p586fig16.16 In the place cell learning model of (Gorchetnikov, Grossberg 2007), three populations of five cells each of entorhinal grid cells (only two are shown) with different spatial periods input to the model's dentate gyrus.  The grid cells are one-dimensional and defined algorithmically.  A model dentate gyrus granule cell that receives strong projections from all three grid cell scales fires (green cell) and activates a recurrent inhibitory interneuron that inhibits other granule cells.  It also generates back-propagating action potentials that trigger learning in the adaptive weights of the projections from the grid cells, thereby causing learning of place cell receptive fields.<BR>||  Grid-to-place Self-Organizing map (Gorchetnikov, Grossberg 2007).  Formation of place cell fields via grid-to-place cell learning.  Least common multiple: [grid (cm), place (m)] scales: [40, 50, 60 (cm); 6m], [50, 60, 70 (cm); 21m], [41, 53, 59 (cm); 1.282 km].  Our simulations: [40, 50 (cm); 2m], [44, 52 (cm); 5.72m].  Our SOM: Spiking Hodgkin-Huxley membrane equations; Nonlinear choice by contrast-enhancing recurrent on-center off-surround net;.  Choice triggers back-propagating action potentials that induce STDP-modulated learning on cell dendrites.