Hotspots of dendritic spine turnover facilitates new spines and NN sparsity (Frank et al 2018)

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Model for the following publication: Adam C. Frank, Shan Huang, Miou Zhou, Amos Gdalyahu, George Kastellakis, Panayiota Poirazi, Tawnie K. Silva, Ximiao Wen, Joshua T. Trachtenberg, and Alcino J. Silva Hotspots of Dendritic Spine Turnover Facilitate Learning-related Clustered Spine Addition and Network Sparsity
1 . Frank AC, Huang S, Zhou M, Gdalyahu A, Kastellakis G, Silva TK, Lu E, Wen X, Poirazi P, Trachtenberg JT, Silva AJ (2018) Hotspots of dendritic spine turnover facilitate clustered spine addition and learning and memory. Nat Commun 9:422 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Connectionist Network;
Brain Region(s)/Organism:
Cell Type(s): Abstract integrate-and-fire leaky neuron with dendritic subunits;
Gap Junctions:
Receptor(s): NMDA;
Simulation Environment: C or C++ program; MATLAB;
Model Concept(s): Active Dendrites; Synaptic Plasticity;
Implementer(s): Kastellakis, George [gkastel at];
Search NeuronDB for information about:  NMDA;
// test program mttest.cpp, see mtreadme.txt for information
#include "mtrand.h"
#include <cstdio>

int main() {
  unsigned long init[4] = {0x123, 0x234, 0x345, 0x456}, length = 4;
  MTRand_int32 irand(init, length); // 32-bit int generator
// this is an example of initializing by an array
// you may use MTRand(seed) with any 32bit integer
// as a seed for a simpler initialization
  MTRand drand; // double in [0, 1) generator, already init

// generate the same numbers as in the original C test program
  std::printf("1000 32-bit integer random numbers:\n");
  for (int i = 0; i < 1000; ++i) {
    std::printf("%10lu ", irand());
    if ((i % 5) == 4) std::printf("\n");
  std::printf("\n1000 random numbers in [0, 1):\n");
  for (int i = 0; i < 1000; ++i) {
    std::printf("%10.8f ", drand());
    if ((i % 5) == 4) std::printf("\n");