Simple cells (visual cortex)
This software has been realized by Ben Chandler at the CNS Technology Lab at Boston University (http://techlab.bu.edu/). The main author of the software is Ben Chandler ( http://www.neurdon.com/about-2/editors/ben-chandler/ )
This is a one-dimensional stand-alone implementation of the Grossberg and Todorović model of a cortical simple cell.
Reference
Grossberg, S. , Todorovic, D., Neural dynamics of 1-D and 2-D brightness perception: A unified model of classical and recent phenomena, Perception and Psychophysics, 43, 241-277 (1988).
Computer simulations of a neural network model of I-D and 2-D brightness phenomena are presented. The simulations indicate how configural image properties trigger interactions among spatially organized contrastive, boundary segmentation, and filling-in processes to generate emergent percepts. They provide the first unified mechanistic explanation of this set of phenomena, a number of which have received no previous mechanistic explanation. Network interactions between a Boundary Contour (BC) System and a Feature Contour (FC) System comprise the model. The BC System consists of a hierarchy of contrast-sensitive and orientationally tuned interactions, leading to a boundary segmentation. On and off geniculate cells and simple and complex cortical cells are modeled. Output signals from the BC System segmentation generate compartmental boundaries within the FC System. Contrast-sensitive inputs to the FC System generate a lateral filling-in of activation within FC System compartments. The filling-in process is defined by a nonlinear diffusion mechanism. Simulated phenomena include network responses to stimulus distributions that involve combinations of luminance steps, gradients, cusps, and corners of various sizes. These images include impossible staircases, bull's-eyes, nested combinations of luminance profiles, and images viewed under nonuniform illumination conditions. Simulated phenomena include variants of brightness constancy, brightness contrast, brightness assimilation, the Craik-O'Brien-Cornsweet effect, the Kofika-Benussi ring, the Kanizsa-Minguzzi anomalous brightness differentiation, the Hermann grid, and a Land Mondrian viewed under constant and gradient illumination that cannot be explained by retinex theory.
Code Description
This Matlab implementation includes stand-alone source code, simplecell.m, as well as documentation and a GUI-based example. For stand-alone use instructions, see how_to_run.pdf. Otherwise, run main_gui from Matlab to see the full GUI example.
Cite As
Massimiliano Versace (2026). Simple cells (visual cortex) (https://www.mathworks.com/matlabcentral/fileexchange/24796-simple-cells-visual-cortex), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform Compatibility
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- AI and Statistics > Deep Learning Toolbox >
- Sciences > Neuroscience > Behavior and Psychophysics >
- Sciences > Neuroscience > Neural Simulation >
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