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Proceedings of the National Academy of Sciences of the United States of America logoLink to Proceedings of the National Academy of Sciences of the United States of America
. 1990 Sep;87(18):7200–7204. doi: 10.1073/pnas.87.18.7200

Global processing of visual stimuli in a neural network of coupled oscillators.

H Sompolinsky 1, D Golomb 1, D Kleinfeld 1
PMCID: PMC54711  PMID: 2402502

Abstract

An oscillator neural network model is presented that is capable of processing local and global attributes of sensory input. Local features in the input are encoded in the average firing rate of the neurons while the relationships between these features can modulate the temporal structure of the neuronal output. Neurons that share the same receptive field interact via relatively strong feedback connections, while neurons with different fields interact via specific, relatively weak connections. This pattern of connectivity mimics that of primary visual cortex. The model is studied in the context of processing visual stimuli that are coded for orientation. We compare our theoretical results with recent experimental evidence on coherent oscillatory activity in the cat visual cortex. The computational capabilities of the model for performing discrimination and segmentation tasks are demonstrated.

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

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