Receptive Field and Feature Map Formation in the Primary Visual Cortex via Hebbian Learning with Inhibitory Feedback
نویسندگان
چکیده
A linear neural network is proposed for mamalian vision system in which backward connections from the primary visual cortex (V1) to the lateral geniculate nucleus play a key role. The backward connections control the flow of information from the LGN to V1 in such a way as to maximize the rate of transfer of information from the LGN to V1. The application of hebbian learning to the forward and backward connections causes the formation of receptive fields which are sensitive to edges, bars, and spatial frequencies of preferred orientations. Receptive field types in V1 are shown to depend on the density of the afferent connections in the LGN. Orientational preferences are organized in the primary visual cortex by the application of lateral interactions during the learning phase. Change in the size of the eye between the immature and mature animal is shown be an important factor in the development of V1 organization. The orgainization of the mature network is compared to that found in the macaque monkey by several analytical tests.
منابع مشابه
Receptive Field Encoding Model for Dynamic Natural Vision
Introduction: Encoding models are used to predict human brain activity in response to sensory stimuli. The purpose of these models is to explain how sensory information represent in the brain. Convolutional neural networks trained by images are capable of encoding magnetic resonance imaging data of humans viewing natural images. Considering the hemodynamic response function, these networks are ...
متن کاملCo-development of Visual Receptive Fields and Their Motor Primitive-based Decoding Scheme
Neurons in the primary visual cortex respond to specific patterns of visual input, i.e., the spikes encode visual feature properties. These patterns define the receptive field of the neurons. Receptive fields are known to become refined over time throughout development, and the process has been intensively studied both by neurophysiological and computational methods. The focus of these earlier ...
متن کاملTopographic Receptive Fields and Patterned Lateral Interaction in a Self-Organizing Model of the Primary Visual Cortex
This article presents a self-organizing neural network model for the simultaneous and cooperative development of topographic receptive fields and lateral interactions in cortical maps. Both afferent and lateral connections adapt by the same Hebbian mechanism in a purely local and unsupervised learning process. Afferent input weights of each neuron self-organize into hill-shaped profiles, recept...
متن کاملCORTICAL ORIENTATION MAP DEVELOPMENT FROM NATURAL IMAGES: THE ROLE OF CORTICAL RESPONSE AMPLIFICATION IN V1 CHRISTIAN PIEPENBROCK and KLAUS OBERMAYER
Simple cells in the primary visual cortex respond selectively to oriented stimuli. It has been proposed that such feature detecting neurons should generate a sparse representation of the visual world and orientation selective receptive fields are in this sense optimal spatial filters for “natural” visual environments. In this contribution we show that a competitive Hebbian development model dri...
متن کاملDevelopment of Maps of Simple and Complex Cells in the Primary Visual Cortex
Hubel and Wiesel (1962) classified primary visual cortex (V1) neurons as either simple, with responses modulated by the spatial phase of a sine grating, or complex, i.e., largely phase invariant. Much progress has been made in understanding how simple-cells develop, and there are now detailed computational models establishing how they can form topographic maps ordered by orientation preference....
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2005