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+# GCAL: Gain Control, Adaptation, Laterally connected
+
+Simple but robust single-population V1 model orientation map from:
+
+Jean-Luc R. Stevens, Judith S. Law, Jan Antolik, and James A. Bednar. 
+Mechanisms for stable, robust, and adaptive development of orientation 
+maps in the primary visual cortex. 
+*Journal of Neuroscience*, 33:15747-15766, 2013.
+
+Development of orientation maps in ferret and cat primary visual 
+cortex (V1) has been shown to be stable, in that the earliest 
+measurable maps are similar in form to the eventual adult map, 
+robust, in that similar maps develop in both dark rearing and in a 
+variety of normal visual environments, and yet adaptive, in that 
+the final map pattern reflects the statistics of the specific 
+visual environment. How can these three properties be reconciled? 
+Using mechanistic models of the development of neural connectivity 
+in V1, we show for the first time that realistic stable, robust, 
+and adaptive map development can be achieved by including two 
+low-level mechanisms originally motivated from single-neuron 
+results. Specifically, contrast-gain control in the retinal 
+ganglion cells and the lateral geniculate nucleus reduces variation 
+in the presynaptic drive due to differences in input patterns, 
+while homeostatic plasticity of V1 neuron excitability reduces the 
+postsynaptic variability in firing rates. Together these two 
+mechanisms, thought to be applicable across sensory systems in 
+general, lead to biological maps that develop stably and robustly, 
+yet adapt to the visual environment. The modeling results suggest 
+that topographic map stability is a natural outcome of low-level 
+processes of adaptation and normalization. The resulting model is 
+more realistic, simpler, and far more robust, and is thus a good 
+starting point for future studies of cortical map development.
+
+@article{Stevens02102013,  
+   author = {Stevens, Jean-Luc R. and Law, Judith S. and Antolik,  
+   Jan and Bednar, James A.},  
+   title = {Mechanisms for Stable, Robust, and Adaptive Development  
+   of Orientation Maps in the Primary Visual Cortex},  
+   journal = {*The Journal of Neuroscience*},  
+   volume = {33},  
+   number = {40},  
+   pages = {15747-15766},  
+   year = {2013},  
+   doi = {10.1523/JNEUROSCI.1037-13.2013},  
+   url = [http://www.jneurosci.org/content/33/40/15747.full](http://www.jneurosci.org/content/33/40/15747.full)  
+}
+
+# Running the model
+
+This model may be run with the Topographica simulator as follow:
+
+    ./topographica -g gcal.ty
+
+A suitable version of the Topographica simulator may be obtained using 
+git:
+
+    git clone https://github.com/ioam/topographica.git
+    cd topographica
+    git submodule update --init
+    git checkout GCALModelDB
+
+After 10000 iterations (~ 15 minutes on a quad-core 3Ghz machine), the 
+orientation map corresponding to the condition shown in Figure 9F can 
+be measured (GCAL model at 100% contrast). In the GUI, this may be 
+viewed by opening the Orientation Preference window (Plots -> 
+Preference Maps -> Orientation Preference).
+
+The default settings are appropriate for quick simulations, suitable 
+for regular exploratory work. An exact match to Figure 9E requires a 
+slower simulation:
+
+    ./topographica -p cortex_density=98 -p area=1.5 -g gcal.ty
+
+The linear density of cortical units is doubled for a cortical area of 
+1.5 x 1.5. Making the cortical area 2.25 times larger allows border 
+effects to be eliminated from the central 1.0 x 1.0 area. With four 
+times more cortical units due to the higher density, the overall 
+network is nine times larger.
+
+# Reproducing all published figures
+
+An IPython Notebook detailing how to reproduce the entire paper 
+(including all figures and simulations) may be viewed or run from 
+here:
+
+[http://topographica.org/_static/stevens_jn13.html](http://topographica.org/_static/stevens_jn13.html)
+
+---
+
+2025-07-09: Converted README to Markdown.