# Experiments and Statistics

### Experiment 1: 900 neurons, 2 spatially distinct patterns. Pattern is active for 10
cycles.

### Using Pearson Product Moment Correlation.

| 0 Runs | 200 Runs | 400 Runs |

Maximum Neurons | 10 | 30 | 31 |

A-A Correlation | -.0074 | .7585 | .7442 |

B-B Correlation | -.0067 | .6456 | .8077 |

A Self Correlation | .0068 | .1649 | .2110 |

B Self Correlation | -.0057 | .2175 | .2332 |

A-B Correlation | -.0073 | -.0068 | -.0351 |

**A-A and B-B Correlation shows reliable activation, A and B self
correlation shows persistence, and A-B correlation shows
uniqueness**.

### Experiment 2: 400 neurons, more acurate neural model (neurons either
inhibitory or excitatory but not both, and firing loses all activation).

### Exploring different patterns. All exhaustive so no spontaneous activation
needed. Patterns varied on locality.

###

| Local | Half Local | Interleaved |

Number of Runs | 300 | 350 | 1500 |

A-A Correlation | 1 | .9286 | .9900 |

B-B Correlation | 1 | .9492 | .9917 |

A Self Correlation | .9970 | .8821 | .8261 |

B Self Correlation | .9734 | .9562 | .9386 |

A-B Correlation | -1 | -.4973 | -.9826 |

**All of the patterns are learned**. Distance-biasing makes
it easier to learn, but even interleaved patterns are learned.