity Patterns; Detailed Neuronal Models; Learning; Sensory processing;
Implementer(s): Yamazaki, Tadashi ;
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell; Cerebellum interneuron granule GLU cell;
#!/usr/bin/ruby

T = 2000
Binsize = 10
DT = 0.001

N = 102400
Input = "gr.spk.a1"
Output = "sum.dat"

ary = Array.new(T/Binsize)

IO.foreach(Input){|l|
  t, n = l.chomp.split
  ary[t.to_i/Binsize] = ary[t.to_i/Binsize].to_i + 1
}

open(Output, "w"){|o|
  ary.each_with_index{|n, i|
    o.puts "#{DT*i.to_f*Binsize} #{n.to_f/(N.to_f)}"
  }
}

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