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• W2912239974 abstract "Pattern recognition is a fundamental neuronal process which enables a cortical system to interpret visual stimuli. How the brain learns to recognize patterns is, however, an unsolved problem. The frequently employed method of back propagation excels at this task but has been found to be unbiological in many aspects. In this Rapid Communication we achieve pattern recognition tasks in a biologically, fully consistent framework. We consider a neuronal network exhibiting avalanche dynamics, as observed experimentally, and implement negative feedback signals. These are chemical signals, such as dopamine, which mediate synaptic plasticity and sculpt the network to achieve certain tasks. The system is able to distinguish horizontal and vertical lines with high accuracy, as well as to perform well at the more complicated task of handwritten digit recognition. Resulting from the learning mechanism, spatially separate activity regions emerge, as observed in the primary visual cortex using functional magnetic resonance imaging techniques. The results therefore suggest that negative feedback signals offer an explanation for the emergence of distinct activity areas in the visual cortex." @default.
• W2912239974 created "2019-02-21" @default.
• W2912239974 creator A5004712124 @default.
• W2912239974 creator A5038868656 @default.
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• W2912239974 date "2019-01-22" @default.
• W2912239974 modified "2023-10-09" @default.
• W2912239974 title "Pattern recognition with neuronal avalanche dynamics" @default.
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• W2912239974 doi "https://doi.org/10.1103/physreve.99.010302" @default.
• W2912239974 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30780306" @default.
• W2912239974 hasPublicationYear "2019" @default.
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