Tests on cell assembly theory of the action of the brain, using a large digital computer
Neurocomputing: foundations of research
Self-organization of orientation sensitive cells in the striata cortex
Neurocomputing: foundations of research
The role of constraints in Hebbian learning
Neural Computation
What is the goal of sensory coding?
Neural Computation
Probabilistic interpretation of population codes
Neural Computation
Pattern-generator-driven development in self-organizing models
CNS '97 Proceedings of the sixth annual conference on Computational neuroscience : trends in research, 1998: trends in research, 1998
A Self-Organizing Neural Network Model Of The Primary Visual Cortex
A Self-Organizing Neural Network Model Of The Primary Visual Cortex
Tilt Aftereffects in a Self-Organizing Model of the Primary Visual Cortex
Tilt Aftereffects in a Self-Organizing Model of the Primary Visual Cortex
Parameter extraction from population codes: A critical assessment
Neural Computation
An efficient parallel algorithm for LISSOM neural network
Parallel Computing
Object recognition by artificial cortical maps
Neural Networks
A sparse generative model of v1 simple cells with intrinsic plasticity
Neural Computation
IEEE Transactions on Neural Networks
Visual cortex as a general-purpose information-processing device
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
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RF-LISSOM, a self-organizing model of laterally connected orientation maps in the primary visual cortex, was used to study the psychological phenomenon known as the tilt aftereffect. The same self-organizing processes that are responsible for the long-term development of the map are shown to result in tilt aftereffects over short timescales in the adult. The model permits simultaneous observation of large numbers of neurons and connections, making it possible to relate high-level phenomena to low-level events, which is difficult to do experimentally. The results give detailed computational support for the long-standing conjecture that the direct tilt aftereffect arises from adaptive lateral interactions between feature detectors. They also make a new prediction that the indirect effect results from the normalization of synaptic efficacies during this process. The model thus provides a unified computational explanation of self-organization and both the direct and indirect tilt aftereffect in the primary visual cortex.